--- a/src/java.base/share/classes/java/util/random/RNGSupport.java Fri Jul 26 15:20:31 2019 -0300
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,1085 +0,0 @@
-/*
- * Copyright (c) 2013, 2019, 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.random;
-
-import java.util.Spliterator;
-import java.util.stream.DoubleStream;
-import java.util.stream.IntStream;
-import java.util.stream.LongStream;
-
-/**
- * Low-level utility methods helpful for implementing pseudorandom number generators.
- *
- * This class is mostly for library writers creating specific implementations of the
- * interface {@link RandomNumberGenerator}.
- *
- * @since 14
- */
-public class RNGSupport {
-
- /*
- * Implementation Overview.
- *
- * This class provides utility methods and constants frequently
- * useful in the implentation of pseudorandom number generators
- * that satisfy the interface {@link RandomNumberGenerator}.
- *
- * File organization: First some message strings, then the main
- * public methods, followed by a non-public base spliterator class.
- */
-
- // IllegalArgumentException messages
- static final String BAD_SIZE = "size must be non-negative";
- static final String BAD_DISTANCE = "jump distance must be finite, positive, and an exact integer";
- static final String BAD_BOUND = "bound must be positive";
- static final String BAD_FLOATING_BOUND = "bound must be finite and positive";
- static final String BAD_RANGE = "bound must be greater than origin";
-
- /* ---------------- public methods ---------------- */
-
- /**
- * Check a {@code long} proposed stream size for validity.
- *
- * @param streamSize the proposed stream size
- *
- * @throws IllegalArgumentException if {@code streamSize} is negative
- */
- public static void checkStreamSize(long streamSize) {
- if (streamSize < 0L)
- throw new IllegalArgumentException(BAD_SIZE);
- }
-
- /**
- * Check a {@code double} proposed jump distance for validity.
- *
- * @param distance the proposed jump distance
- *
- * @throws IllegalArgumentException if {@code size} not positive, finite, and an exact integer
- */
- public static void checkJumpDistance(double distance) {
- if (!(distance > 0.0 && distance < Float.POSITIVE_INFINITY
- && distance == Math.floor(distance))) {
- throw new IllegalArgumentException(BAD_DISTANCE);
- }
- }
-
- /**
- * Checks a {@code float} upper bound value for validity.
- *
- * @param bound the upper bound (exclusive)
- *
- * @throws IllegalArgumentException if {@code bound} is not positive and finite
- */
- public static void checkBound(float bound) {
- if (!(bound > 0.0 && bound < Float.POSITIVE_INFINITY)) {
- throw new IllegalArgumentException(BAD_FLOATING_BOUND);
- }
- }
-
- /**
- * Checks a {@code double} upper bound value for validity.
- *
- * @param bound the upper bound (exclusive)
- *
- * @throws IllegalArgumentException if {@code bound} is not positive and finite
- */
- public static void checkBound(double bound) {
- if (!(bound > 0.0 && bound < Double.POSITIVE_INFINITY)) {
- throw new IllegalArgumentException(BAD_FLOATING_BOUND);
- }
- }
-
- /**
- * Checks an {@code int} upper bound value for validity.
- *
- * @param bound the upper bound (exclusive)
- *
- * @throws IllegalArgumentException if {@code bound} is not positive
- */
- public static void checkBound(int bound) {
- if (bound <= 0) {
- throw new IllegalArgumentException(BAD_BOUND);
- }
- }
-
- /**
- * Checks a {@code long} upper bound value for validity.
- *
- * @param bound the upper bound (exclusive)
- *
- * @throws IllegalArgumentException if {@code bound} is not positive
- */
- public static void checkBound(long bound) {
- if (bound <= 0) {
- throw new IllegalArgumentException(BAD_BOUND);
- }
- }
-
- /**
- * Checks a {@code float} range for validity.
- *
- * @param origin the least value (inclusive) in the range
- * @param bound the upper bound (exclusive) of the range
- *
- * @throws IllegalArgumentException unless {@code origin} is finite, {@code bound} is finite,
- * and {@code bound - origin} is finite
- */
- public static void checkRange(float origin, float bound) {
- if (!(origin < bound && (bound - origin) < Float.POSITIVE_INFINITY)) {
- throw new IllegalArgumentException(BAD_RANGE);
- }
- }
-
- /**
- * Checks a {@code double} range for validity.
- *
- * @param origin the least value (inclusive) in the range
- * @param bound the upper bound (exclusive) of the range
- *
- * @throws IllegalArgumentException unless {@code origin} is finite, {@code bound} is finite,
- * and {@code bound - origin} is finite
- */
- public static void checkRange(double origin, double bound) {
- if (!(origin < bound && (bound - origin) < Double.POSITIVE_INFINITY)) {
- throw new IllegalArgumentException(BAD_RANGE);
- }
- }
-
- /**
- * Checks an {@code int} range for validity.
- *
- * @param origin the least value that can be returned
- * @param bound the upper bound (exclusive) for the returned value
- *
- * @throws IllegalArgumentException if {@code origin} is greater than or equal to {@code bound}
- */
- public static void checkRange(int origin, int bound) {
- if (origin >= bound) {
- throw new IllegalArgumentException(BAD_RANGE);
- }
- }
-
- /**
- * Checks a {@code long} range for validity.
