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dl |
1.1 |
/* |
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jsr166 |
1.26 |
* Copyright (c) 1995, 2008, Oracle and/or its affiliates. All rights reserved. |
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jsr166 |
1.20 |
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. |
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dl |
1.1 |
* |
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jsr166 |
1.20 |
* This code is free software; you can redistribute it and/or modify it |
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* under the terms of the GNU General Public License version 2 only, as |
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* published by the Free Software Foundation. Sun designates this |
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* particular file as subject to the "Classpath" exception as provided |
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* by Sun in the LICENSE file that accompanied this code. |
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* |
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* This code is distributed in the hope that it will be useful, but WITHOUT |
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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* version 2 for more details (a copy is included in the LICENSE file that |
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* accompanied this code). |
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* |
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* You should have received a copy of the GNU General Public License version |
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* 2 along with this work; if not, write to the Free Software Foundation, |
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. |
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* |
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jsr166 |
1.26 |
* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA |
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* or visit www.oracle.com if you need additional information or have any |
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* questions. |
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dl |
1.1 |
*/ |
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package java.util; |
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import java.io.*; |
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1.3 |
import java.util.concurrent.atomic.AtomicLong; |
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dl |
1.14 |
import sun.misc.Unsafe; |
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dl |
1.1 |
|
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/** |
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jsr166 |
1.11 |
* An instance of this class is used to generate a stream of |
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* pseudorandom numbers. The class uses a 48-bit seed, which is |
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* modified using a linear congruential formula. (See Donald Knuth, |
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jsr166 |
1.24 |
* <i>The Art of Computer Programming, Volume 2</i>, Section 3.2.1.) |
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dl |
1.1 |
* <p> |
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jsr166 |
1.12 |
* If two instances of {@code Random} are created with the same |
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jsr166 |
1.11 |
* seed, and the same sequence of method calls is made for each, they |
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* will generate and return identical sequences of numbers. In order to |
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* guarantee this property, particular algorithms are specified for the |
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jsr166 |
1.12 |
* class {@code Random}. Java implementations must use all the algorithms |
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* shown here for the class {@code Random}, for the sake of absolute |
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* portability of Java code. However, subclasses of class {@code Random} |
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jsr166 |
1.11 |
* are permitted to use other algorithms, so long as they adhere to the |
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dl |
1.1 |
* general contracts for all the methods. |
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* <p> |
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jsr166 |
1.12 |
* The algorithms implemented by class {@code Random} use a |
48 |
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* {@code protected} utility method that on each invocation can supply |
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dl |
1.1 |
* up to 32 pseudorandomly generated bits. |
