Class BoxSampler

java.lang.Object

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

All Implemented Interfaces:

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

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)

Method Summary

Modifier and Type	Method	Description
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

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.

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.