/*
* 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
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*/
package java.util.random;
import java.util.function.Consumer;
import java.util.function.DoubleConsumer;
import java.util.function.IntConsumer;
import java.util.function.LongConsumer;
import java.util.random.RandomGenerator.SplittableGenerator;
import java.util.Spliterator;
import java.util.stream.DoubleStream;
import java.util.stream.IntStream;
import java.util.stream.LongStream;
import java.util.stream.Stream;
import java.util.stream.StreamSupport;
/**
* Low-level utility methods helpful for implementing pseudorandom number generators.
*
* This class is mostly for library writers creating specific implementations of the
* interface {@link RandomGenerator}.
*
* @since 14
*/
public class RandomSupport {
/*
* Implementation Overview.
*
* This class provides utility methods and constants frequently
* useful in the implementation of pseudorandom number generators
* that satisfy the interface {@link RandomGenerator}.
*
* 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} fails to be 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} fails to be 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} fails to be 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 if {@code origin} is not finite, {@code bound} is not finite,
* or {@code bound - origin} is not 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 if {@code origin} is not finite, {@code bound} is not finite,
* or {@code bound - origin} is not 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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(RandomGenerator 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 RandomGenerator}
* 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 AbstractSplittableGenerator
// and AbstractArbitrarilyJumpableGenerator and AbstractSharedGenerator
/**
* Base class for making Spliterator classes for streams of randomly chosen values.
*/
public abstract static class RandomSpliterator {
/** low range value */
public long index;
/** high range value */
public final long fence;
/**
* Constructor
*
* @param index low range value
* @param fence high range value
*/
public RandomSpliterator(long index, long fence) {
this.index = index; this.fence = fence;
}
/**
* Returns estimated size.
*
* @return estimated size
*/
public long estimateSize() {
return fence - index;
}
/**
* Returns characteristics.
*
* @return characteristics
*/
public int characteristics() {
return (Spliterator.SIZED | Spliterator.SUBSIZED |
Spliterator.NONNULL | Spliterator.IMMUTABLE);
}
}
/*
* Implementation support for nextExponential() and nextGaussian() methods of RandomGenerator.
*
* 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(RandomGenerator 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(RandomGenerator 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;
}
/**
* This class overrides the stream-producing methods (such as {@code ints()})
* in class {@link AbstractGenerator} to provide {@link Spliterator}-based
* implmentations that support potentially parallel execution.
*
* To implement a pseudorandom number generator, the programmer needs
* only to extend this class and provide implementations for the methods
* {@code nextInt()}, {@code nextLong()}, {@code makeIntsSpliterator},
* {@code makeLongsSpliterator}, and {@code makeDoublesSpliterator}.
*
* This class is not public; it provides shared code to the public
* classes {@link AbstractSplittableGenerator}, {@link AbstractSharedGenerator},
* and {@link AbstractArbitrarilyJumpableGenerator}.
*
* @since 14
*/
public abstract static class AbstractSpliteratorGenerator implements RandomGenerator {
/*
* Implementation Overview.
*
* This class provides most of the "user API" methods needed to
* satisfy the interface RandomGenerator. An implementation of this
* interface need only extend this class and provide implementations
* of six methods: nextInt, nextLong, and nextDouble (the versions
* that take no arguments) and makeIntsSpliterator,
* makeLongsSpliterator, and makeDoublesSpliterator.
*
* File organization: First the non-public abstract methods needed
* to create spliterators, then the main public methods.
*/
/**
* Create an instance of {@link Spliterator.OfInt} that for each traversal position
* between the specified index (inclusive) and the specified fence (exclusive) generates
* a pseudorandomly chosen {@code int} value between the specified origin (inclusive) and
* the specified bound (exclusive).
*
* @param index the (inclusive) lower bound on traversal positions
* @param fence the (exclusive) upper bound on traversal positions
* @param origin the (inclusive) lower bound on the pseudorandom values to be generated
* @param bound the (exclusive) upper bound on the pseudorandom values to be generated
* @return an instance of {@link Spliterator.OfInt}
*/
public abstract Spliterator.OfInt makeIntsSpliterator(long index, long fence, int origin, int bound);
/**
* Create an instance of {@link Spliterator.OfLong} that for each traversal position
* between the specified index (inclusive) and the specified fence (exclusive) generates
* a pseudorandomly chosen {@code long} value between the specified origin (inclusive) and
* the specified bound (exclusive).
*
* @param index the (inclusive) lower bound on traversal positions
* @param fence the (exclusive) upper bound on traversal positions
* @param origin the (inclusive) lower bound on the pseudorandom values to be generated
* @param bound the (exclusive) upper bound on the pseudorandom values to be generated
* @return an instance of {@link Spliterator.OfLong}
*/
public abstract Spliterator.OfLong makeLongsSpliterator(long index, long fence, long origin, long bound);
/**
* Create an instance of {@link Spliterator.OfDouble} that for each traversal position
* between the specified index (inclusive) and the specified fence (exclusive) generates
* a pseudorandomly chosen {@code double} value between the specified origin (inclusive) and
* the specified bound (exclusive).