50 |
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* <p> |
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jsr166 |
1.12 |
* Many applications will find the method {@link Math#random} simpler to use. |
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dl |
1.1 |
* |
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jsr166 |
1.25 |
* <p>Instances of {@code java.util.Random} are threadsafe. |
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* However, the concurrent use of the same {@code java.util.Random} |
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* instance across threads may encounter contention and consequent |
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* poor performance. Consider instead using |
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* {@link java.util.concurrent.ThreadLocalRandom} in multithreaded |
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* designs. |
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* |
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* <p>Instances of {@code java.util.Random} are not cryptographically |
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* secure. Consider instead using {@link java.security.SecureRandom} to |
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* get a cryptographically secure pseudo-random number generator for use |
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* by security-sensitive applications. |
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* |
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dl |
1.1 |
* @author Frank Yellin |
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jsr166 |
1.12 |
* @since 1.0 |
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1.1 |
*/ |
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public |
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class Random implements java.io.Serializable { |
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/** use serialVersionUID from JDK 1.1 for interoperability */ |
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static final long serialVersionUID = 3905348978240129619L; |
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/** |
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* The internal state associated with this pseudorandom number generator. |
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* (The specs for the methods in this class describe the ongoing |
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* computation of this value.) |
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*/ |
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dl |
1.14 |
private final AtomicLong seed; |
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1.1 |
|
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private final static long multiplier = 0x5DEECE66DL; |
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private final static long addend = 0xBL; |
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private final static long mask = (1L << 48) - 1; |
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|
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jsr166 |
1.4 |
/** |
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* Creates a new random number generator. This constructor sets |
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* the seed of the random number generator to a value very likely |
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* to be distinct from any other invocation of this constructor. |
88 |
dl |
1.1 |
*/ |
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jsr166 |
1.4 |
public Random() { this(++seedUniquifier + System.nanoTime()); } |
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private static volatile long seedUniquifier = 8682522807148012L; |
91 |
dl |
1.1 |
|
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jsr166 |
1.11 |
/** |
93 |
jsr166 |
1.12 |
* Creates a new random number generator using a single {@code long} seed. |
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* The seed is the initial value of the internal state of the pseudorandom |
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* number generator which is maintained by method {@link #next}. |
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* |
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* <p>The invocation {@code new Random(seed)} is equivalent to: |
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* <pre> {@code |
99 |
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* Random rnd = new Random(); |
100 |
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* rnd.setSeed(seed);}</pre> |
101 |
dl |
1.1 |
* |
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jsr166 |
1.12 |
* @param seed the initial seed |
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* @see #setSeed(long) |
104 |
dl |
1.1 |
*/ |
105 |