- *
- * @param origin the least value that can be returned
- * @param bound the upper bound (exclusive) for the returned value
- *
- * @throws IllegalArgumentException if {@code origin} is greater than or equal to {@code bound}
- */
- public static void checkRange(long origin, long bound) {
- if (origin >= bound) {
- throw new IllegalArgumentException(BAD_RANGE);
- }
- }
-
- /**
- * Given an array of seed bytes of any length, construct an array
- * of {@code long} seed values of length {@code n}, such that the
- * last {@code z} values are not all zero.
- *
- * @param seed an array of {@code byte} values
- * @param n the length of the result array (should be nonnegative)
- * @param z the number of trailing result elements that are required
- * to be not all zero (should be nonnegative but not larger
- * than {@code n})
- *
- * @return an array of length {@code n} containing {@code long} seed values
- */
- public static long[] convertSeedBytesToLongs(byte[] seed, int n, int z) {
- final long[] result = new long[n];
- final int m = Math.min(seed.length, n << 3);
- // Distribute seed bytes into the words to be formed.
- for (int j = 0; j < m; j++) {
- result[j>>3] = (result[j>>3] << 8) | seed[j];
- }
- // If there aren't enough seed bytes for all the words we need,
- // use a SplitMix-style PRNG to fill in the rest.
- long v = result[0];
- for (int j = (m + 7) >> 3; j < n; j++) {
- result[j] = mixMurmur64(v += SILVER_RATIO_64);
- }
- // Finally, we need to make sure the last z words are not all zero.
- search: {
- for (int j = n - z; j < n; j++) {
- if (result[j] != 0) break search;
- }
- // If they are, fill in using a SplitMix-style PRNG.
- // Using "& ~1L" in the next line defends against the case z==1
- // by guaranteeing that the first generated value will be nonzero.
- long w = result[0] & ~1L;
- for (int j = n - z; j < n; j++) {
- result[j] = mixMurmur64(w += SILVER_RATIO_64);
- }
- }
- return result;
- }
-
- /**
- * Given an array of seed bytes of any length, construct an array
- * of {@code int} seed values of length {@code n}, such that the
- * last {@code z} values are not all zero.
- *
- * @param seed an array of {@code byte} values
- * @param n the length of the result array (should be nonnegative)
- * @param z the number of trailing result elements that are required
- * to be not all zero (should be nonnegative but not larger
- * than {@code n})
- *
- * @return an array of length {@code n} containing {@code int} seed values
- */
- public static int[] convertSeedBytesToInts(byte[] seed, int n, int z) {
- final int[] result = new int[n];
- final int m = Math.min(seed.length, n << 2);
- // Distribute seed bytes into the words to be formed.
- for (int j = 0; j < m; j++) {
- result[j>>2] = (result[j>>2] << 8) | seed[j];
- }
- // If there aren't enough seed bytes for all the words we need,
- // use a SplitMix-style PRNG to fill in the rest.
- int v = result[0];
- for (int j = (m + 3) >> 2; j < n; j++) {
- result[j] = mixMurmur32(v += SILVER_RATIO_32);
- }
- // Finally, we need to make sure the last z words are not all zero.
- search: {
- for (int j = n - z; j < n; j++) {
- if (result[j] != 0) break search;
- }
- // If they are, fill in using a SplitMix-style PRNG.
- // Using "& ~1" in the next line defends against the case z==1
- // by guaranteeing that the first generated value will be nonzero.
- int w = result[0] & ~1;
- for (int j = n - z; j < n; j++) {
- result[j] = mixMurmur32(w += SILVER_RATIO_32);
- }
- }
- return result;
- }
-
- /*
- * Bounded versions of nextX methods used by streams, as well as
- * the public nextX(origin, bound) methods. These exist mainly to
- * avoid the need for multiple versions of stream spliterators
- * across the different exported forms of streams.
- */
-
- /**
- * This is the form of {@code nextLong} used by a {@link LongStream}
- * {@link Spliterator} and by the public method
- * {@code nextLong(origin, bound)}. If {@code origin} is greater
- * than {@code bound}, then this method simply calls the unbounded
- * version of {@code nextLong()}, choosing pseudorandomly from
- * among all 2<sup>64</sup> possible {@code long} values}, and
- * otherwise uses one or more calls to {@code nextLong()} to
- * choose a value pseudorandomly from the possible values
- * between {@code origin} (inclusive) and {@code bound} (exclusive).
- *
- * @implNote This method first calls {@code nextLong()} to obtain
- * a {@code long} value that is assumed to be pseudorandomly
- * chosen uniformly and independently from the 2<sup>64</sup>
- * possible {@code long} values (that is, each of the 2<sup>64</sup>
- * possible long values is equally likely to be chosen).
- * Under some circumstances (when the specified range is not
- * a power of 2), {@code nextLong()} may be called additional times
- * to ensure that that the values in the specified range are
- * equally likely to be chosen (provided the assumption holds).
- * <p>
- * The implementation considers four cases:
- * <ol>
- *
- * <li> If the {@code} bound} is less than or equal to the {@code origin}
- * (indicated an unbounded form), the 64-bit {@code long} value
- * obtained from {@code nextLong()} is returned directly.
- *
- * <li> Otherwise, if the length <i>n</i> of the specified range is an
- * exact power of two 2<sup><i>m</i></sup> for some integer
- * <i>m</i>, then return the sum of {@code origin} and the
- * <i>m</i> lowest-order bits of the value from {@code nextLong()}.
