Class BoxSampler

java.lang.Object

org.apache.commons.rng.sampling.shape.BoxSampler

All Implemented Interfaces:

ObjectSampler<double[]>, SharedStateObjectSampler<double[]>, SharedStateSampler<SharedStateObjectSampler<double[]>>

Direct Known Subclasses:

BoxSampler.BoxSampler2D, BoxSampler.BoxSampler3D, BoxSampler.BoxSamplerND

public abstract class BoxSampler
extends Object
implements SharedStateObjectSampler<double[]>

Generate points uniformly distributed within a n-dimension box (hyperrectangle).

Sampling uses:

• UniformRandomProvider.nextDouble()

Since:

1.4

See Also:

• Hyperrectangle (Wikipedia)

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
private static final class	BoxSampler.BoxSampler2D	Sample uniformly from a box in 2D.
private static final class	BoxSampler.BoxSampler3D	Sample uniformly from a box in 3D.
private static final class	BoxSampler.BoxSamplerND	Sample uniformly from a box in ND.

Field Summary

Fields

Modifier and Type	Field	Description
private final UniformRandomProvider	rng	The source of randomness.
private static final int	THREE_D	The dimension for 3D sampling.
private static final int	TWO_D	The dimension for 2D sampling.

Constructor Summary

Constructors

Constructor	Description
BoxSampler(UniformRandomProvider rng)

Method Summary

Modifier and Type	Method	Description
(package private) double	createSample(double a, double b)	Creates the sample between bound a and b.
static BoxSampler	of(UniformRandomProvider rng, double[] a, double[] b)	Create a box sampler with bounds a and b.
abstract double[]	sample()	Create an object sample.
abstract BoxSampler	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, toString, wait, wait, wait

Methods inherited from interface ObjectSampler

samples, samples

Field Details

TWO_D

private static final int TWO_D

The dimension for 2D sampling.

See Also:

• Constant Field Values

THREE_D

private static final int THREE_D

The dimension for 3D sampling.

See Also:

• Constant Field Values

rng

private final UniformRandomProvider rng

The source of randomness.

Constructor Details

BoxSampler

BoxSampler(UniformRandomProvider rng)

Parameters:

rng - Source of randomness.

Method Details

sample

public abstract double[] sample()

Description copied from interface: ObjectSampler

Create an object sample.

Specified by:

sample in interface ObjectSampler<double[]>

Returns:

a random Cartesian coordinate within the box.

createSample

double createSample(double a,
 double b)

Creates the sample between bound a and b.

Parameters:

a - Bound a

b - Bound b

Returns:

the sample

withUniformRandomProvider

public abstract BoxSampler 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.

Specified by:

withUniformRandomProvider in interface SharedStateSampler<SharedStateObjectSampler<double[]>>

Parameters:

rng - Generator of uniformly distributed random numbers.

Returns:

the sampler

of

public static BoxSampler of(UniformRandomProvider rng,
 double[] a,
 double[] b)

Create a box sampler with bounds a and b. Sampled points are uniformly distributed within the box defined by the bounds.

Sampling is supported in dimensions of 2 or above. Single dimension sampling can be performed using a LineSampler.

Note: There is no requirement that a <= b. The samples will be uniformly distributed in the range a to b for each dimension.

Parameters:

rng - Source of randomness.

a - Bound a.

b - Bound b.

Returns:

the sampler

Throws:

IllegalArgumentException - If the bounds do not have the same dimension; the dimension is less than 2; or bounds have non-finite coordinates.