Package org.apache.commons.rng.sampling.shape

Class TriangleSampler

java.lang.Object

org.apache.commons.rng.sampling.shape.TriangleSampler

All Implemented Interfaces:

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

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

Generate points uniformly distributed within a triangle.

• Uses the algorithm described in:

  Turk, G. Generating random points in triangles. Glassner, A. S. (ed) (1990).
  Graphic Gems Academic Press, pp. 24-28.

Sampling uses:

• UniformRandomProvider.nextDouble()

Since:

1.4

Method Summary

Modifier and Type	Method	Description
protected abstract double[]	createSample(double p1msmt, double s, double t)	Creates the sample given the random variates s and t in the interval [0, 1] and s + t <= 1.
static TriangleSampler	of(UniformRandomProvider rng, double[] a, double[] b, double[] c)	Create a triangle sampler with vertices a, b and c.
double[]	sample()	Create an object sample.
abstract TriangleSampler	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 java.lang.Object

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

Methods inherited from interface org.apache.commons.rng.sampling.ObjectSampler

samples, samples

Method Detail

sample

public 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 triangle.

createSample

protected abstract double[] createSample(double p1msmt,
                                         double s,
                                         double t)

Creates the sample given the random variates s and t in the interval [0, 1] and s + t <= 1. The sum 1 - s - t is provided. The sample can be obtained from the triangle abc using:

 p = a(1 - s - t) + sb + tc
 

Parameters:

p1msmt - plus 1 minus s minus t (1 - s - t)

s - the first variate s

t - the second variate t

Returns:

the sample

withUniformRandomProvider

public abstract TriangleSampler 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 TriangleSampler of(UniformRandomProvider rng,
                                 double[] a,
                                 double[] b,
                                 double[] c)

Create a triangle sampler with vertices a, b and c. Sampled points are uniformly distributed within the triangle.

Sampling is supported in dimensions of 2 or above. Samples will lie in the plane (2D Euclidean space) defined by using the three triangle vertices to create two vectors starting at a point in the plane and orientated in different directions along the plane.

No test for collinear points is performed. If the points are collinear the sampling distribution is undefined.

Parameters:

rng - Source of randomness.

a - The first vertex.

b - The second vertex.

c - The third vertex.

Returns:

the sampler

Throws:

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