- *
- * <li> Otherwise, if the length <i>n</i> of the specified range
- * is less than 2<sup>63</sup>, then the basic idea is to use the
- * remainder modulo <i>n</i> of the value from {@code nextLong()},
- * but with this approach some values will be over-represented.
- * Therefore a loop is used to avoid potential bias by rejecting
- * candidates that are too large. Assuming that the results from
- * {@code nextLong()} are truly chosen uniformly and independently,
- * the expected number of iterations will be somewhere between
- * 1 and 2, depending on the precise value of <i>n</i>.
- *
- * <li> Otherwise, the length <i>n</i> of the specified range
- * cannot be represented as a positive {@code long} value.
- * A loop repeatedly calls {@code nextlong()} until obtaining
- * a suitable candidate, Again, the expected number of iterations
- * is less than 2.
- *
- * </ol>
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code long} values
- * @param origin the least value that can be produced,
- * unless greater than or equal to {@code bound}
- * @param bound the upper bound (exclusive), unless {@code origin}
- * is greater than or equal to {@code bound}
- *
- * @return a pseudorandomly chosen {@code long} value,
- * which will be between {@code origin} (inclusive) and
- * {@code bound} exclusive unless {@code origin}
- * is greater than or equal to {@code bound}
- */
- public static long boundedNextLong(RandomNumberGenerator rng, long origin, long bound) {
- long r = rng.nextLong();
- if (origin < bound) {
- // It's not case (1).
- final long n = bound - origin;
- final long m = n - 1;
- if ((n & m) == 0L) {
- // It is case (2): length of range is a power of 2.
- r = (r & m) + origin;
- } else if (n > 0L) {
- // It is case (3): need to reject over-represented candidates.
- /* This loop takes an unlovable form (but it works):
- because the first candidate is already available,
- we need a break-in-the-middle construction,
- which is concisely but cryptically performed
- within the while-condition of a body-less for loop. */
- for (long u = r >>> 1; // ensure nonnegative
- u + m - (r = u % n) < 0L; // rejection check
- u = rng.nextLong() >>> 1) // retry
- ;
- r += origin;
- }
- else {
- // It is case (4): length of range not representable as long.
- while (r < origin || r >= bound)
- r = rng.nextLong();
- }
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextLong} used by the public method
- * {@code nextLong(bound)}. This is essentially a version of
- * {@code boundedNextLong(origin, bound)} that has been
- * specialized for the case where the {@code origin} is zero
- * and the {@code bound} is greater than zero. The value
- * returned is chosen pseudorandomly from nonnegative integer
- * values less than {@code bound}.
- *
- * @implNote This method first calls {@code nextLong()} to obtain
- * a {@code long} value that is assumed to be pseudorandomly
- * chosen uniformly and independently from the 2<sup>64</sup>
- * possible {@code long} values (that is, each of the 2<sup>64</sup>
- * possible long values is equally likely to be chosen).
- * Under some circumstances (when the specified range is not
- * a power of 2), {@code nextLong()} may be called additional times
- * to ensure that that the values in the specified range are
- * equally likely to be chosen (provided the assumption holds).
- * <p>
- * The implementation considers two cases:
- * <ol>
- *
- * <li> If {@code bound} is an exact power of two 2<sup><i>m</i></sup>
- * for some integer <i>m</i>, then return the sum of {@code origin}
- * and the <i>m</i> lowest-order bits of the value from
- * {@code nextLong()}.
- *
- * <li> Otherwise, the basic idea is to use the remainder modulo
- * <i>bound</i> of the value from {@code nextLong()},
- * but with this approach some values will be over-represented.
- * Therefore a loop is used to avoid potential bias by rejecting
- * candidates that vare too large. Assuming that the results from
- * {@code nextLong()} are truly chosen uniformly and independently,
- * the expected number of iterations will be somewhere between
- * 1 and 2, depending on the precise value of <i>bound</i>.
- *
- * </ol>
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code long} values
- * @param bound the upper bound (exclusive); must be greater than zero
- *
- * @return a pseudorandomly chosen {@code long} value
- */
- public static long boundedNextLong(RandomNumberGenerator rng, long bound) {
- // Specialize boundedNextLong for origin == 0, bound > 0
- final long m = bound - 1;
- long r = rng.nextLong();
- if ((bound & m) == 0L) {
- // The bound is a power of 2.
- r &= m;
- } else {
- // Must reject over-represented candidates
- /* This loop takes an unlovable form (but it works):
- because the first candidate is already available,
- we need a break-in-the-middle construction,
- which is concisely but cryptically performed
- within the while-condition of a body-less for loop. */
- for (long u = r >>> 1;
- u + m - (r = u % bound) < 0L;
- u = rng.nextLong() >>> 1)
- ;
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextInt} used by an {@link IntStream}
- * {@link Spliterator} and by the public method
- * {@code nextInt(origin, bound)}. If {@code origin} is greater
- * than {@code bound}, then this method simply calls the unbounded
- * version of {@code nextInt()}, choosing pseudorandomly from
- * among all 2<sup>64</sup> possible {@code int} values}, and
- * otherwise uses one or more calls to {@code nextInt()} to
- * choose a value pseudorandomly from the possible values
- * between {@code origin} (inclusive) and {@code bound} (exclusive).