*
* @param index the (inclusive) lower bound on traversal positions
* @param fence the (exclusive) upper bound on traversal positions
* @param origin the (inclusive) lower bound on the pseudorandom values to be generated
* @param bound the (exclusive) upper bound on the pseudorandom values to be generated
* @return an instance of {@link Spliterator.OfDouble}
*/
public abstract Spliterator.OfDouble makeDoublesSpliterator(long index, long fence, double origin, double bound);
/* ---------------- public methods ---------------- */
// stream methods, coded in a way intended to better isolate for
// maintenance purposes the small differences across forms.
private static IntStream intStream(Spliterator.OfInt srng) {
return StreamSupport.intStream(srng, false);
}
private static LongStream longStream(Spliterator.OfLong srng) {
return StreamSupport.longStream(srng, false);
}
private static DoubleStream doubleStream(Spliterator.OfDouble srng) {
return StreamSupport.doubleStream(srng, false);
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code int}
* values from this generator and/or one split from it.
*
* @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
*/
public IntStream ints(long streamSize) {
RandomSupport.checkStreamSize(streamSize);
return intStream(makeIntsSpliterator(0L, streamSize, Integer.MAX_VALUE, 0));
}
/**
* Returns an effectively unlimited stream of pseudorandomly chosen
* {@code int} values.
*
* @implNote The implementation of this method is effectively
* equivalent to {@code ints(Long.MAX_VALUE)}.
*
* @return a stream of pseudorandomly chosen {@code int} values
*/
public IntStream ints() {
return intStream(makeIntsSpliterator(0L, Long.MAX_VALUE, Integer.MAX_VALUE, 0));
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code int}
* values from this generator and/or one split from it; each value conforms to the given origin
* (inclusive) and bound (exclusive).
*
* @param streamSize the number of values to generate
* @param randomNumberOrigin the origin (inclusive) of each random value
* @param randomNumberBound the bound (exclusive) of each random value
*
* @return a stream of pseudorandom {@code 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}
*/
public IntStream ints(long streamSize, int randomNumberOrigin, int randomNumberBound) {
RandomSupport.checkStreamSize(streamSize);
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return intStream(makeIntsSpliterator(0L, streamSize, randomNumberOrigin, randomNumberBound));
}
/**
* Returns an effectively unlimited stream of pseudorandom {@code int} values from this
* generator and/or one split from it; each value conforms to the given origin (inclusive) and
* bound (exclusive).
*
* @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}
*
* @implNote This method is implemented to be equivalent to {@code ints(Long.MAX_VALUE,
* randomNumberOrigin, randomNumberBound)}.
*/
public IntStream ints(int randomNumberOrigin, int randomNumberBound) {
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return intStream(makeIntsSpliterator(0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound));
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code long}
* values from this generator and/or one split from it.
*
* @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
*/
public LongStream longs(long streamSize) {
RandomSupport.checkStreamSize(streamSize);
return longStream(makeLongsSpliterator(0L, streamSize, Long.MAX_VALUE, 0L));
}
/**
* Returns an effectively unlimited stream of pseudorandom {@code long} values from this
* generator and/or one split from it.
*
* @return a stream of pseudorandom {@code long} values
*
* @implNote This method is implemented to be equivalent to {@code
* longs(Long.MAX_VALUE)}.
*/
public LongStream longs() {
return longStream(makeLongsSpliterator(0L, Long.MAX_VALUE, Long.MAX_VALUE, 0L));
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code long}
* values from this generator and/or one split from it; each value conforms to the given origin
* (inclusive) and bound (exclusive).
*
* @param streamSize the number of values to generate
* @param randomNumberOrigin the origin (inclusive) of each random value
* @param randomNumberBound the bound (exclusive) of each random value
*
* @return a stream of pseudorandom {@code 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}
*/
public LongStream longs(long streamSize, long randomNumberOrigin,
long randomNumberBound) {
RandomSupport.checkStreamSize(streamSize);
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return longStream(makeLongsSpliterator(0L, streamSize, randomNumberOrigin, randomNumberBound));
}
/**
* Returns an effectively unlimited stream of pseudorandom {@code long} values from this
* generator and/or one split from it; each value conforms to the given origin (inclusive) and
* bound (exclusive).
*
* @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}
*
* @implNote This method is implemented to be equivalent to {@code longs(Long.MAX_VALUE,
* randomNumberOrigin, randomNumberBound)}.
*/
public LongStream longs(long randomNumberOrigin, long randomNumberBound) {
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return StreamSupport.longStream
(makeLongsSpliterator(0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound),
false);
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code double}
* values from this generator and/or one split from it; each value is between zero (inclusive)
* and one (exclusive).
*
* @param streamSize the number of values to generate
*
* @return a stream of {@code double} values
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public DoubleStream doubles(long streamSize) {
RandomSupport.checkStreamSize(streamSize);
return doubleStream(makeDoublesSpliterator(0L, streamSize, Double.MAX_VALUE, 0.0));
}
/**
* Returns an effectively unlimited stream of pseudorandom {@code double} values from this
* generator and/or one split from it; each value is between zero (inclusive) and one
* (exclusive).
*
* @return a stream of pseudorandom {@code double} values
*
* @implNote This method is implemented to be equivalent to {@code
* doubles(Long.MAX_VALUE)}.
*/
public DoubleStream doubles() {
return doubleStream(makeDoublesSpliterator(0L, Long.MAX_VALUE, Double.MAX_VALUE, 0.0));
}
/**
* Returns a stream producing the given {@code streamSize} number of pseudorandom {@code double}
* values from this generator and/or one split from it; each value conforms to the given origin
* (inclusive) and bound (exclusive).
