/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package java.util;
/**
* An instance of this class is used to generate a stream of pseudorandom numbers. The class uses a 48-bit seed, which is modified using a linear congruential formula. (See Donald Knuth, The Art of Computer Programming, Volume 2, Section 3.2.1.)
* If two instances of Random are created with the same seed, and the same sequence of method calls is made for each, they will generate and return identical sequences of numbers. In order to guarantee this property, particular algorithms are specified for the class Random. Java implementations must use all the algorithms shown here for the class Random, for the sake of absolute portability of Java code. However, subclasses of class Random are permitted to use other algorithms, so long as they adhere to the general contracts for all the methods.
* The algorithms implemented by class Random use a protected utility method that on each invocation can supply up to 32 pseudorandomly generated bits.
* Since: JDK1.0, CLDC 1.0 Version: 12/17/01 (CLDC 1.1)
*/
public class Random{
private static final long multiplier = 0x5deece66dL;
/**
* @serial It is associated with the internal state of this generator.
*/
private long seed;
/**
* Creates a new random number generator. Its seed is initialized to a value based on the current time: public Random() { this(System.currentTimeMillis()); }
* See Also:System.currentTimeMillis()
*/
public Random() {
this(System.currentTimeMillis());
}
/**
* Creates a new random number generator using a single long seed: public Random(long seed) { setSeed(seed); } Used by method next to hold the state of the pseudorandom number generator.
* Parameters:seed - the initial seed.See Also:setSeed(long)
*/
public Random(long seed){
setSeed(seed);
}
/**
* Generates the next pseudorandom number. Subclass should override this, as this is used by all other methods.
* The general contract of next is that it returns an int value and if the argument bits is between 1 and 32 (inclusive), then that many low-order bits of the returned value will be (approximately) independently chosen bit values, each of which is (approximately) equally likely to be 0 or 1. The method next is implemented by class Random as follows:
* synchronized protected int next(int bits) { seed = (seed * 0x5DEECE66DL + 0xBL) & ((1L << 48) - 1); return (int)(seed >>> (48 - bits)); } This is a linear congruential pseudorandom number generator, as defined by D. H. Lehmer and described by Donald E. Knuth in
* Volume 2:
* , section 3.2.1.
*/
protected int next(int bits){
seed = (seed * multiplier + 0xbL) & ((1L << 48) - 1);
return (int) (seed >>> (48 - bits));
}
/**
* Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.
* The general contract of nextDouble is that one double value, chosen (approximately) uniformly from the range 0.0d (inclusive) to 1.0d (exclusive), is pseudorandomly generated and returned. All 253 possible float values of the form mx2-53 , where m is a positive integer less than 253, are produced with (approximately) equal probability. The method nextDouble is implemented by class Random as follows:
* public double nextDouble() { return (((long)next(26) << 27) + next(27)) / (double)(1L << 53); }
* The hedge "approximately" is used in the foregoing description only because the next method is only approximately an unbiased source of independently chosen bits. If it were a perfect source or randomly chosen bits, then the algorithm shown would choose double values from the stated range with perfect uniformity.
* [In early versions of Java, the result was incorrectly calculated as:
* return (((long)next(27) << 27) + next(27)) / (double)(1L << 54); This might seem to be equivalent, if not better, but in fact it introduced a large nonuniformity because of the bias in the rounding of floating-point numbers: it was three times as likely that the low-order bit of the significand would be 0 than that it would be 1! This nonuniformity probably doesn't matter much in practice, but we strive for perfection.]
*/
public double nextDouble(){
return ((((long) next(26) << 27) + next(27)) / (double) (1L << 53));
}
/**
* Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.
* The general contract of nextFloat is that one float value, chosen (approximately) uniformly from the range 0.0f (inclusive) to 1.0f (exclusive), is pseudorandomly generated and returned. All 224 possible float values of the form mx 2-24, where m is a positive integer less than 224 , are produced with (approximately) equal probability. The method nextFloat is implemented by class Random as follows:
* public float nextFloat() { return next(24) / ((float)(1 << 24)); } The hedge "approximately" is used in the foregoing description only because the next method is only approximately an unbiased source of independently chosen bits. If it were a perfect source or randomly chosen bits, then the algorithm shown would choose float values from the stated range with perfect uniformity.
* [In early versions of Java, the result was incorrectly calculated as:
* return next(30) / ((float)(1 << 30)); This might seem to be equivalent, if not better, but in fact it introduced a slight nonuniformity because of the bias in the rounding of floating-point numbers: it was slightly more likely that the low-order bit of the significand would be 0 than that it would be 1.]
*/
public float nextFloat(){
return (next(24) / 16777216f);
}
/**
* Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence. The general contract of nextInt is that one int value is pseudorandomly generated and returned. All 232 possible int values are produced with (approximately) equal probability. The method nextInt is implemented by class Random as follows: public int nextInt() { return next(32); }
*/
public int nextInt(){
return next(32);
}
/**
* Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence. The general contract of nextInt is that one int value in the specified range is pseudorandomly generated and returned. All n possible int values are produced with (approximately) equal probability. The method nextInt(int n) is implemented by class Random as follows: public int nextInt(int n) { if (n<=0) throw new IllegalArgumentException("n must be positive"); if ((n & -n) == n) // i.e., n is a power of 2 return (int)((n * (long)next(31)) >> 31); int bits, val; do { bits = next(31); val = bits % n; } while(bits - val + (n-1) < 0); return val; }
* The hedge "approximately" is used in the foregoing description only because the next method is only approximately an unbiased source of independently chosen bits. If it were a perfect source of randomly chosen bits, then the algorithm shown would choose int values from the stated range with perfect uniformity.
* The algorithm rejects values that would result in an uneven distribution (due to the fact that 2^31 is not divisible by n). The probability of a value being rejected depends on n. The worst case is n=2^30+1, for which the probability of a reject is 1/2, and the expected number of iterations before the loop terminates is 2.
* The algorithm treats the case where n is a power of two specially: it returns the correct number of high-order bits from the underlying pseudo-random number generator. In the absence of special treatment, the correct number of low-order bits would be returned. Linear congruential pseudo-random number generators such as the one implemented by this class are known to have short periods in the sequence of values of their low-order bits. Thus, this special case greatly increases the length of the sequence of values returned by successive calls to this method if n is a small power of two.
*/
public int nextInt(int n){
if (n > 0) {
if ((n & -n) == n) {
return (int) ((n * (long) next(31)) >> 31);
}
int bits, val;
do {
bits = next(31);
val = bits % n;
} while (bits - val + (n - 1) < 0);
return val;
}
throw new IllegalArgumentException();
}
/**
* Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence. The general contract of nextLong is that one long value is pseudorandomly generated and returned. All 264 possible long values are produced with (approximately) equal probability. The method nextLong is implemented by class Random as follows: public long nextLong() { return ((long)next(32) << 32) + next(32); }
*/
public long nextLong(){
return ((long) next(32) << 32) + next(32);
}
/**
* Sets the seed of this random number generator using a single long seed. The general contract of setSeed is that it alters the state of this random number generator object so as to be in exactly the same state as if it had just been created with the argument seed as a seed. The method setSeed is implemented by class Random as follows: synchronized public void setSeed(long seed) { this.seed = (seed ^ 0x5DEECE66DL) & ((1L << 48) - 1); } The implementation of setSeed by class Random happens to use only 48 bits of the given seed. In general, however, an overriding method may use all 64 bits of the long argument as a seed value.
*/
public void setSeed(long seed){
this.seed = (seed ^ multiplier) & ((1L << 48) - 1);
}
}