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code int} values
- * @param origin the least value that can be produced,
- * unless greater than or equal to {@code bound}
- * @param bound the upper bound (exclusive), unless {@code origin}
- * is greater than or equal to {@code bound}
- *
- * @return a pseudorandomly chosen {@code int} value,
- * which will be between {@code origin} (inclusive) and
- * {@code bound} exclusive unless {@code origin}
- * is greater than or equal to {@code bound}
- *
- * @implNote The implementation of this method is identical to
- * the implementation of {@code nextLong(origin, bound)}
- * except that {@code int} values and the {@code nextInt()}
- * method are used rather than {@code long} values and the
- * {@code nextLong()} method.
- */
- public static int boundedNextInt(RandomNumberGenerator rng, int origin, int bound) {
- int r = rng.nextInt();
- if (origin < bound) {
- // It's not case (1).
- final int n = bound - origin;
- final int m = n - 1;
- if ((n & m) == 0) {
- // It is case (2): length of range is a power of 2.
- r = (r & m) + origin;
- } else if (n > 0) {
- // It is case (3): need to reject over-represented candidates.
- for (int u = r >>> 1;
- u + m - (r = u % n) < 0;
- u = rng.nextInt() >>> 1)
- ;
- r += origin;
- }
- else {
- // It is case (4): length of range not representable as long.
- while (r < origin || r >= bound) {
- r = rng.nextInt();
- }
- }
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextInt} used by the public method
- * {@code nextInt(bound)}. This is essentially a version of
- * {@code boundedNextInt(origin, bound)} that has been
- * specialized for the case where the {@code origin} is zero
- * and the {@code bound} is greater than zero. The value
- * returned is chosen pseudorandomly from nonnegative integer
- * values less than {@code bound}.
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code long} values
- * @param bound the upper bound (exclusive); must be greater than zero
- *
- * @return a pseudorandomly chosen {@code long} value
- *
- * @implNote The implementation of this method is identical to
- * the implementation of {@code nextLong(bound)}
- * except that {@code int} values and the {@code nextInt()}
- * method are used rather than {@code long} values and the
- * {@code nextLong()} method.
- */
- public static int boundedNextInt(RandomNumberGenerator rng, int bound) {
- // Specialize boundedNextInt for origin == 0, bound > 0
- final int m = bound - 1;
- int r = rng.nextInt();
- if ((bound & m) == 0) {
- // The bound is a power of 2.
- r &= m;
- } else {
- // Must reject over-represented candidates
- for (int u = r >>> 1;
- u + m - (r = u % bound) < 0;
- u = rng.nextInt() >>> 1)
- ;
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextDouble} used by a {@link DoubleStream}
- * {@link Spliterator} and by the public method
- * {@code nextDouble(origin, bound)}. If {@code origin} is greater
- * than {@code bound}, then this method simply calls the unbounded
- * version of {@code nextDouble()}, and otherwise scales and translates
- * the result of a call to {@code nextDouble()} so that it lies
- * between {@code origin} (inclusive) and {@code bound} (exclusive).
- *
- * @implNote The implementation considers two cases:
- * <ol>
- *
- * <li> If the {@code bound} is less than or equal to the {@code origin}
- * (indicated an unbounded form), the 64-bit {@code double} value
- * obtained from {@code nextDouble()} is returned directly.
- *
- * <li> Otherwise, the result of a call to {@code nextDouble} is
- * multiplied by {@code (bound - origin)}, then {@code origin}
- * is added, and then if this this result is not less than
- * {@code bound} (which can sometimes occur because of rounding),
- * it is replaced with the largest {@code double} value that
- * is less than {@code bound}.
- *
- * </ol>
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code double} values
- * @param origin the least value that can be produced,
- * unless greater than or equal to {@code bound}; must be finite
- * @param bound the upper bound (exclusive), unless {@code origin}
- * is greater than or equal to {@code bound}; must be finite
- * @return a pseudorandomly chosen {@code double} value,
- * which will be between {@code origin} (inclusive) and
- * {@code bound} exclusive unless {@code origin}
- * is greater than or equal to {@code bound},
- * in which case it will be between 0.0 (inclusive)
- * and 1.0 (exclusive)
- */
- public static double boundedNextDouble(RandomNumberGenerator rng, double origin, double bound) {
- double r = rng.nextDouble();
- if (origin < bound) {
- r = r * (bound - origin) + origin;
- if (r >= bound) // may need to correct a rounding problem
- r = Double.longBitsToDouble(Double.doubleToLongBits(bound) - 1);
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextDouble} used by the public method
- * {@code nextDouble(bound)}. This is essentially a version of
- * {@code boundedNextDouble(origin, bound)} that has been
- * specialized for the case where the {@code origin} is zero
- * and the {@code bound} is greater than zero.
- *
- * @implNote The result of a call to {@code nextDouble} is
- * multiplied by {@code bound}, and then if this result is
- * not less than {@code bound} (which can sometimes occur
- * because of rounding), it is replaced with the largest
- * {@code double} value that is less than {@code bound}.