*
* @param streamSize the number of values to generate
* @param randomNumberOrigin the origin (inclusive) of each random value
* @param randomNumberBound the bound (exclusive) of each random value
*
* @return a stream of pseudorandom {@code double} values, each with the given origin
* (inclusive) and bound (exclusive)
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
* @throws IllegalArgumentException if {@code randomNumberOrigin} is greater than or equal to
* {@code randomNumberBound}
*/
public DoubleStream doubles(long streamSize, double randomNumberOrigin, double randomNumberBound) {
RandomSupport.checkStreamSize(streamSize);
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return doubleStream(makeDoublesSpliterator(0L, streamSize, randomNumberOrigin, randomNumberBound));
}
/**
* Returns an effectively unlimited stream of pseudorandom {@code double} values from this
* generator and/or one split from it; each value conforms to the given origin (inclusive) and
* bound (exclusive).
*
* @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}
*
* @implNote This method is implemented to be equivalent to {@code
* doubles(Long.MAX_VALUE, randomNumberOrigin, randomNumberBound)}.
*/
public DoubleStream doubles(double randomNumberOrigin, double randomNumberBound) {
RandomSupport.checkRange(randomNumberOrigin, randomNumberBound);
return doubleStream(makeDoublesSpliterator(0L, Long.MAX_VALUE, randomNumberOrigin, randomNumberBound));
}
}
/**
* This class provides much of the implementation of the
* {@link ArbitrarilyJumpableGenerator} interface, to minimize the effort
* required to implement that interface.
*
* To implement a pseudorandom number generator, the programmer needs
* only to extend this class and provide implementations for the
* methods {@link #nextInt()}, {@link #nextLong()}, {@link #copy()},
* {@link #jump(double)}, {@link #jumpPowerOfTwo(int)},
* {@link #defaultJumpDistance()}, and {@link #defaultLeapDistance()}.
*
* (If the pseudorandom number generator also has the ability to split,
* then the programmer may wish to consider instead extending
* {@link AbstractSplittableGenerator}.)
*
* The programmer should generally provide at least three constructors:
* one that takes no arguments, one that accepts a {@code long}
* seed value, and one that accepts an array of seed {@code byte} values.
* This class provides a public {@code initialSeed()} method that may
* be useful in initializing some static state from which to derive
* defaults seeds for use by the no-argument constructor.
*
* For the stream methods (such as {@code ints()} and {@code splits()}),
* this class provides {@link Spliterator}-based implementations that
* allow parallel execution when appropriate. In this respect
* {@link ArbitrarilyJumpableGenerator} differs from {@link JumpableGenerator},
* which provides very simple implementations that produce
* sequential streams only.
*
* <p>An implementation of the {@link AbstractArbitrarilyJumpableGenerator} class
* must provide concrete definitions for the methods {@code nextInt()},
* {@code nextLong}, {@code period()}, {@code copy()}, {@code jump(double)},
* {@code defaultJumpDistance()}, and {@code defaultLeapDistance()}.
* Default implementations are provided for all other methods.
*
* The documentation for each non-abstract method in this class
* describes its implementation in detail. Each of these methods may
* be overridden if the pseudorandom number generator being
* implemented admits a more efficient implementation.
*
* @since 14
*/
public abstract static class AbstractArbitrarilyJumpableGenerator
extends AbstractSpliteratorGenerator implements RandomGenerator.ArbitrarilyJumpableGenerator {
/*
* Implementation Overview.
*
* This class provides most of the "user API" methods needed to satisfy
* the interface ArbitrarilyJumpableGenerator. Most of these methods
* are in turn inherited from AbstractGenerator and the non-public class
* AbstractSpliteratorGenerator; this file implements four versions of the
* jumps method and defines the spliterators necessary to support them.
*
* File organization: First the non-public methods needed by the class
* AbstractSpliteratorGenerator, then the main public methods, followed by some
* custom spliterator classes needed for stream methods.
*/
// IllegalArgumentException messages
static final String BadLogDistance = "logDistance must be non-negative";
// Methods required by class AbstractSpliteratorGenerator
public Spliterator.OfInt makeIntsSpliterator(long index, long fence, int origin, int bound) {
return new RandomIntsSpliterator(this, index, fence, origin, bound);
}
public Spliterator.OfLong makeLongsSpliterator(long index, long fence, long origin, long bound) {
return new RandomLongsSpliterator(this, index, fence, origin, bound);
}
public Spliterator.OfDouble makeDoublesSpliterator(long index, long fence, double origin, double bound) {
return new RandomDoublesSpliterator(this, index, fence, origin, bound);
}
// Similar methods used by this class
Spliterator<RandomGenerator> makeJumpsSpliterator(long index, long fence, double distance) {
return new RandomJumpsSpliterator(this, index, fence, distance);
}
Spliterator<JumpableGenerator> makeLeapsSpliterator(long index, long fence, double distance) {
return new RandomLeapsSpliterator(this, index, fence, distance);
}
Spliterator<ArbitrarilyJumpableGenerator> makeArbitraryJumpsSpliterator(long index, long fence, double distance) {
return new RandomArbitraryJumpsSpliterator(this, index, fence, distance);
}
/* ---------------- public methods ---------------- */
/**
* Returns a new generator whose internal state is an exact copy
* of this generator (therefore their future behavior should be
* identical if subjected to the same series of operations).
