Class GaussianSampler

java.lang.Object

org.apache.commons.rng.sampling.distribution.GaussianSampler

All Implemented Interfaces:

ContinuousSampler, SharedStateContinuousSampler, SharedStateSampler<SharedStateContinuousSampler>

public class GaussianSampler
extends Object
implements SharedStateContinuousSampler

Sampling from a Gaussian distribution with given mean and standard deviation.

Note

The mean and standard deviation are validated to ensure they are finite. This prevents generation of NaN samples by avoiding invalid arithmetic (inf * 0 or inf - inf). However use of an extremely large standard deviation and/or mean may result in samples that are infinite; that is the parameters are not validated to prevent truncation of the output distribution.

Since:

1.1

Field Summary

Fields

Modifier and Type	Field	Description
private final double	mean	Mean.
private final NormalizedGaussianSampler	normalized	Normalized Gaussian sampler.
private final double	standardDeviation	standardDeviation.

Constructor Summary

Constructors

Modifier	Constructor	Description
private	GaussianSampler(double mean, double standardDeviation, NormalizedGaussianSampler normalized)
	GaussianSampler(NormalizedGaussianSampler normalized, double mean, double standardDeviation)	Create an instance.

Method Summary

Modifier and Type	Method	Description
static SharedStateContinuousSampler	of(NormalizedGaussianSampler normalized, double mean, double standardDeviation)	Create a new normalised Gaussian sampler.
double	sample()	Creates a double sample.
String	toString()
SharedStateContinuousSampler	withUniformRandomProvider(UniformRandomProvider rng)	Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Methods inherited from class Object

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

Methods inherited from interface ContinuousSampler

samples, samples

Field Details

mean

private final double mean

Mean.

standardDeviation

private final double standardDeviation

standardDeviation.

normalized

private final NormalizedGaussianSampler normalized

Normalized Gaussian sampler.

Constructor Details

GaussianSampler

public GaussianSampler(NormalizedGaussianSampler normalized,
 double mean,
 double standardDeviation)

Create an instance.

Parameters:

normalized - Generator of N(0,1) Gaussian distributed random numbers.

mean - Mean of the Gaussian distribution.

standardDeviation - Standard deviation of the Gaussian distribution.

Throws:

IllegalArgumentException - if standardDeviation <= 0 or is infinite; or mean is infinite

GaussianSampler

private GaussianSampler(double mean,
 double standardDeviation,
 NormalizedGaussianSampler normalized)

Parameters:

mean - Mean of the Gaussian distribution.

standardDeviation - Standard deviation of the Gaussian distribution.

normalized - Generator of N(0,1) Gaussian distributed random numbers.

Method Details

sample

public double sample()

Creates a double sample.

Specified by:

sample in interface ContinuousSampler

Returns:

a sample.

toString

public String toString()

Overrides:

toString in class Object

withUniformRandomProvider

public SharedStateContinuousSampler withUniformRandomProvider(UniformRandomProvider rng)

Create a new instance of the sampler with the same underlying state using the given uniform random provider as the source of randomness.

Note: This function is available if the underlying NormalizedGaussianSampler is a SharedStateSampler. Otherwise a run-time exception is thrown.

Specified by:

withUniformRandomProvider in interface SharedStateSampler<SharedStateContinuousSampler>

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

Throws:

UnsupportedOperationException - if the underlying sampler is not a SharedStateSampler or does not return a NormalizedGaussianSampler when sharing state.

Since:

1.3

of

public static SharedStateContinuousSampler of(NormalizedGaussianSampler normalized,
 double mean,
 double standardDeviation)

Create a new normalised Gaussian sampler.

Note: The shared-state functionality is available if the NormalizedGaussianSampler is a SharedStateSampler. Otherwise a run-time exception will be thrown when the sampler is used to share state.

Parameters:

normalized - Generator of N(0,1) Gaussian distributed random numbers.

mean - Mean of the Gaussian distribution.

standardDeviation - Standard deviation of the Gaussian distribution.

Returns:

the sampler

Throws:

IllegalArgumentException - if standardDeviation <= 0 or is infinite; or mean is infinite

Since:

1.3

See Also:

• withUniformRandomProvider(UniformRandomProvider)