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code double} values
- * @param bound the upper bound (exclusive); must be finite and
- * greater than zero
- * @return a pseudorandomly chosen {@code double} value
- * between zero (inclusive) and {@code bound} (exclusive)
- */
- public static double boundedNextDouble(RandomNumberGenerator rng, double bound) {
- // Specialize boundedNextDouble for origin == 0, bound > 0
- double r = rng.nextDouble();
- r = r * bound;
- if (r >= bound) // may need to correct a rounding problem
- r = Double.longBitsToDouble(Double.doubleToLongBits(bound) - 1);
- return r;
- }
-
- /**
- * This is the form of {@code nextFloat} used by a {@code Stream<Float>}
- * {@link Spliterator} (if there were any) and by the public method
- * {@code nextFloat(origin, bound)}. If {@code origin} is greater
- * than {@code bound}, then this method simply calls the unbounded
- * version of {@code nextFloat()}, and otherwise scales and translates
- * the result of a call to {@code nextFloat()} so that it lies
- * between {@code origin} (inclusive) and {@code bound} (exclusive).
- *
- * @implNote The implementation of this method is identical to
- * the implementation of {@code nextDouble(origin, bound)}
- * except that {@code float} values and the {@code nextFloat()}
- * method are used rather than {@code double} values and the
- * {@code nextDouble()} method.
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code float} values
- * @param origin the least value that can be produced,
- * unless greater than or equal to {@code bound}; must be finite
- * @param bound the upper bound (exclusive), unless {@code origin}
- * is greater than or equal to {@code bound}; must be finite
- * @return a pseudorandomly chosen {@code float} value,
- * which will be between {@code origin} (inclusive) and
- * {@code bound} exclusive unless {@code origin}
- * is greater than or equal to {@code bound},
- * in which case it will be between 0.0 (inclusive)
- * and 1.0 (exclusive)
- */
- public static float boundedNextFloat(RandomNumberGenerator rng, float origin, float bound) {
- float r = rng.nextFloat();
- if (origin < bound) {
- r = r * (bound - origin) + origin;
- if (r >= bound) // may need to correct a rounding problem
- r = Float.intBitsToFloat(Float.floatToIntBits(bound) - 1);
- }
- return r;
- }
-
- /**
- * This is the form of {@code nextFloat} used by the public method
- * {@code nextFloat(bound)}. This is essentially a version of
- * {@code boundedNextFloat(origin, bound)} that has been
- * specialized for the case where the {@code origin} is zero
- * and the {@code bound} is greater than zero.
- *
- * @implNote The implementation of this method is identical to
- * the implementation of {@code nextDouble(bound)}
- * except that {@code float} values and the {@code nextFloat()}
- * method are used rather than {@code double} values and the
- * {@code nextDouble()} method.
- *
- * @param rng a random number generator to be used as a
- * source of pseudorandom {@code float} values
- * @param bound the upper bound (exclusive); must be finite and
- * greater than zero
- * @return a pseudorandomly chosen {@code float} value
- * between zero (inclusive) and {@code bound} (exclusive)
- */
- public static float boundedNextFloat(RandomNumberGenerator rng, float bound) {
- // Specialize boundedNextFloat for origin == 0, bound > 0
- float r = rng.nextFloat();
- r = r * bound;
- if (r >= bound) // may need to correct a rounding problem
- r = Float.intBitsToFloat(Float.floatToIntBits(bound) - 1);
- return r;
- }
-
- // The following decides which of two strategies initialSeed() will use.
- private static boolean secureRandomSeedRequested() {
- String pp = java.security.AccessController.doPrivileged(
- new sun.security.action.GetPropertyAction(
- "java.util.secureRandomSeed"));
- return (pp != null && pp.equalsIgnoreCase("true"));
- }
-
- private static final boolean useSecureRandomSeed = secureRandomSeedRequested();
-
- /**
- * Returns a {@code long} value (chosen from some
- * machine-dependent entropy source) that may be useful for
- * initializing a source of seed values for instances of {@link RandomNumberGenerator}
- * created by zero-argument constructors. (This method should
- * <i>not</i> be called repeatedly, once per constructed
- * object; at most it should be called once per class.)
- *
- * @return a {@code long} value, randomly chosen using
- * appropriate environmental entropy
- */
- public static long initialSeed() {
- if (useSecureRandomSeed) {
- byte[] seedBytes = java.security.SecureRandom.getSeed(8);
- long s = (long)(seedBytes[0]) & 0xffL;
- for (int i = 1; i < 8; ++i)
- s = (s << 8) | ((long)(seedBytes[i]) & 0xffL);
- return s;
- }
- return (mixStafford13(System.currentTimeMillis()) ^
- mixStafford13(System.nanoTime()));
- }
-
- /**
- * The first 32 bits of the golden ratio (1+sqrt(5))/2, forced to be odd.
- * Useful for producing good Weyl sequences or as an arbitrary nonzero odd value.
- */
- public static final int GOLDEN_RATIO_32 = 0x9e3779b9;
-
- /**
- * The first 64 bits of the golden ratio (1+sqrt(5))/2, forced to be odd.
- * Useful for producing good Weyl sequences or as an arbitrary nonzero odd value.
- */
- public static final long GOLDEN_RATIO_64 = 0x9e3779b97f4a7c15L;
-
- /**
- * The first 32 bits of the silver ratio 1+sqrt(2), forced to be odd.
- * Useful for producing good Weyl sequences or as an arbitrary nonzero odd value.
- */
- public static final int SILVER_RATIO_32 = 0x6A09E667;
-
- /**
- * The first 64 bits of the silver ratio 1+sqrt(2), forced to be odd.