*
* @return a new object that is a copy of this generator
*/
public abstract AbstractArbitrarilyJumpableGenerator copy();
// Stream methods for jumping
private static <T> Stream<T> stream(Spliterator<T> srng) {
return StreamSupport.stream(srng, false);
}
/**
* Returns an effectively unlimited stream of new pseudorandom number generators, each of which
* implements the {@link RandomGenerator} interface, produced by jumping copies of this
* generator by different integer multiples of the default jump distance.
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*
* @implNote This method is implemented to be equivalent to {@code
* jumps(Long.MAX_VALUE)}.
*/
public Stream<RandomGenerator> jumps() {
return stream(makeJumpsSpliterator(0L, Long.MAX_VALUE, defaultJumpDistance()));
}
/**
* Returns a stream producing the given {@code streamSize} number of
* new pseudorandom number generators, each of which implements the
* {@link RandomGenerator} interface, produced by jumping copies of this generator
* by different integer multiples of the default jump distance.
*
* @param streamSize the number of generators to generate
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public Stream<RandomGenerator> jumps(long streamSize) {
RandomSupport.checkStreamSize(streamSize);
return stream(makeJumpsSpliterator(0L, streamSize, defaultJumpDistance()));
}
/**
* Returns an effectively unlimited stream of new pseudorandom number generators, each of which
* implements the {@link RandomGenerator} interface, produced by jumping copies of this
* generator by different integer multiples of the specified jump distance.
*
* @param distance a distance to jump forward within the state cycle
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*
* @implNote This method is implemented to be equivalent to {@code
* jumps(Long.MAX_VALUE)}.
*/
public Stream<ArbitrarilyJumpableGenerator> jumps(double distance) {
return stream(makeArbitraryJumpsSpliterator(0L, Long.MAX_VALUE, distance));
}
/**
* Returns a stream producing the given {@code streamSize} number of new pseudorandom number
* generators, each of which implements the {@link RandomGenerator} interface, produced by
* jumping copies of this generator by different integer multiples of the specified jump
* distance.
*
* @param streamSize the number of generators to generate
* @param distance a distance to jump forward within the state cycle
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public Stream<ArbitrarilyJumpableGenerator> jumps(long streamSize, double distance) {
RandomSupport.checkStreamSize(streamSize);
return stream(makeArbitraryJumpsSpliterator(0L, streamSize, distance));
}
/**
* Alter the state of this pseudorandom number generator so as to
* jump forward a very large, fixed distance (typically 2<sup>128</sup>
* or more) within its state cycle. The distance used is that
* returned by method {@code defaultLeapDistance()}.
*/
public void leap() {
jump(defaultLeapDistance());
}
// Stream methods for leaping
/**
* Returns an effectively unlimited stream of new pseudorandom number generators, each of which
* implements the {@link RandomGenerator} interface, produced by jumping copies of this
* generator by different integer multiples of the default leap distance.
*
* @implNote This method is implemented to be equivalent to {@code leaps(Long.MAX_VALUE)}.
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*/
public Stream<JumpableGenerator> leaps() {
return stream(makeLeapsSpliterator(0L, Long.MAX_VALUE, defaultLeapDistance()));
}
/**
* Returns a stream producing the given {@code streamSize} number of new pseudorandom number
* generators, each of which implements the {@link RandomGenerator} interface, produced by
* jumping copies of this generator by different integer multiples of the default leap
* distance.
*
* @param streamSize the number of generators to generate
*
* @return a stream of objects that implement the {@link RandomGenerator} interface
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public Stream<JumpableGenerator> leaps(long streamSize) {
return stream(makeLeapsSpliterator(0L, streamSize, defaultLeapDistance()));
}
/**
* 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
* {@code Long.MAX_VALUE}. For splits, we choose to override the method {@code trySplit()} to
* try to optimize execution speed: instead of dividing a range in half, it breaks off the
* largest possible chunk whose size is a power of two such that the remaining chunk is not
* empty. In this way, the necessary jump distances will tend to be powers of two. The long
* and double versions of this class are identical except for types.
*/
static class RandomIntsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfInt {
final ArbitrarilyJumpableGenerator generatingGenerator;
final int origin;
final int bound;
RandomIntsSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, int origin, int bound) {
super(index, fence);
this.origin = origin; this.bound = bound;
this.generatingGenerator = generatingGenerator;
}
public Spliterator.OfInt trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
ArbitrarilyJumpableGenerator r = generatingGenerator;
return new RandomIntsSpliterator(r.copyAndJump((double)delta), i, m, origin, bound);
}
public boolean tryAdvance(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextInt(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
int o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextInt(r, o, b));
} while (++i < f);
}
}
}
/**
* Spliterator for long streams.
*/
static class RandomLongsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfLong {
final ArbitrarilyJumpableGenerator generatingGenerator;
final long origin;
final long bound;
RandomLongsSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, long origin, long bound) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.origin = origin; this.bound = bound;
}
public Spliterator.OfLong trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
ArbitrarilyJumpableGenerator r = generatingGenerator;
return new RandomLongsSpliterator(r.copyAndJump((double)delta), i, m, origin, bound);
}
public boolean tryAdvance(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextLong(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
long o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextLong(r, o, b));
} while (++i < f);
}
}
}
/**
* Spliterator for double streams.