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public Random(long seed) { |
106 |
dl |
1.3 |
this.seed = new AtomicLong(0L); |
107 |
dl |
1.1 |
setSeed(seed); |
108 |
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} |
109 |
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110 |
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/** |
111 |
dl |
1.9 |
* Sets the seed of this random number generator using a single |
112 |
jsr166 |
1.12 |
* {@code long} seed. The general contract of {@code setSeed} is |
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* that it alters the state of this random number generator object |
114 |
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* so as to be in exactly the same state as if it had just been |
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* created with the argument {@code seed} as a seed. The method |
116 |
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* {@code setSeed} is implemented by class {@code Random} by |
117 |
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* atomically updating the seed to |
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* <pre>{@code (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1)}</pre> |
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* and clearing the {@code haveNextNextGaussian} flag used by {@link |
120 |
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* #nextGaussian}. |
121 |
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* |
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* <p>The implementation of {@code setSeed} by class {@code Random} |
123 |
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* happens to use only 48 bits of the given seed. In general, however, |
124 |
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* an overriding method may use all 64 bits of the {@code long} |
125 |
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* argument as a seed value. |
126 |
dl |
1.1 |
* |
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jsr166 |
1.12 |
* @param seed the initial seed |
128 |
dl |
1.1 |
*/ |
129 |
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synchronized public void setSeed(long seed) { |
130 |
dl |
1.3 |
seed = (seed ^ multiplier) & mask; |
131 |
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this.seed.set(seed); |
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jsr166 |
1.21 |
haveNextNextGaussian = false; |
133 |
dl |
1.1 |
} |
134 |
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/** |
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jsr166 |
1.12 |
* Generates the next pseudorandom number. Subclasses should |
137 |
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* override this, as this is used by all other methods. |
138 |
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* |
139 |
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* <p>The general contract of {@code next} is that it returns an |
140 |
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* {@code int} value and if the argument {@code bits} is between |
141 |
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* {@code 1} and {@code 32} (inclusive), then that many low-order |
142 |
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* bits of the returned value will be (approximately) independently |
143 |
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* chosen bit values, each of which is (approximately) equally |
144 |
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* likely to be {@code 0} or {@code 1}. The method {@code next} is |
145 |
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* implemented by class {@code Random} by atomically updating the seed to |
146 |
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* <pre>{@code (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)}</pre> |
147 |
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* and returning |
148 |
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* <pre>{@code (int)(seed >>> (48 - bits))}.</pre> |
149 |
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* |
150 |
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* This is a linear congruential pseudorandom number generator, as |
151 |
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* defined by D. H. Lehmer and described by Donald E. Knuth in |
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* <i>The Art of Computer Programming,</i> Volume 3: |
153 |
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* <i>Seminumerical Algorithms</i>, section 3.2.1. |
154 |
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* |
155 |
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* @param bits random bits |
156 |
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* @return the next pseudorandom value from this random number |
157 |
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* generator's sequence |
158 |