- * Useful for producing good Weyl sequences or as an arbitrary nonzero odd value.
- */
- public static final long SILVER_RATIO_64 = 0x6A09E667F3BCC909L;
-
- /**
- * Computes the 64-bit mixing function for MurmurHash3.
- * This is a 64-bit hashing function with excellent avalanche statistics.
- * https://github.com/aappleby/smhasher/wiki/MurmurHash3
- *
- * Note that if the argument {@code z} is 0, the result is 0.
- *
- * @param z any long value
- *
- * @return the result of hashing z
- */
- public static long mixMurmur64(long z) {
- z = (z ^ (z >>> 33)) * 0xff51afd7ed558ccdL;
- z = (z ^ (z >>> 33)) * 0xc4ceb9fe1a85ec53L;
- return z ^ (z >>> 33);
- }
-
- /**
- * Computes Stafford variant 13 of the 64-bit mixing function for MurmurHash3.
- * This is a 64-bit hashing function with excellent avalanche statistics.
- * http://zimbry.blogspot.com/2011/09/better-bit-mixing-improving-on.html
- *
- * Note that if the argument {@code z} is 0, the result is 0.
- *
- * @param z any long value
- *
- * @return the result of hashing z
- */
- public static long mixStafford13(long z) {
- z = (z ^ (z >>> 30)) * 0xbf58476d1ce4e5b9L;
- z = (z ^ (z >>> 27)) * 0x94d049bb133111ebL;
- return z ^ (z >>> 31);
- }
-
- /**
- * Computes Doug Lea's 64-bit mixing function.
- * This is a 64-bit hashing function with excellent avalanche statistics.
- * It has the advantages of using the same multiplicative constant twice
- * and of using only 32-bit shifts.
- *
- * Note that if the argument {@code z} is 0, the result is 0.
- *
- * @param z any long value
- *
- * @return the result of hashing z
- */
- public static long mixLea64(long z) {
- z = (z ^ (z >>> 32)) * 0xdaba0b6eb09322e3L;
- z = (z ^ (z >>> 32)) * 0xdaba0b6eb09322e3L;
- return z ^ (z >>> 32);
- }
-
- /**
- * Computes the 32-bit mixing function for MurmurHash3.
- * This is a 32-bit hashing function with excellent avalanche statistics.
- * https://github.com/aappleby/smhasher/wiki/MurmurHash3
- *
- * Note that if the argument {@code z} is 0, the result is 0.
- *
- * @param z any long value
- *
- * @return the result of hashing z
- */
- public static int mixMurmur32(int z) {
- z = (z ^ (z >>> 16)) * 0x85ebca6b;
- z = (z ^ (z >>> 13)) * 0xc2b2ae35;
- return z ^ (z >>> 16);
- }
-
- /**
- * Computes Doug Lea's 32-bit mixing function.
- * This is a 32-bit hashing function with excellent avalanche statistics.
- * It has the advantages of using the same multiplicative constant twice
- * and of using only 16-bit shifts.
- *
- * Note that if the argument {@code z} is 0, the result is 0.
- *
- * @param z any long value
- *
- * @return the result of hashing z
- */
- public static int mixLea32(int z) {
- z = (z ^ (z >>> 16)) * 0xd36d884b;
- z = (z ^ (z >>> 16)) * 0xd36d884b;
- return z ^ (z >>> 16);
- }
-
- // Non-public (package only) support for spliterators needed by AbstractSplittableRNG
- // and AbstractArbitrarilyJumpableRNG and AbstractSharedRNG
-
- /**
- * Base class for making Spliterator classes for streams of randomly chosen values.
- */
- static abstract class RandomSpliterator {
- long index;
- final long fence;
-
- RandomSpliterator(long index, long fence) {
- this.index = index; this.fence = fence;
- }
-
- public long estimateSize() {
- return fence - index;
- }
-
- public int characteristics() {
- return (Spliterator.SIZED | Spliterator.SUBSIZED |
- Spliterator.NONNULL | Spliterator.IMMUTABLE);
- }
- }
-
-
- /*
- * Implementation support for nextExponential() and nextGaussian() methods of RandomNumberGenerator.
- *
- * Each is implemented using McFarland's fast modified ziggurat algorithm (largely
- * table-driven, with rare cases handled by computation and rejection sampling).
- * Walker's alias method for sampling a discrete distribution also plays a role.
- *
- * The tables themselves, as well as a number of associated parameters, are defined
- * in class java.util.DoubleZigguratTables, which is automatically generated by the
- * program create_ziggurat_tables.c (which takes only a few seconds to run).
- *
- * For more information about the algorithms, see these articles:
- *
- * Christopher D. McFarland. 2016 (published online 24 Jun 2015). A modified ziggurat
- * algorithm for generating exponentially and normally distributed pseudorandom numbers.
- * Journal of Statistical Computation and Simulation 86 (7), pages 1281-1294.
- * https://www.tandfonline.com/doi/abs/10.1080/00949655.2015.1060234
- * Also at https://arxiv.org/abs/1403.6870 (26 March 2014).
- *
- * Alastair J. Walker. 1977. An efficient method for generating discrete random
- * variables with general distributions. ACM Trans. Math. Software 3, 3
- * (September 1977), 253-256. DOI: https://doi.org/10.1145/355744.355749
- *
- * Certain details of these algorithms depend critically on the quality of the
- * low-order bits delivered by NextLong(). These algorithms should not be used
- * with RNG algorithms (such as a simple Linear Congruential Generator) whose
- * low-order output bits do not have good statistical quality.
