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/* |
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* %W% %E% |
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* @(#)Random.java 1.44 05/02/01 |
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* |
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* Copyright 2004 Sun Microsystems, Inc. All rights reserved. |
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* SUN PROPRIETARY/CONFIDENTIAL. Use is subject to license terms. |
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* class <code>Math</code> simpler to use. |
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* |
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* @author Frank Yellin |
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* @version %I%, %G% |
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* @version 1.44, 02/01/05 |
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* @see java.lang.Math#random() |
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* @since JDK1.0 |
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*/ |
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} |
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/** |
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* Sets the seed of this random number generator using a single |
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* <code>long</code> seed. The general contract of <tt>setSeed</tt> |
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* is that it alters the state of this random number generator |
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* object so as to be in exactly the same state as if it had just |
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* been created with the argument <tt>seed</tt> as a seed. The method |
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* <tt>setSeed</tt> is implemented by class Random as follows: |
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* <blockquote><pre> |
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* synchronized public void setSeed(long seed) { |
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* this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1); |
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* haveNextNextGaussian = false; |
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* }</pre></blockquote> |
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* The implementation of <tt>setSeed</tt> by class <tt>Random</tt> |
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* happens to use only 48 bits of the given seed. In general, however, |
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* an overriding method may use all 64 bits of the long argument |
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* as a seed value. |
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* |
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* Note: Although the seed value is an AtomicLong, this method |
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* must still be synchronized to ensure correct semantics |
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* of haveNextNextGaussian. |
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* Sets the seed of this random number generator using a single |
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* <code>long</code> seed. The general contract of |
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* <tt>setSeed</tt> is that it alters the state of this random |
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* number generator object so as to be in exactly the same state |
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* as if it had just been created with the argument <tt>seed</tt> |
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* as a seed. The method <tt>setSeed</tt> is implemented by class |
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* Random using a thread-safe update of the seed to <code> (seed * |
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* 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)</code> and clearing the |
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* <code>haveNextNextGaussian</code> flag used by {@link |
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* #nextGaussian}. The implementation of <tt>setSeed</tt> by class |
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* <tt>Random</tt> happens to use only 48 bits of the given |
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* seed. In general, however, an overriding method may use all 64 |
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* bits of the long argument as a seed value. |
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* |
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* @param seed the initial seed. |
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*/ |
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/** |
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* Generates the next pseudorandom number. Subclass should |
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* override this, as this is used by all other methods.<p> |
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* The general contract of <tt>next</tt> is that it returns an |
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* <tt>int</tt> value and if the argument bits is between <tt>1</tt> |
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* and <tt>32</tt> (inclusive), then that many low-order bits of the |
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* returned value will be (approximately) independently chosen bit |
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* values, each of which is (approximately) equally likely to be |
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* <tt>0</tt> or <tt>1</tt>. The method <tt>next</tt> is implemented |
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* by class <tt>Random</tt> as follows: |
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* <blockquote><pre> |
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* synchronized protected int next(int bits) { |
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* seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1); |
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* return (int)(seed >>> (48 - bits)); |
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* }</pre></blockquote> |
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* This is a linear congruential pseudorandom number generator, as |
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* defined by D. H. Lehmer and described by Donald E. Knuth in <i>The |
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* Art of Computer Programming,</i> Volume 2: <i>Seminumerical |
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* override this, as this is used by all other methods.<p> The |
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* general contract of <tt>next</tt> is that it returns an |
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* <tt>int</tt> value and if the argument bits is between |
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* <tt>1</tt> and <tt>32</tt> (inclusive), then that many |
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* low-order bits of the returned value will be (approximately) |
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* independently chosen bit values, each of which is |
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* (approximately) equally likely to be <tt>0</tt> or |
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* <tt>1</tt>. The method <tt>next</tt> is implemented by class |
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* <tt>Random</tt> using a thread-safe update of the seed to <code> |
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* (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1)</code> and |
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* returning <code>(int)(seed >>> (48 - bits))</code>. This is a |
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* linear congruential pseudorandom number generator, as defined |
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* by D. H. Lehmer and described by Donald E. Knuth in <i>The Art |
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* of Computer Programming,</i> Volume 2: <i>Seminumerical |
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* Algorithms</i>, section 3.2.1. |
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* |
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* @param bits random bits |
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long oldseed, nextseed; |
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AtomicLong seed = this.seed; |
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do { |
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oldseed = seed.get(); |
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nextseed = (oldseed * multiplier + addend) & mask; |
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oldseed = seed.get(); |
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nextseed = (oldseed * multiplier + addend) & mask; |
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} while (!seed.compareAndSet(oldseed, nextseed)); |
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return (int)(nextseed >>> (48 - bits)); |
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} |
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* <tt>double</tt> value, chosen from (approximately) the usual |
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* normal distribution with mean <tt>0.0</tt> and standard deviation |
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* <tt>1.0</tt>, is pseudorandomly generated and returned. The method |
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* <tt>nextGaussian</tt> is implemented by class <tt>Random</tt> as follows: |
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* <tt>nextGaussian</tt> is implemented by class <tt>Random</tt> as if |
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* by a threadsafe version of the following: |
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* <blockquote><pre> |
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* synchronized public double nextGaussian() { |
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* public double nextGaussian() { |
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* if (haveNextNextGaussian) { |
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* haveNextNextGaussian = false; |
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* return nextNextGaussian; |
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* v2 = 2 * nextDouble() - 1; // between -1.0 and 1.0 |
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* s = v1 * v1 + v2 * v2; |
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* } while (s >= 1 || s == 0); |
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* double multiplier = Math.sqrt(-2 * Math.log(s)/s); |
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* double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
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* nextNextGaussian = v2 * multiplier; |
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* haveNextNextGaussian = true; |
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* return v1 * multiplier; |
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* G. Marsaglia, as described by Donald E. Knuth in <i>The Art of |
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* Computer Programming</i>, Volume 2: <i>Seminumerical Algorithms</i>, |
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* section 3.4.1, subsection C, algorithm P. Note that it generates two |
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* independent values at the cost of only one call to <tt>Math.log</tt> |
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* and one call to <tt>Math.sqrt</tt>. |
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* independent values at the cost of only one call to <tt>StrictMath.log</tt> |
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* and one call to <tt>StrictMath.sqrt</tt>. |
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* |
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* @return the next pseudorandom, Gaussian ("normally") distributed |
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* <code>double</code> value with mean <code>0.0</code> and |
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v2 = 2 * nextDouble() - 1; // between -1 and 1 |
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s = v1 * v1 + v2 * v2; |
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} while (s >= 1 || s == 0); |
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double multiplier = Math.sqrt(-2 * Math.log(s)/s); |
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double multiplier = StrictMath.sqrt(-2 * StrictMath.log(s)/s); |
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nextNextGaussian = v2 * multiplier; |
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haveNextNextGaussian = true; |
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return v1 * multiplier; |