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* @since 1.1 |
159 |
dl |
1.1 |
*/ |
160 |
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protected int next(int bits) { |
161 |
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long oldseed, nextseed; |
162 |
dl |
1.6 |
AtomicLong seed = this.seed; |
163 |
dl |
1.1 |
do { |
164 |
jsr166 |
1.21 |
oldseed = seed.get(); |
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nextseed = (oldseed * multiplier + addend) & mask; |
166 |
jsr166 |
1.19 |
} while (!seed.compareAndSet(oldseed, nextseed)); |
167 |
dl |
1.1 |
return (int)(nextseed >>> (48 - bits)); |
168 |
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} |
169 |
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170 |
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/** |
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jsr166 |
1.11 |
* Generates random bytes and places them into a user-supplied |
172 |
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* byte array. The number of random bytes produced is equal to |
173 |
dl |
1.1 |
* the length of the byte array. |
174 |
jsr166 |
1.11 |
* |
175 |
jsr166 |
1.12 |
* <p>The method {@code nextBytes} is implemented by class {@code Random} |
176 |
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* as if by: |
177 |
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* <pre> {@code |
178 |
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* public void nextBytes(byte[] bytes) { |
179 |
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* for (int i = 0; i < bytes.length; ) |
180 |
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* for (int rnd = nextInt(), n = Math.min(bytes.length - i, 4); |
181 |
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* n-- > 0; rnd >>= 8) |
182 |
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* bytes[i++] = (byte)rnd; |
183 |
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* }}</pre> |
184 |
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* |
185 |
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* @param bytes the byte array to fill with random bytes |
186 |
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* @throws NullPointerException if the byte array is null |
187 |
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* @since 1.1 |
188 |
dl |
1.1 |
*/ |
189 |
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public void nextBytes(byte[] bytes) { |
190 |
jsr166 |
1.21 |
for (int i = 0, len = bytes.length; i < len; ) |
191 |
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for (int rnd = nextInt(), |
192 |
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n = Math.min(len - i, Integer.SIZE/Byte.SIZE); |
193 |
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n-- > 0; rnd >>= Byte.SIZE) |
194 |
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bytes[i++] = (byte)rnd; |
195 |
dl |
1.1 |
} |
196 |
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|
197 |
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/** |
198 |
jsr166 |
1.12 |
* Returns the next pseudorandom, uniformly distributed {@code int} |
199 |
jsr166 |
1.11 |
* value from this random number generator's sequence. The general |
200 |
jsr166 |
1.12 |
* contract of {@code nextInt} is that one {@code int} value is |
201 |
dl |
1.1 |
* pseudorandomly generated and returned. All 2<font size="-1"><sup>32 |
202 |
jsr166 |
1.12 |
* </sup></font> possible {@code int} values are produced with |
203 |
|
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* (approximately) equal probability. |
204 |
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* |
205 |
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* <p>The method {@code nextInt} is implemented by class {@code Random} |
206 |
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* as if by: |
207 |
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* <pre> {@code |
208 |
|
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* public int nextInt() { |
209 |
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* return next(32); |
210 |
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* }}</pre> |
211 |
dl |
1.1 |
* |
212 |
jsr166 |
1.12 |
* @return the next pseudorandom, uniformly distributed {@code int} |
213 |
|
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* value from this random number generator's sequence |
214 |
dl |
1.1 |
*/ |
215 |
jsr166 |
1.12 |
public int nextInt() { |
216 |
jsr166 |
1.21 |
return next(32); |
217 |
jsr166 |
1.12 |
} |
218 |
dl |
1.1 |
|
219 |
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/** |
220 |
jsr166 |
1.12 |
* Returns a pseudorandom, uniformly distributed {@code int} value |
221 |
dl |
1.1 |
* between 0 (inclusive) and the specified value (exclusive), drawn from |
222 |
|
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* this random number generator's sequence. The general contract of |
223 |
jsr166 |
1.12 |