- */
-
- // Implementation support for nextExponential()
-
- static double computeNextExponential(RandomNumberGenerator rng) {
- long U1 = rng.nextLong();
- // Experimentation on a variety of machines indicates that it is overall much faster
- // to do the following & and < operations on longs rather than first cast U1 to int
- // (but then we need to cast to int before doing the array indexing operation).
- long i = U1 & DoubleZigguratTables.exponentialLayerMask;
- if (i < DoubleZigguratTables.exponentialNumberOfLayers) {
- // This is the fast path (occurring more than 98% of the time). Make an early exit.
- return DoubleZigguratTables.exponentialX[(int)i] * (U1 >>> 1);
- }
- // We didn't use the upper part of U1 after all. We'll be able to use it later.
-
- for (double extra = 0.0; ; ) {
- // Use Walker's alias method to sample an (unsigned) integer j from a discrete
- // probability distribution that includes the tail and all the ziggurat overhangs;
- // j will be less than DoubleZigguratTables.exponentialNumberOfLayers + 1.
- long UA = rng.nextLong();
- int j = (int)UA & DoubleZigguratTables.exponentialAliasMask;
- if (UA >= DoubleZigguratTables.exponentialAliasThreshold[j]) {
- j = DoubleZigguratTables.exponentialAliasMap[j] & DoubleZigguratTables.exponentialSignCorrectionMask;
- }
- if (j > 0) { // Sample overhang j
- // For the exponential distribution, every overhang is convex.
- final double[] X = DoubleZigguratTables.exponentialX;
- final double[] Y = DoubleZigguratTables.exponentialY;
- for (;; U1 = (rng.nextLong() >>> 1)) {
- long U2 = (rng.nextLong() >>> 1);
- // Compute the actual x-coordinate of the randomly chosen point.
- double x = (X[j] * 0x1.0p63) + ((X[j-1] - X[j]) * (double)U1);
- // Does the point lie below the curve?
- long Udiff = U2 - U1;
- if (Udiff < 0) {
- // We picked a point in the upper-right triangle. None of those can be accepted.
- // So remap the point into the lower-left triangle and try that.
- // In effect, we swap U1 and U2, and invert the sign of Udiff.
- Udiff = -Udiff;
- U2 = U1;
- U1 -= Udiff;
- }
- if (Udiff >= DoubleZigguratTables.exponentialConvexMargin) {
- return x + extra; // The chosen point is way below the curve; accept it.
- }
- // Compute the actual y-coordinate of the randomly chosen point.
- double y = (Y[j] * 0x1.0p63) + ((Y[j] - Y[j-1]) * (double)U2);
- // Now see how that y-coordinate compares to the curve
- if (y <= Math.exp(-x)) {
- return x + extra; // The chosen point is below the curve; accept it.
- }
- // Otherwise, we reject this sample and have to try again.
- }
- }
- // We are now committed to sampling from the tail. We could do a recursive call
- // and then add X[0] but we save some time and stack space by using an iterative loop.
- extra += DoubleZigguratTables.exponentialX0;
- // This is like the first five lines of this method, but if it returns, it first adds "extra".
- U1 = rng.nextLong();
- i = U1 & DoubleZigguratTables.exponentialLayerMask;
- if (i < DoubleZigguratTables.exponentialNumberOfLayers) {
- return DoubleZigguratTables.exponentialX[(int)i] * (U1 >>> 1) + extra;
- }
- }
- }
-
- // Implementation support for nextGaussian()
-
- static double computeNextGaussian(RandomNumberGenerator rng) {
- long U1 = rng.nextLong();
- // Experimentation on a variety of machines indicates that it is overall much faster
- // to do the following & and < operations on longs rather than first cast U1 to int
- // (but then we need to cast to int before doing the array indexing operation).
- long i = U1 & DoubleZigguratTables.normalLayerMask;
-
- if (i < DoubleZigguratTables.normalNumberOfLayers) {
- // This is the fast path (occurring more than 98% of the time). Make an early exit.
- return DoubleZigguratTables.normalX[(int)i] * U1; // Note that the sign bit of U1 is used here.
- }
- // We didn't use the upper part of U1 after all.
- // Pull U1 apart into a sign bit and a 63-bit value for later use.
- double signBit = (U1 >= 0) ? 1.0 : -1.0;
- U1 = (U1 << 1) >>> 1;
-
- // Use Walker's alias method to sample an (unsigned) integer j from a discrete
- // probability distribution that includes the tail and all the ziggurat overhangs;
- // j will be less than DoubleZigguratTables.normalNumberOfLayers + 1.
- long UA = rng.nextLong();
- int j = (int)UA & DoubleZigguratTables.normalAliasMask;
- if (UA >= DoubleZigguratTables.normalAliasThreshold[j]) {
- j = DoubleZigguratTables.normalAliasMap[j] & DoubleZigguratTables.normalSignCorrectionMask;
- }
-
- double x;
- // Now the goal is to choose the result, which will be multiplied by signBit just before return.