*/
static class RandomDoublesSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfDouble {
final ArbitrarilyJumpableGenerator generatingGenerator;
final double origin;
final double bound;
RandomDoublesSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, double origin, double bound) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.origin = origin; this.bound = bound;
}
public Spliterator.OfDouble trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
ArbitrarilyJumpableGenerator r = generatingGenerator;
return new RandomDoublesSpliterator(r.copyAndJump((double)delta), i, m, origin, bound);
}
public boolean tryAdvance(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextDouble(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
double o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextDouble(r, o, b));
} while (++i < f);
}
}
}
// Spliterators for producing new generators by jumping or leaping. The
// complete implementation of each of these spliterators is right here.
// In the same manner as for the preceding spliterators, the method trySplit() is
// coded to optimize execution speed: instead of dividing a range
// in half, it breaks off the largest possible chunk whose
// size is a power of two such that the remaining chunk is not
// empty. In this way, the necessary jump distances will tend to be
// powers of two.
/**
* Spliterator for stream of generators of type RandomGenerator produced by jumps.
*/
static class RandomJumpsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator<RandomGenerator> {
ArbitrarilyJumpableGenerator generatingGenerator;
final double distance;
RandomJumpsSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, double distance) {
super(index, fence);
this.generatingGenerator = generatingGenerator; this.distance = distance;
}
public Spliterator<RandomGenerator> trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
ArbitrarilyJumpableGenerator r = generatingGenerator;
// Because delta is a power of two, (distance * (double)delta) can always be computed exactly.
return new RandomJumpsSpliterator(r.copyAndJump(distance * (double)delta), i, m, distance);
}
public boolean tryAdvance(Consumer<? super RandomGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(generatingGenerator.copyAndJump(distance));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(Consumer<? super RandomGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
do {
consumer.accept(r.copyAndJump(distance));
} while (++i < f);
}
}
}
/**
* Spliterator for stream of generators of type RandomGenerator produced by leaps.
*/
static class RandomLeapsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator<JumpableGenerator> {
ArbitrarilyJumpableGenerator generatingGenerator;
final double distance;
RandomLeapsSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, double distance) {
super(index, fence);
this.generatingGenerator = generatingGenerator; this.distance = distance;
}
public Spliterator<JumpableGenerator> trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
// Because delta is a power of two, (distance * (double)delta) can always be computed exactly.
return new RandomLeapsSpliterator(generatingGenerator.copyAndJump(distance * (double)delta), i, m, distance);
}
public boolean tryAdvance(Consumer<? super JumpableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(generatingGenerator.copyAndJump(distance));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(Consumer<? super JumpableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
do {
consumer.accept(r.copyAndJump(distance));
} while (++i < f);
}
}
}
/**
* Spliterator for stream of generators of type RandomGenerator produced by arbitrary jumps.
*/
static class RandomArbitraryJumpsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator<ArbitrarilyJumpableGenerator> {
ArbitrarilyJumpableGenerator generatingGenerator;
final double distance;
RandomArbitraryJumpsSpliterator(ArbitrarilyJumpableGenerator generatingGenerator, long index, long fence, double distance) {
super(index, fence);
this.generatingGenerator = generatingGenerator; this.distance = distance;
}
public Spliterator<ArbitrarilyJumpableGenerator> trySplit() {
long i = index, delta = Long.highestOneBit((fence - i) - 1), m = i + delta;
if (m <= i) return null;
index = m;
// Because delta is a power of two, (distance * (double)delta) can always be computed exactly.
return new RandomArbitraryJumpsSpliterator(generatingGenerator.copyAndJump(distance * (double)delta), i, m, distance);
}
public boolean tryAdvance(Consumer<? super ArbitrarilyJumpableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(generatingGenerator.copyAndJump(distance));
index = i + 1;
return true;
}
return false;
}
public void forEachRemaining(Consumer<? super ArbitrarilyJumpableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
ArbitrarilyJumpableGenerator r = generatingGenerator;
do {
consumer.accept(r.copyAndJump(distance));
} while (++i < f);
}
}
}
}
/**
* This class provides much of the implementation of the {@link SplittableGenerator} interface, to
* minimize the effort required to implement this interface.
* <p>
* To implement a pseudorandom number generator, the programmer needs only to extend this class and
* provide implementations for the methods {@code nextInt()}, {@code nextLong()}, {@code period()},
* and {@code split(SplittableGenerator)}.
* <p>
* (If the pseudorandom number generator also has the ability to jump an arbitrary
* specified distance, then the programmer may wish to consider instead extending the
* class {@link AbstractArbitrarilyJumpableGenerator}. See also the class
* {@link AbstractSplittableWithBrineGenerator}.)
* <p>
* The programmer should generally provide at least three constructors: one that takes no arguments,
* one that accepts a {@code long} seed value, and one that accepts an array of seed {@code byte}
* values. This class provides a public {@code initialSeed()} method that may be useful in
* initializing some static state from which to derive defaults seeds for use by the no-argument
* constructor.
* <p>
* For the stream methods (such as {@code ints()} and {@code splits()}), this class provides
* {@link Spliterator}-based implementations that allow parallel execution when appropriate.
* <p>
* The documentation for each non-abstract method in this class describes its implementation in
* detail. Each of these methods may be overridden if the pseudorandom number generator being
* implemented admits a more efficient implementation.
*
* @since 14
*/
public abstract static class AbstractSplittableGenerator extends AbstractSpliteratorGenerator implements SplittableGenerator {
/*
* Implementation Overview.
*
* This class provides most of the "user API" methods needed to
* satisfy the interface SplittableGenerator. Most of these methods
* are in turn inherited from AbstractGenerator and the non-public class
* AbstractSpliteratorGenerator; this class provides two versions of the
* splits method and defines the spliterators necessary to support
* them.