* {@code nextInt} is that one {@code int} value in the specified range |
224 |
|
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* is pseudorandomly generated and returned. All {@code n} possible |
225 |
|
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* {@code int} values are produced with (approximately) equal |
226 |
|
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* probability. The method {@code nextInt(int n)} is implemented by |
227 |
|
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* class {@code Random} as if by: |
228 |
|
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* <pre> {@code |
229 |
dl |
1.1 |
* public int nextInt(int n) { |
230 |
jsr166 |
1.12 |
* if (n <= 0) |
231 |
|
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* throw new IllegalArgumentException("n must be positive"); |
232 |
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* |
233 |
|
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* if ((n & -n) == n) // i.e., n is a power of 2 |
234 |
|
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* return (int)((n * (long)next(31)) >> 31); |
235 |
dl |
1.1 |
* |
236 |
jsr166 |
1.12 |
* int bits, val; |
237 |
|
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* do { |
238 |
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* bits = next(31); |
239 |
|
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* val = bits % n; |
240 |
|
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* } while (bits - val + (n-1) < 0); |
241 |
|
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* return val; |
242 |
|
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* }}</pre> |
243 |
dl |
1.1 |
* |
244 |
jsr166 |
1.12 |
* <p>The hedge "approximately" is used in the foregoing description only |
245 |
dl |
1.1 |
* because the next method is only approximately an unbiased source of |
246 |
jsr166 |
1.11 |
* independently chosen bits. If it were a perfect source of randomly |
247 |
jsr166 |
1.12 |
* chosen bits, then the algorithm shown would choose {@code int} |
248 |
dl |
1.1 |
* values from the stated range with perfect uniformity. |
249 |
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* <p> |
250 |
|
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* The algorithm is slightly tricky. It rejects values that would result |
251 |
|
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* in an uneven distribution (due to the fact that 2^31 is not divisible |
252 |
|
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* by n). The probability of a value being rejected depends on n. The |
253 |
|
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* worst case is n=2^30+1, for which the probability of a reject is 1/2, |
254 |
|
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* and the expected number of iterations before the loop terminates is 2. |
255 |
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* <p> |
256 |
|
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* The algorithm treats the case where n is a power of two specially: it |
257 |
|
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* returns the correct number of high-order bits from the underlying |
258 |
|
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* pseudo-random number generator. In the absence of special treatment, |
259 |
|
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* the correct number of <i>low-order</i> bits would be returned. Linear |
260 |
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* congruential pseudo-random number generators such as the one |
261 |
|
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* implemented by this class are known to have short periods in the |
262 |
|
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* sequence of values of their low-order bits. Thus, this special case |
263 |
|
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* greatly increases the length of the sequence of values returned by |
264 |
|
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* successive calls to this method if n is a small power of two. |
265 |
|
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* |
266 |
|
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* @param n the bound on the random number to be returned. Must be |
267 |
jsr166 |
1.21 |
* positive. |
268 |
jsr166 |
1.12 |
* @return the next pseudorandom, uniformly distributed {@code int} |
269 |
|
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* value between {@code 0} (inclusive) and {@code n} (exclusive) |
270 |
|
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* from this random number generator's sequence |
271 |
jsr166 |
1.27 |
* @throws IllegalArgumentException if n is not positive |
272 |
dl |
1.1 |
* @since 1.2 |
273 |
|
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*/ |
274 |
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|
275 |
|
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public int nextInt(int n) { |