-
- // There are four kinds of overhangs:
- //
- // j == 0 : Sample from tail
- // 0 < j < normalInflectionIndex : Overhang is convex; can reject upper-right triangle
- // j == normalInflectionIndex : Overhang includes the inflection point
- // j > normalInflectionIndex : Overhang is concave; can accept point in lower-left triangle
- //
- // Choose one of four loops to compute x, each specialized for a specific kind of overhang.
- // Conditional statements are arranged such that the more likely outcomes are first.
-
- // In the three cases other than the tail case:
- // U1 represents a fraction (scaled by 2**63) of the width of rectangle measured from the left.
- // U2 represents a fraction (scaled by 2**63) of the height of rectangle measured from the top.
- // Together they indicate a randomly chosen point within the rectangle.
-
- final double[] X = DoubleZigguratTables.normalX;
- final double[] Y = DoubleZigguratTables.normalY;
- if (j > DoubleZigguratTables.normalInflectionIndex) { // Concave overhang
- for (;; U1 = (rng.nextLong() >>> 1)) {
- long U2 = (rng.nextLong() >>> 1);
- // Compute the actual x-coordinate of the randomly chosen point.
- x = (X[j] * 0x1.0p63) + ((X[j-1] - X[j]) * (double)U1);
- // Does the point lie below the curve?
- long Udiff = U2 - U1;
- if (Udiff >= 0) {
- break; // The chosen point is in the lower-left triangle; accept it.
- }
- if (Udiff <= -DoubleZigguratTables.normalConcaveMargin) {
- continue; // The chosen point is way above the curve; reject it.
- }
- // Compute the actual y-coordinate of the randomly chosen point.
- double y = (Y[j] * 0x1.0p63) + ((Y[j] - Y[j-1]) * (double)U2);
- // Now see how that y-coordinate compares to the curve
- if (y <= Math.exp(-0.5*x*x)) {
- break; // The chosen point is below the curve; accept it.
- }
- // Otherwise, we reject this sample and have to try again.
- }
- } else if (j == 0) { // Tail
- // Tail-sampling method of Marsaglia and Tsang. See any one of:
- // Marsaglia and Tsang. 1984. A fast, easily implemented method for sampling from decreasing
- // or symmetric unimodal density functions. SIAM J. Sci. Stat. Comput. 5, 349-359.
- // Marsaglia and Tsang. 1998. The Monty Python method for generating random variables.
- // ACM Trans. Math. Softw. 24, 3 (September 1998), 341-350. See page 342, step (4).
- // http://doi.org/10.1145/292395.292453
- // Thomas, Luk, Leong, and Villasenor. 2007. Gaussian random number generators.
- // ACM Comput. Surv. 39, 4, Article 11 (November 2007). See Algorithm 16.
- // http://doi.org/10.1145/1287620.1287622
- // Compute two separate random exponential samples and then compare them in certain way.
- do {
- x = (1.0 / DoubleZigguratTables.normalX0) * computeNextExponential(rng);
- } while (computeNextExponential(rng) < 0.5*x*x);
- x += DoubleZigguratTables.normalX0;
- } else if (j < DoubleZigguratTables.normalInflectionIndex) { // Convex overhang
- for (;; U1 = (rng.nextLong() >>> 1)) {
- long U2 = (rng.nextLong() >>> 1);
- // Compute the actual x-coordinate of the randomly chosen point.
- x = (X[j] * 0x1.0p63) + ((X[j-1] - X[j]) * (double)U1);
- // Does the point lie below the curve?
- long Udiff = U2 - U1;
- if (Udiff < 0) {
- // We picked a point in the upper-right triangle. None of those can be accepted.
- // So remap the point into the lower-left triangle and try that.
- // In effect, we swap U1 and U2, and invert the sign of Udiff.
- Udiff = -Udiff;
- U2 = U1;
- U1 -= Udiff;
- }
- if (Udiff >= DoubleZigguratTables.normalConvexMargin) {
- break; // The chosen point is way below the curve; accept it.
- }
- // Compute the actual y-coordinate of the randomly chosen point.
- double y = (Y[j] * 0x1.0p63) + ((Y[j] - Y[j-1]) * (double)U2);
- // Now see how that y-coordinate compares to the curve
- if (y <= Math.exp(-0.5*x*x)) break; // The chosen point is below the curve; accept it.
- // Otherwise, we reject this sample and have to try again.
- }
- } else {
- // The overhang includes the inflection point, so the curve is both convex and concave
- for (;; U1 = (rng.nextLong() >>> 1)) {
- long U2 = (rng.nextLong() >>> 1);
- // Compute the actual x-coordinate of the randomly chosen point.
- x = (X[j] * 0x1.0p63) + ((X[j-1] - X[j]) * (double)U1);
- // Does the point lie below the curve?
- long Udiff = U2 - U1;
- if (Udiff >= DoubleZigguratTables.normalConvexMargin) {
- break; // The chosen point is way below the curve; accept it.
- }
- if (Udiff <= -DoubleZigguratTables.normalConcaveMargin) {
- continue; // The chosen point is way above the curve; reject it.
- }
- // Compute the actual y-coordinate of the randomly chosen point.
- double y = (Y[j] * 0x1.0p63) + ((Y[j] - Y[j-1]) * (double)U2);
- // Now see how that y-coordinate compares to the curve
- if (y <= Math.exp(-0.5*x*x)) {
- break; // The chosen point is below the curve; accept it.
- }
- // Otherwise, we reject this sample and have to try again.
- }
- }
- return signBit*x;
- }
-
-}
-