*
* File organization: First the non-public methods needed by the class
* AbstractSpliteratorGenerator, then the main public methods, followed by some
* custom spliterator classes.
*/
public Spliterator.OfInt makeIntsSpliterator(long index, long fence, int origin, int bound) {
return new RandomIntsSpliterator(this, index, fence, origin, bound);
}
public Spliterator.OfLong makeLongsSpliterator(long index, long fence, long origin, long bound) {
return new RandomLongsSpliterator(this, index, fence, origin, bound);
}
public Spliterator.OfDouble makeDoublesSpliterator(long index, long fence, double origin, double bound) {
return new RandomDoublesSpliterator(this, index, fence, origin, bound);
}
Spliterator<SplittableGenerator> makeSplitsSpliterator(long index, long fence, SplittableGenerator source) {
return new RandomSplitsSpliterator(source, index, fence, this);
}
/* ---------------- public methods ---------------- */
/**
* Implements the @code{split()} method as {@code this.split(this)}.
*
* @return the new {@link SplittableGenerator} instance
*/
public SplittableGenerator split() {
return this.split(this);
}
// Stream methods for splittings
/**
* Returns an effectively unlimited stream of new pseudorandom number generators, each of which
* implements the {@link SplittableGenerator} interface.
* <p>
* This pseudorandom number generator provides the entropy used to seed the new ones.
*
* @return a stream of {@link SplittableGenerator} objects
*
* @implNote This method is implemented to be equivalent to {@code splits(Long.MAX_VALUE)}.
*/
public Stream<SplittableGenerator> splits() {
return this.splits(Long.MAX_VALUE, this);
}
/**
* Returns a stream producing the given {@code streamSize} number of new pseudorandom number
* generators, each of which implements the {@link SplittableGenerator} interface.
* <p>
* This pseudorandom number generator provides the entropy used to seed the new ones.
*
* @param streamSize the number of values to generate
*
* @return a stream of {@link SplittableGenerator} objects
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public Stream<SplittableGenerator> splits(long streamSize) {
return this.splits(streamSize, this);
}
/**
* Returns an effectively unlimited stream of new pseudorandom number generators, each of which
* implements the {@link SplittableGenerator} interface.
*
* @param source a {@link SplittableGenerator} instance to be used instead of this one as a source of
* pseudorandom bits used to initialize the state of the new ones.
*
* @return a stream of {@link SplittableGenerator} objects
*
* @implNote This method is implemented to be equivalent to {@code splits(Long.MAX_VALUE)}.
*/
public Stream<SplittableGenerator> splits(SplittableGenerator source) {
return this.splits(Long.MAX_VALUE, source);
}
/**
* Returns a stream producing the given {@code streamSize} number of new pseudorandom number
* generators, each of which implements the {@link SplittableGenerator} interface.
*
* @param streamSize the number of values to generate
* @param source a {@link SplittableGenerator} instance to be used instead of this one as a source
* of pseudorandom bits used to initialize the state of the new ones.
*
* @return a stream of {@link SplittableGenerator} objects
*
* @throws IllegalArgumentException if {@code streamSize} is less than zero
*/
public Stream<SplittableGenerator> splits(long streamSize, SplittableGenerator source) {
RandomSupport.checkStreamSize(streamSize);
return StreamSupport.stream(makeSplitsSpliterator(0L, streamSize, source), 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
* {@code 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 class RandomIntsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfInt {
final SplittableGenerator generatingGenerator;
final int origin;
final int bound;
RandomIntsSpliterator(SplittableGenerator generatingGenerator, long index, long fence, int origin, int bound) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.origin = origin; this.bound = bound;
}
public Spliterator.OfInt trySplit() {
long i = index, m = (i + fence) >>> 1;
if (m <= i) return null;
index = m;
return new RandomIntsSpliterator(generatingGenerator.split(), i, m, origin, bound);
}
public boolean tryAdvance(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextInt(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(IntConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
RandomGenerator r = generatingGenerator;
int o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextInt(r, o, b));
} while (++i < f);
}
}
}
/**
* Spliterator for long streams.
*/
static class RandomLongsSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfLong {
final SplittableGenerator generatingGenerator;
final long origin;
final long bound;
RandomLongsSpliterator(SplittableGenerator generatingGenerator, long index, long fence, long origin, long bound) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.origin = origin; this.bound = bound;
}
public Spliterator.OfLong trySplit() {
long i = index, m = (i + fence) >>> 1;
if (m <= i) return null;
index = m;
return new RandomLongsSpliterator(generatingGenerator.split(), i, m, origin, bound);
}
public boolean tryAdvance(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextLong(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(LongConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
RandomGenerator r = generatingGenerator;
long o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextLong(r, o, b));
} while (++i < f);
}
}
}
/**
* Spliterator for double streams.
*/
static class RandomDoublesSpliterator extends RandomSupport.RandomSpliterator implements Spliterator.OfDouble {
final SplittableGenerator generatingGenerator;
final double origin;
final double bound;
RandomDoublesSpliterator(SplittableGenerator generatingGenerator, long index, long fence, double origin, double bound) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.origin = origin; this.bound = bound;
}
public Spliterator.OfDouble trySplit() {
long i = index, m = (i + fence) >>> 1;
if (m <= i) return null;
index = m;
return new RandomDoublesSpliterator(generatingGenerator.split(), i, m, origin, bound);
}
public boolean tryAdvance(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(RandomSupport.boundedNextDouble(generatingGenerator, origin, bound));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(DoubleConsumer consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
RandomGenerator r = generatingGenerator;
double o = origin, b = bound;
do {
consumer.accept(RandomSupport.boundedNextDouble(r, o, b));
} while (++i < f);
}
}
}
/**
* Spliterator for stream of generators of type SplittableGenerator. We multiplex the two
* versions into one class by treating "infinite" as equivalent to Long.MAX_VALUE.