276 |
jsr166 |
1.12 |
if (n <= 0) |
277 |
dl |
1.1 |
throw new IllegalArgumentException("n must be positive"); |
278 |
|
|
|
279 |
|
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if ((n & -n) == n) // i.e., n is a power of 2 |
280 |
|
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return (int)((n * (long)next(31)) >> 31); |
281 |
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|
282 |
|
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int bits, val; |
283 |
|
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do { |
284 |
|
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bits = next(31); |
285 |
|
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val = bits % n; |
286 |
jsr166 |
1.12 |
} while (bits - val + (n-1) < 0); |
287 |
dl |
1.1 |
return val; |
288 |
|
|
} |
289 |
|
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|
290 |
|
|
/** |
291 |
jsr166 |
1.12 |
* Returns the next pseudorandom, uniformly distributed {@code long} |
292 |
jsr166 |
1.11 |
* value from this random number generator's sequence. The general |
293 |
jsr166 |
1.12 |
* contract of {@code nextLong} is that one {@code long} value is |
294 |
|
|
* pseudorandomly generated and returned. |
295 |
|
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* |
296 |
|
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* <p>The method {@code nextLong} is implemented by class {@code Random} |
297 |
|
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* as if by: |
298 |
|
|
* <pre> {@code |
299 |
dl |
1.1 |
* public long nextLong() { |
300 |
jsr166 |
1.12 |
* return ((long)next(32) << 32) + next(32); |
301 |
|
|
* }}</pre> |
302 |
dl |
1.1 |
* |
303 |
jsr166 |
1.12 |
* Because class {@code Random} uses a seed with only 48 bits, |
304 |
|
|
* this algorithm will not return all possible {@code long} values. |
305 |
|
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* |
306 |
|
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* @return the next pseudorandom, uniformly distributed {@code long} |
307 |
|
|
* value from this random number generator's sequence |
308 |
dl |
1.1 |
*/ |
309 |
|
|
public long nextLong() { |
310 |
|
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// it's okay that the bottom word remains signed. |
311 |
|
|
return ((long)(next(32)) << 32) + next(32); |
312 |
|
|
} |
313 |
|
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|
314 |
|
|
/** |
315 |
|
|
* Returns the next pseudorandom, uniformly distributed |
316 |
jsr166 |
1.12 |
* {@code boolean} value from this random number generator's |
317 |
|
|
* sequence. The general contract of {@code nextBoolean} is that one |
318 |
|
|
* {@code boolean} value is pseudorandomly generated and returned. The |
319 |
|
|
* values {@code true} and {@code false} are produced with |
320 |
|
|
* (approximately) equal probability. |
321 |
|
|
* |
322 |
|
|
* <p>The method {@code nextBoolean} is implemented by class {@code Random} |
323 |
|
|
* as if by: |
324 |
|
|
* <pre> {@code |
325 |
|
|
* public boolean nextBoolean() { |
326 |
|
|
* return next(1) != 0; |
327 |
|
|
* }}</pre> |
328 |
|
|
* |
329 |
|
|
* @return the next pseudorandom, uniformly distributed |
330 |
|
|
* {@code boolean} value from this random number generator's |
331 |
jsr166 |
1.21 |
* sequence |
332 |
dl |
1.1 |
* @since 1.2 |
333 |
|
|
*/ |
334 |
jsr166 |
1.12 |
public boolean nextBoolean() { |
335 |
jsr166 |
1.21 |
return next(1) != 0; |
336 |
jsr166 |
1.12 |
} |
337 |
dl |
1.1 |
|
338 |
|
|
/** |
339 |
jsr166 |
1.12 |
* Returns the next pseudorandom, uniformly distributed {@code float} |
340 |
|
|
* value between {@code 0.0} and {@code 1.0} from this random |
341 |
|
|
* number generator's sequence. |
342 |
|
|
* |
343 |
|
|
* <p>The general contract of {@code nextFloat} is that one |
344 |
|
|
* {@code float} value, chosen (approximately) uniformly from the |
345 |
|
|
* range {@code 0.0f} (inclusive) to {@code 1.0f} (exclusive), is |
346 |
|
|
* pseudorandomly generated and returned. All 2<font |
347 |
|
|
* size="-1"><sup>24</sup></font> possible {@code float} values |
348 |
|
|
* of the form <i>m x </i>2<font |
349 |
|
|
* size="-1"><sup>-24</sup></font>, where <i>m</i> is a positive |
350 |
|
|
* integer less than 2<font size="-1"><sup>24</sup> </font>, are |
351 |
|
|
* produced with (approximately) equal probability. |
352 |
|
|
* |
353 |
|
|
* <p>The method {@code nextFloat} is implemented by class {@code Random} |
354 |
|
|
* as if by: |
355 |
|
|
* <pre> {@code |
356 |
dl |
1.1 |
* public float nextFloat() { |
357 |
jsr166 |
1.12 |
* return next(24) / ((float)(1 << 24)); |
358 |
|
|
* }}</pre> |
359 |
|
|
* |
360 |
|
|
* <p>The hedge "approximately" is used in the foregoing description only |
361 |
jsr166 |
1.11 |
* because the next method is only approximately an unbiased source of |
362 |
jsr166 |
1.12 |
* independently chosen bits. If it were a perfect source of randomly |
