broadwick.rng

Class RNG

java.lang.Object

broadwick.rng.RNG

All Implemented Interfaces:

Serializable

public class RNG
extends Object
implements Serializable

Random number generator singleton class This class is not thread safe.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RNG.Generator Random number generator type.

Field Summary

Fields

Modifier and Type	Field and Description
private org.apache.commons.math3.random.RandomDataGenerator	generator Random number generator type.
private String	name

Constructor Summary

Constructors

Constructor and Description
RNG() Create a random number generator using the default JDK-provied PRNG.
RNG(RNG.Generator gen) Create a random number generator from a given generator using the current time as a seed.

Method Summary

Modifier and Type	Method and Description
int	getBinomial(int n, double p) Generates a random value from the binomial distribution with the given N and p.
boolean	getBoolean() Get a boolean (true/false) value.
double	getDouble() Generates a uniformly distributed random value from the open interval ( 0.0, 1.0) (i.e., endpoints excluded).
double	getDouble(double lower, double upper) Generates a uniformly distributed random value from the open interval ( lower, upper) (i.e., endpoints excluded).
double	getGaussian(double mu, double sigma) Generates a random value from the Normal (or Gaussian) distribution with the given mean and standard deviation.
int	getInteger(int lower, int upper) Generates a uniformly distributed random integer between lower and upper (endpoints included).
long	getPoisson(double mean) Generates a random value from the Poisson distribution with the given mean.
void	seed(int seed) Seed the random number generator.
<T> List<T>	selectManyOf(Collection<T> objects, int n) Randomly pick N objects from an array of objects.
<T> Set<T>	selectManyOf(Set<T> objects, int n) Randomly pick N objects from an array of objects.
<T> List<T>	selectManyOf(T[] objects, int n) Randomly pick N objects from an array of objects.
<T> T	selectOneOf(Collection<T> objects) Randomly pick an object from an array of objects.
<T> T	selectOneOf(Set<T> set)
<T> T	selectOneOf(T[] objects) Randomly pick an object from an array of objects.
<T> T	selectOneOf(T[] objects, double[] probabilities) Randomly pick an object from an array of objects.
static List<String>	validGenerators() Get a list of valid geometries for the lattice.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

generator

private final org.apache.commons.math3.random.RandomDataGenerator generator

Random number generator type.

name

private String name

Constructor Detail

RNG

public RNG()

Create a random number generator using the default JDK-provied PRNG.

RNG

public RNG(RNG.Generator gen)

Create a random number generator from a given generator using the current time as a seed.

Parameters:

gen - the random number generator to use.

Method Detail

validGenerators

public static List<String> validGenerators()

Get a list of valid geometries for the lattice.

Returns:

List<> a list of valid lattice geometries (in uppercase)

seed

public final void seed(int seed)

Seed the random number generator.

Parameters:

seed - the seed to use in the Rng

getDouble

public final double getDouble()

Generates a uniformly distributed random value from the open interval ( 0.0, 1.0) (i.e., endpoints excluded).

Definition: Uniform Distribution 0.0 and 1.0 - 0.0 are the location and scale parameters, respectively.

Returns:

uniformly distributed random value between lower and upper (exclusive)

getDouble

public final double getDouble(double lower,
                              double upper)

Generates a uniformly distributed random value from the open interval ( lower, upper) (i.e., endpoints excluded).

Definition: Uniform Distribution lower and upper - lower are the location and scale parameters, respectively.

Preconditions:

• lower < upper (otherwise an IllegalArgumentException is thrown.)

Parameters:

lower - lower endpoint of the interval of support

upper - upper endpoint of the interval of support

Returns:

uniformly distributed random value between lower and upper (exclusive)

getInteger

public final int getInteger(int lower,
                            int upper)

Generates a uniformly distributed random integer between lower and upper (endpoints included).

The generated integer will be random, but not cryptographically secure. To generate cryptographically secure integer sequences, use nextSecureInt.

Preconditions:

• lower < upper (otherwise an IllegalArgumentException is thrown.)