* For splits, it uses the standard divide-by-two approach.
*/
static class RandomSplitsSpliterator extends RandomSpliterator implements Spliterator<SplittableGenerator> {
final SplittableGenerator generatingGenerator;
final SplittableGenerator constructingGenerator;
RandomSplitsSpliterator(SplittableGenerator generatingGenerator,
long index, long fence,
SplittableGenerator constructingGenerator) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.constructingGenerator = constructingGenerator;
}
public Spliterator<SplittableGenerator> trySplit() {
long i = index, m = (i + fence) >>> 1;
if (m <= i) return null;
index = m;
return new RandomSplitsSpliterator(generatingGenerator.split(), i, m, constructingGenerator);
}
public boolean tryAdvance(Consumer<? super SplittableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(constructingGenerator.split(generatingGenerator));
index = i + 1;
return true;
}
else return false;
}
public void forEachRemaining(Consumer<? super SplittableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
SplittableGenerator c = constructingGenerator;
SplittableGenerator r = generatingGenerator;
do {
consumer.accept(c.split(r));
} while (++i < f);
}
}
}
}
/**
* This class provides much of the implementation of the {@link SplittableGenerator} interface, to
* minimize the effort required to implement this interface. It is similar to the class
* {@link AbstractSplittableGenerator} but makes use of the brine technique for ensuring that
* distinct generators created by a single call to a {@code splits} method have distinct state cycles.
* <p>
* To implement a pseudorandom number generator, the programmer needs only to extend this class and
* provide implementations for the methods {@code nextInt()}, {@code nextLong()}, {@code period()},
* and {@code split(SplittableGenerator, long)}.
* <p>
* The programmer should generally provide at least three constructors: one that takes no arguments,
* one that accepts a {@code long} seed value, and one that accepts an array of seed {@code byte}
* values. This class provides a public {@code initialSeed()} method that may be useful in
* initializing some static state from which to derive defaults seeds for use by the no-argument
* constructor.
* <p>
* For the stream methods (such as {@code ints()} and {@code splits()}), this class provides
* {@link Spliterator}-based implementations that allow parallel execution when appropriate.
* <p>
* The documentation for each non-abstract method in this class describes its implementation in
* detail. Each of these methods may be overridden if the pseudorandom number generator being
* implemented admits a more efficient implementation.
*
* @since 14
*/
public abstract static class AbstractSplittableWithBrineGenerator
extends AbstractSplittableGenerator {
/*
* Implementation Overview.
*
* This class provides most of the "user API" methods needed to
* satisfy the interface SplittableGenerator. Most of these methods
* are in turn inherited from AbstractSplittableGenerator and the non-public class
* AbstractSpliteratorGenerator; this class provides four versions of the
* splits method and defines the spliterators necessary to support
* them.
*
* File organization: First the non-public methods needed by the class
* AbstractSplittableWithBrineGenerator, then the main public methods,
* followed by some custom spliterator classes needed for stream methods.
*/
// The salt consists groups of bits each SALT_SHIFT in size, starting from
// the left-hand (high-order) end of the word. We can regard them as
// digits base (1 << SALT_SHIFT). If SALT_SHIFT does not divide 64
// evenly, then any leftover bits at the low end of the word are zero.
// The lowest digit of the salt is set to the largest possible digit
// (all 1-bits, or ((1 << SALT_SHIFT) - 1)); all other digits are set
// to a randomly chosen value less than that largest possible digit.
// The salt may be shifted left by SALT_SHIFT any number of times.
// If any salt remains in the word, its right-hand end can be identified
// by searching from left to right for an occurrence of a digit that is
// all 1-bits (not that we ever do that; this is simply a proof that one
// can identify the boundary between the salt and the index if any salt
// remains in the word). The idea is that before computing the bitwise OR
// of an index and the salt, one can first check to see whether the
// bitwise AND is nonzero; if so, one can shift the salt left by
// SALT_SHIFT and try again. In this way, when the bitwise OR is
// computed, if the salt is nonzero then its rightmost 1-bit is to the
// left of the leftmost 1-bit of the index.
// We need 2 <= SALT_SHIFT <= 63 (3 through 8 are good values; 4 is probably best)
static final int SALT_SHIFT = 4;
// Methods required by class AbstractSpliteratorGenerator (override)
Spliterator<SplittableGenerator> makeSplitsSpliterator(long index, long fence, SplittableGenerator source) {
// This little algorithm to generate a new salt value is carefully
// designed to work even if SALT_SHIFT does not evenly divide 64
// (the number of bits in a long value).
long bits = nextLong();
long multiplier = (1 << SALT_SHIFT) - 1;
long salt = multiplier << (64 - SALT_SHIFT);
while ((salt & multiplier) != 0) {
long digit = Math.multiplyHigh(bits, multiplier);
salt = (salt >>> SALT_SHIFT) | (digit << (64 - SALT_SHIFT));
bits *= multiplier;
}
// This is the point at which newly generated salt gets injected into
// the root of a newly created brine-generating splits-spliterator.
return new RandomSplitsSpliteratorWithSalt(source, index, fence, this, salt);
}
/* ---------------- public methods ---------------- */
// Stream methods for splitting
/**
* Constructs and returns a new instance of {@code AbstractSplittableWithBrineGenerator}
* that shares no mutable state with this instance. However, with very high
* probability, the set of values collectively generated by the two objects
* should have the same statistical properties as if the same quantity of
* values were generated by a single thread using a single may be
* {@code AbstractSplittableWithBrineGenerator} object. Either or both of the two objects
* further split using the {@code split()} method, and the same expected
* statistical properties apply to the entire set of generators constructed
* by such recursive splitting.
