org.apache.commons.math3.random
Class AbstractRandomGenerator

java.lang.Object
  extended by org.apache.commons.math3.random.AbstractRandomGenerator
All Implemented Interfaces:
RandomGenerator

public abstract class AbstractRandomGenerator
extends Object
implements RandomGenerator

Abstract class implementing the RandomGenerator interface. Default implementations for all methods other than nextDouble() and setSeed(long) are provided.

All data generation methods are based on code nextDouble(). Concrete implementations must override this method and should provide better / more performant implementations of the other methods if the underlying PRNG supplies them.

Since:
1.1
Version:
$Id: AbstractRandomGenerator.java 3720 2012-03-16 16:34:17Z CardosoP $

Constructor Summary
AbstractRandomGenerator()
          Construct a RandomGenerator.
 
Method Summary
 void clear()
          Clears the cache used by the default implementation of nextGaussian().
 boolean nextBoolean()
          Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.
 void nextBytes(byte[] bytes)
          Generates random bytes and places them into a user-supplied byte array.
abstract  double nextDouble()
          Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.
 float nextFloat()
          Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.
 double nextGaussian()
          Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
 int nextInt()
          Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.
 int nextInt(int n)
          Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
 long nextLong()
          Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
 void setSeed(int seed)
          Sets the seed of the underlying random number generator using an int seed.
 void setSeed(int[] seed)
          Sets the seed of the underlying random number generator using an int array seed.
abstract  void setSeed(long seed)
          Sets the seed of the underlying random number generator using a long seed.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

AbstractRandomGenerator

public AbstractRandomGenerator()
Construct a RandomGenerator.

Method Detail

clear

public void clear()
Clears the cache used by the default implementation of nextGaussian(). Implementations that do not override the default implementation of nextGaussian should call this method in the implementation of setSeed(long)


setSeed

public void setSeed(int seed)
Sets the seed of the underlying random number generator using an int seed.

Sequences of values generated starting with the same seeds should be identical.

Specified by:
setSeed in interface RandomGenerator
Parameters:
seed - the seed value

setSeed

public void setSeed(int[] seed)
Sets the seed of the underlying random number generator using an int array seed.

Sequences of values generated starting with the same seeds should be identical.

Specified by:
setSeed in interface RandomGenerator
Parameters:
seed - the seed value

setSeed

public abstract void setSeed(long seed)
Sets the seed of the underlying random number generator using a long seed. Sequences of values generated starting with the same seeds should be identical.

Implementations that do not override the default implementation of nextGaussian should include a call to clear() in the implementation of this method.

Specified by:
setSeed in interface RandomGenerator
Parameters:
seed - the seed value

nextBytes

public void nextBytes(byte[] bytes)
Generates random bytes and places them into a user-supplied byte array. The number of random bytes produced is equal to the length of the byte array.

The default implementation fills the array with bytes extracted from random integers generated using nextInt().

Specified by:
nextBytes in interface RandomGenerator
Parameters:
bytes - the non-null byte array in which to put the random bytes

nextInt

public int nextInt()
Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence. All 232 possible int values should be produced with (approximately) equal probability.

The default implementation provided here returns

 (int) (nextDouble() * Integer.MAX_VALUE)
 

Specified by:
nextInt in interface RandomGenerator
Returns:
the next pseudorandom, uniformly distributed int value from this random number generator's sequence

nextInt

public int nextInt(int n)
Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.

The default implementation returns

 (int) (nextDouble() * n
 

Specified by:
nextInt in interface RandomGenerator
Parameters:
n - the bound on the random number to be returned. Must be positive.
Returns:
a pseudorandom, uniformly distributed int value between 0 (inclusive) and n (exclusive).
Throws:
NotStrictlyPositiveException - if n <= 0.

nextLong

public long nextLong()
Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence. All 264 possible long values should be produced with (approximately) equal probability.

The default implementation returns

 (long) (nextDouble() * Long.MAX_VALUE)
 

Specified by:
nextLong in interface RandomGenerator
Returns:
the next pseudorandom, uniformly distributed long value from this random number generator's sequence

nextBoolean

public boolean nextBoolean()
Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.

The default implementation returns

 nextDouble() <= 0.5
 

Specified by:
nextBoolean in interface RandomGenerator
Returns:
the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence

nextFloat

public float nextFloat()
Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.

The default implementation returns

 (float) nextDouble() 
 

Specified by:
nextFloat in interface RandomGenerator
Returns:
the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence

nextDouble

public abstract double nextDouble()
Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.

This method provides the underlying source of random data used by the other methods.

Specified by:
nextDouble in interface RandomGenerator
Returns:
the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence

nextGaussian

public double nextGaussian()
Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.

The default implementation uses the Polar Method due to G.E.P. Box, M.E. Muller and G. Marsaglia, as described in D. Knuth, The Art of Computer Programming, 3.4.1C.

The algorithm generates a pair of independent random values. One of these is cached for reuse, so the full algorithm is not executed on each activation. Implementations that do not override this method should make sure to call clear() to clear the cached value in the implementation of setSeed(long).

Specified by:
nextGaussian in interface RandomGenerator
Returns:
the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence


Copyright © 2016 CNES. All Rights Reserved.