363 |
|
|
* chosen bits, then the algorithm shown would choose {@code float} |
364 |
dl |
1.1 |
* values from the stated range with perfect uniformity.<p> |
365 |
|
|
* [In early versions of Java, the result was incorrectly calculated as: |
366 |
jsr166 |
1.12 |
* <pre> {@code |
367 |
|
|
* return next(30) / ((float)(1 << 30));}</pre> |
368 |
jsr166 |
1.11 |
* This might seem to be equivalent, if not better, but in fact it |
369 |
|
|
* introduced a slight nonuniformity because of the bias in the rounding |
370 |
|
|
* of floating-point numbers: it was slightly more likely that the |
371 |
|
|
* low-order bit of the significand would be 0 than that it would be 1.] |
372 |
dl |
1.1 |
* |
373 |
jsr166 |
1.12 |
* @return the next pseudorandom, uniformly distributed {@code float} |
374 |
|
|
* value between {@code 0.0} and {@code 1.0} from this |
375 |
|
|
* random number generator's sequence |
376 |
dl |
1.1 |
*/ |
377 |
|
|
public float nextFloat() { |
378 |
jsr166 |
1.12 |
return next(24) / ((float)(1 << 24)); |
379 |
dl |
1.1 |
} |
380 |
|
|
|
381 |
|
|
/** |
382 |
jsr166 |
1.11 |
* Returns the next pseudorandom, uniformly distributed |
383 |
jsr166 |
1.12 |
* {@code double} value between {@code 0.0} and |
384 |
|
|
* {@code 1.0} from this random number generator's sequence. |
385 |
|
|
* |
386 |
|
|
* <p>The general contract of {@code nextDouble} is that one |
387 |
|
|
* {@code double} value, chosen (approximately) uniformly from the |
388 |
|
|
* range {@code 0.0d} (inclusive) to {@code 1.0d} (exclusive), is |
389 |
|
|
* pseudorandomly generated and returned. |
390 |
|
|
* |
391 |
|
|
* <p>The method {@code nextDouble} is implemented by class {@code Random} |
392 |
|
|
* as if by: |
393 |
|
|
* <pre> {@code |
394 |
dl |
1.1 |
* public double nextDouble() { |
395 |
jsr166 |
1.12 |
* return (((long)next(26) << 27) + next(27)) |
396 |
|
|
* / (double)(1L << 53); |
397 |
|
|
* }}</pre> |
398 |
|
|
* |
399 |
|
|
* <p>The hedge "approximately" is used in the foregoing description only |
400 |
|
|
* because the {@code next} method is only approximately an unbiased |
401 |
|
|
* source of independently chosen bits. If it were a perfect source of |
402 |
jsr166 |
1.11 |
* randomly chosen bits, then the algorithm shown would choose |
403 |
jsr166 |
1.12 |
* {@code double} values from the stated range with perfect uniformity. |
404 |
dl |
1.1 |
* <p>[In early versions of Java, the result was incorrectly calculated as: |
405 |
jsr166 |
1.12 |
* <pre> {@code |
406 |
|
|
* return (((long)next(27) << 27) + next(27)) |
407 |
|
|
* / (double)(1L << 54);}</pre> |
408 |
jsr166 |
1.11 |
* This might seem to be equivalent, if not better, but in fact it |
409 |
|
|
* introduced a large nonuniformity because of the bias in the rounding |
410 |
|
|
* of floating-point numbers: it was three times as likely that the |
411 |
jsr166 |
1.12 |
* low-order bit of the significand would be 0 than that it would be 1! |
412 |
|
|
* This nonuniformity probably doesn't matter much in practice, but we |
413 |
|
|
* strive for perfection.] |
414 |
|
|
* |
415 |
|
|
* @return the next pseudorandom, uniformly distributed {@code double} |
416 |
|
|
* value between {@code 0.0} and {@code 1.0} from this |
417 |
|
|
* random number generator's sequence |
418 |
|
|
* @see Math#random |
419 |
dl |
1.1 |
*/ |
420 |
|
|
public double nextDouble() { |
421 |
jsr166 |
1.12 |
return (((long)(next(26)) << 27) + next(27)) |
422 |
jsr166 |
1.21 |
/ (double)(1L << 53); |
423 |
dl |
1.1 |
} |
424 |
|
|
|
425 |
|
|
private double nextNextGaussian; |
426 |
|
|
private boolean haveNextNextGaussian = false; |
427 |
|
|
|
428 |
|
|
/** |
429 |
|
|
* Returns the next pseudorandom, Gaussian ("normally") distributed |
430 |
jsr166 |
1.12 |
* {@code double} value with mean {@code 0.0} and standard |
431 |
|
|
* deviation {@code 1.0} from this random number generator's sequence. |
432 |
dl |
1.1 |
* <p> |
433 |
jsr166 |
1.12 |
* The general contract of {@code nextGaussian} is that one |
434 |
|
|
* {@code double} value, chosen from (approximately) the usual |
435 |
|
|
* normal distribution with mean {@code 0.0} and standard deviation |
436 |
|
|
* {@code 1.0}, is pseudorandomly generated and returned. |
437 |
|
|
* |
438 |
|
|
* <p>The method {@code nextGaussian} is implemented by class |
439 |
|
|
* {@code Random} as if by a threadsafe version of the following: |
440 |
|
|
* <pre> {@code |
441 |
|
|
* private double nextNextGaussian; |
442 |
|
|
* private boolean haveNextNextGaussian = false; |
443 |
|
|
* |
444 |
dl |
1.9 |
* public double nextGaussian() { |
445 |
jsr166 |
1.12 |
* if (haveNextNextGaussian) { |
446 |
|
|
* haveNextNextGaussian = false; |
447 |
|
|
* return nextNextGaussian; |
448 |
|
|
* } else { |
449 |
|
|
* double v1, v2, s; |
450 |
|
|
* do { |
451 |
|
|
* v1 = 2 * nextDouble() - 1; // between -1.0 and 1.0 |
452 |
|
|
* v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0 |
453 |
|
|