Parameters:

lower - lower bound for generated integer

upper - upper bound for generated integer

Returns:

a random integer greater than or equal to lower and less than or equal * * * to upper. If lower == upper then lower is returned.

getPoisson

public final long getPoisson(double mean)

Generates a random value from the Poisson distribution with the given mean.

Definition: Poisson Distribution

Preconditions:

• The specified mean must be positive (otherwise an IllegalArgumentException is thrown.)

Parameters:

mean - Mean of the distribution

Returns:

poisson deviate with the specified mean

getGaussian

public final double getGaussian(double mu,
                                double sigma)

Generates a random value from the Normal (or Gaussian) distribution with the given mean and standard deviation.

Definition: Normal Distribution

Preconditions:

• sigma > 0 (otherwise an IllegalArgumentException is thrown.)

Parameters:

mu - Mean of the distribution

sigma - Standard deviation given as a percentage of the mean.

Returns:

random value from Gaussian distribution with mean = mu, standard deviation = sigma

getBoolean

public final boolean getBoolean()

Get a boolean (true/false) value.

Returns:

boolean random true/false value

getBinomial

public final int getBinomial(int n,
                             double p)

Generates a random value from the binomial distribution with the given N and p. The returned value is a random integer drawn from

P(x) = (ⁿ_x) p^x(1-p)^(n-x)

Successive draws from this distribution can be combined, i.e. if X ~ getBinomial(n, p) and Y ~ getBinomial(m, p) are independent binomial variables , then X + Y is again a binomial variable; its distribution is getBinomial(n+m, p)

Parameters:

n - the number of trials.

p - the probability of success of each trial.

Returns:

the number of successes on n trials.

selectOneOf

public final <T> T selectOneOf(T[] objects)

Randomly pick an object from an array of objects.

Type Parameters:

T - generic type of the array elements.

Parameters:

objects - an array of objects, one of whom is to be picked.

Returns:

a random element from objects.

selectOneOf

public final <T> T selectOneOf(T[] objects,
                               double[] probabilities)

Randomly pick an object from an array of objects.

Type Parameters:

T - generic type of the array elements.

Parameters:

objects - an array of objects, one of whom is to be picked.

probabilities - the probabilities of selecting each of the objects.

Returns:

a random element from objects.

selectOneOf

public <T> T selectOneOf(Set<T> set)

Type Parameters:

T - generic type of the Set elements

Parameters:

set - a Set in which to look for a random element

Returns:

a random element in the Set or null if the set is empty

selectOneOf

public final <T> T selectOneOf(Collection<T> objects)

Randomly pick an object from an array of objects.

Type Parameters:

T - The type of the elements in the collection

Parameters:

objects - an array of objects, one of whom is to be picked.

Returns:

a random element from objects.

selectManyOf

public final <T> List<T> selectManyOf(T[] objects,
                                      int n)

Randomly pick N objects from an array of objects. Note, this assumes that N much much less than the size of the array being sampled from, if this is not the case this method is VERY slow.

Type Parameters:

T - The type of the elements in the collection

Parameters:

objects - an array of objects, one of whom is to be picked.

n - the number of objects we will select.

Returns:

a random element from objects.

selectManyOf

public final <T> List<T> selectManyOf(Collection<T> objects,
                                      int n)

Randomly pick N objects from an array of objects. Note, this assumes that N much much less than the size of the array being sampled from, if this is not the case this method is VERY slow.

Type Parameters:

T - The type of the elements in the collection

Parameters:

objects - an array of objects, one of whom is to be picked.

n - the number of objects we will select.

Returns:

a random element from objects.

selectManyOf

public final <T> Set<T> selectManyOf(Set<T> objects,
                                     int n)

Randomly pick N objects from an array of objects. Note, this assumes that N much much less than the size of the array being sampled from, if this is not the case this method is VERY slow.

Type Parameters:

T - The type of the elements in the collection

Parameters:

objects - an array of objects, one of whom is to be picked.

n - the number of objects we will select.

Returns:

a random element from objects.