*
* @param brine a long value, of which the low 63 bits provide a unique id
* among calls to this method for constructing a single series of Generator objects.
*
* @return the new {@code AbstractSplittableWithBrineGenerator} instance
*/
public SplittableGenerator split(long brine) {
return this.split(this, brine);
}
/**
* Constructs and returns a new instance of {@code L64X128MixRandom}
* that shares no mutable state with this instance.
* However, with very high probability, the set of values collectively
* generated by the two objects has the same statistical properties as if
* same the quantity of values were generated by a single thread using
* a single {@code L64X128MixRandom} object. Either or both of the two
* objects may be further split using the {@code split} method,
* and the same expected statistical properties apply to the
* entire set of generators constructed by such recursive splitting.
*
* @param source a {@code SplittableGenerator} instance to be used instead
* of this one as a source of pseudorandom bits used to
* initialize the state of the new ones.
* @return a new instance of {@code L64X128MixRandom}
*/
public SplittableGenerator split(SplittableGenerator source) {
// It's a one-off: supply randomly chosen brine
return this.split(source, source.nextLong());
}
/**
* Constructs and returns a new instance of {@code AbstractSplittableWithBrineGenerator}
* that shares no mutable state with this instance. However, with very high
* probability, the set of values collectively generated by the two objects
* should have the same statistical properties as if the same quantity of
* values were generated by a single thread using a single may be
* {@code AbstractSplittableWithBrineGenerator} object. Either or both of the two objects
* further split using the {@code split()} method, and the same expected
* statistical properties apply to the entire set of generators constructed
* by such recursive splitting.
*
* @param source a {@code SplittableGenerator} instance to be used instead
* of this one as a source of pseudorandom bits used to
* initialize the state of the new ones.
* @param brine a long value, of which the low 63 bits provide a unique id
* among calls to this method for constructing a single series of
* {@code RandomGenerator} objects.
*
* @return the new {@code AbstractSplittableWithBrineGenerator} instance
*/
public abstract SplittableGenerator split(SplittableGenerator source, long brine);
/* ---------------- spliterator ---------------- */
/**
* Alternate spliterator for stream of generators of type SplittableGenerator. We multiplex
* the two versions into one class by treating "infinite" as equivalent to Long.MAX_VALUE.
* For splits, it uses the standard divide-by-two approach.
*
* This differs from {@code SplittableGenerator.RandomSplitsSpliterator} in that it provides
* a brine argument (a mixture of salt and an index) when calling the {@code split} method.
*/
static class RandomSplitsSpliteratorWithSalt
extends RandomSpliterator implements Spliterator<SplittableGenerator> {
final SplittableGenerator generatingGenerator;
final AbstractSplittableWithBrineGenerator constructingGenerator;
long salt;
// Important invariant: 0 <= index <= fence
// Important invariant: if salt and index are both nonzero,
// the rightmost 1-bit of salt is to the left of the leftmost 1-bit of index.
// If necessary, the salt can be leftshifted by SALT_SHIFT as many times as
// necessary to maintain the invariant.
RandomSplitsSpliteratorWithSalt(SplittableGenerator generatingGenerator, long index, long fence,
AbstractSplittableWithBrineGenerator constructingGenerator, long salt) {
super(index, fence);
this.generatingGenerator = generatingGenerator;
this.constructingGenerator = constructingGenerator;
while ((salt != 0) && (Long.compareUnsigned(salt & -salt, index) <= 0)) {
salt = salt << SALT_SHIFT;
}
this.salt = salt;
}
public Spliterator<SplittableGenerator> trySplit() {
long i = index, m = (i + fence) >>> 1;
if (m <= i) return null;
RandomSplitsSpliteratorWithSalt result =
new RandomSplitsSpliteratorWithSalt(generatingGenerator.split(), i, m, constructingGenerator, salt);
index = m;
while ((salt != 0) && (Long.compareUnsigned(salt & -salt, index) <= 0)) {
salt = salt << SALT_SHIFT;
}
return result;
}
public boolean tryAdvance(Consumer<? super SplittableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
consumer.accept(constructingGenerator.split(generatingGenerator, salt | i));
++i;
index = i;
if ((i & salt) != 0) salt <<= SALT_SHIFT;
return true;
}
return false;
}
public void forEachRemaining(Consumer<? super SplittableGenerator> consumer) {
if (consumer == null) throw new NullPointerException();
long i = index, f = fence;
if (i < f) {
index = f;
AbstractSplittableWithBrineGenerator c = constructingGenerator;
SplittableGenerator r = generatingGenerator;
do {
consumer.accept(c.split(r, salt | i));
++i;
if ((i & salt) != 0) salt <<= SALT_SHIFT;
} while (i < f);
}
}
}
}
}