* s = v1 * v1 + v2 * v2; |
454 |
|
|
* } while (s >= 1 || s == 0); |
455 |
|
|
* double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
456 |
|
|
* nextNextGaussian = v2 * multiplier; |
457 |
|
|
* haveNextNextGaussian = true; |
458 |
|
|
* return v1 * multiplier; |
459 |
|
|
* } |
460 |
|
|
* }}</pre> |
461 |
jsr166 |
1.11 |
* This uses the <i>polar method</i> of G. E. P. Box, M. E. Muller, and |
462 |
|
|
* G. Marsaglia, as described by Donald E. Knuth in <i>The Art of |
463 |
jsr166 |
1.12 |
* Computer Programming</i>, Volume 3: <i>Seminumerical Algorithms</i>, |
464 |
dl |
1.1 |
* section 3.4.1, subsection C, algorithm P. Note that it generates two |
465 |
jsr166 |
1.12 |
* independent values at the cost of only one call to {@code StrictMath.log} |
466 |
|
|
* and one call to {@code StrictMath.sqrt}. |
467 |
dl |
1.1 |
* |
468 |
jsr166 |
1.12 |
* @return the next pseudorandom, Gaussian ("normally") distributed |
469 |
|
|
* {@code double} value with mean {@code 0.0} and |
470 |
|
|
* standard deviation {@code 1.0} from this random number |
471 |
|
|
* generator's sequence |
472 |
dl |
1.1 |
*/ |
473 |
|
|
synchronized public double nextGaussian() { |
474 |
|
|
// See Knuth, ACP, Section 3.4.1 Algorithm C. |
475 |
|
|
if (haveNextNextGaussian) { |
476 |
jsr166 |
1.21 |
haveNextNextGaussian = false; |
477 |
|
|
return nextNextGaussian; |
478 |
|
|
} else { |
479 |
dl |
1.1 |
double v1, v2, s; |
480 |
jsr166 |
1.21 |
do { |
481 |
dl |
1.1 |
v1 = 2 * nextDouble() - 1; // between -1 and 1 |
482 |
jsr166 |
1.21 |
v2 = 2 * nextDouble() - 1; // between -1 and 1 |
483 |
dl |
1.1 |
s = v1 * v1 + v2 * v2; |
484 |
jsr166 |
1.21 |
} while (s >= 1 || s == 0); |
485 |
|
|
double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
486 |
|
|
nextNextGaussian = v2 * multiplier; |
487 |
|
|
haveNextNextGaussian = true; |
488 |
|
|
return v1 * multiplier; |
489 |
dl |
1.1 |
} |
490 |
|
|
} |
491 |
|
|
|
492 |
|
|
/** |
493 |
|
|
* Serializable fields for Random. |
494 |
|
|
* |
495 |
jsr166 |
1.19 |
* @serialField seed long |
496 |
dl |
1.1 |
* seed for random computations |
497 |
jsr166 |
1.19 |
* @serialField nextNextGaussian double |
498 |
dl |
1.1 |
* next Gaussian to be returned |
499 |
|
|
* @serialField haveNextNextGaussian boolean |
500 |
|
|
* nextNextGaussian is valid |
501 |
|
|
*/ |
502 |
|
|
private static final ObjectStreamField[] serialPersistentFields = { |
503 |
|
|
new ObjectStreamField("seed", Long.TYPE), |
504 |
|
|
new ObjectStreamField("nextNextGaussian", Double.TYPE), |
505 |
|
|
new ObjectStreamField("haveNextNextGaussian", Boolean.TYPE) |
506 |
jsr166 |
1.12 |
}; |
507 |
dl |
1.1 |
|
508 |
|
|
/** |
509 |
jsr166 |
1.12 |
* Reconstitute the {@code Random} instance from a stream (that is, |
510 |
|
|
* deserialize it). |
511 |
dl |
1.1 |
*/ |
512 |
|
|
private void readObject(java.io.ObjectInputStream s) |
513 |
|
|
throws java.io.IOException, ClassNotFoundException { |
514 |
|
|
|
515 |
|
|
ObjectInputStream.GetField fields = s.readFields(); |
516 |
|
|
|
517 |
jsr166 |
1.21 |
// The seed is read in as {@code long} for |
518 |
|
|
// historical reasons, but it is converted to an AtomicLong. |
519 |
jsr166 |
1.23 |
long seedVal = fields.get("seed", -1L); |
520 |
dl |
1.1 |
if (seedVal < 0) |
521 |
|
|
throw new java.io.StreamCorruptedException( |
522 |
|
|
"Random: invalid seed"); |
523 |
dl |
1.14 |
resetSeed(seedVal); |
524 |
dl |
1.1 |
nextNextGaussian = fields.get("nextNextGaussian", 0.0); |
525 |
|
|
haveNextNextGaussian = fields.get("haveNextNextGaussian", false); |
526 |
|
|
} |
527 |
|
|
|
528 |
|
|
/** |
529 |
jsr166 |
1.12 |
* Save the {@code Random} instance to a stream. |
530 |
dl |
1.1 |
*/ |
531 |
jsr166 |
1.12 |
synchronized private void writeObject(ObjectOutputStream s) |
532 |
jsr166 |
1.21 |
throws IOException { |
533 |
jsr166 |
1.12 |
|
534 |
dl |
1.1 |
// set the values of the Serializable fields |
535 |
|
|
ObjectOutputStream.PutField fields = s.putFields(); |
536 |
jsr166 |
1.12 |
|
537 |
jsr166 |
1.21 |
// The seed is serialized as a long for historical reasons. |
538 |
dl |
1.3 |
fields.put("seed", seed.get()); |
539 |
dl |
1.1 |
fields.put("nextNextGaussian", nextNextGaussian); |
540 |
|
|
fields.put("haveNextNextGaussian", haveNextNextGaussian); |
541 |
|
|
|
542 |
|
|
// save them |
543 |
|
|
s.writeFields(); |
544 |
|
|
} |
545 |
|
|
|
546 |
dl |
1.14 |
// Support for resetting seed while deserializing |
547 |
|
|
private static final Unsafe unsafe = Unsafe.getUnsafe(); |
548 |
|
|
private static final long seedOffset; |
549 |
|
|
static { |
550 |
|
|
try { |
551 |
|
|
seedOffset = unsafe.objectFieldOffset |
552 |
|
|
(Random.class.getDeclaredField("seed")); |
553 |
jsr166 |
1.21 |
} catch (Exception ex) { throw new Error(ex); } |
554 |
dl |
1.14 |
} |
555 |
|
|
private void resetSeed(long seedVal) { |
556 |
|
|
unsafe.putObjectVolatile(this, seedOffset, new AtomicLong(seedVal)); |
557 |
|
|
} |
558 |
jsr166 |
1.11 |
} |