[jira] [Resolved] (RNG-131) TriangleSampler: Sample uniformly within a triangle

["Alex Herbert (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/RNG-131?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Alex Herbert resolved RNG-131.
------------------------------
    Fix Version/s: 1.4
       Resolution: Implemented

Added to master in commit 6e346fefff881e9fcc0509a5a0af93283089c53a

 

> TriangleSampler: Sample uniformly within a triangle
> ---------------------------------------------------
>
>                 Key: RNG-131
>                 URL: https://issues.apache.org/jira/browse/RNG-131
>             Project: Commons RNG
>          Issue Type: New Feature
>          Components: sampling
>    Affects Versions: 1.4
>            Reporter: Alex Herbert
>            Priority: Minor
>             Fix For: 1.4
>
>          Time Spent: 1h 20m
>  Remaining Estimate: 0h
>
> Create a sampler to sample uniformly within a triangle:
> {code:java}
> public abstract class TriangleSampler implements 
>         SharedStateSampler<TriangleSampler> {
>     public static TriangleSampler of(double[] a,
>                                      double[] b,
>                                      double[] c,
>                                      UniformRandomProvider rng);
> }
> {code}
> Sampling of a point p can be performed within a triangle with vertices a, b, c using:
> {noformat}
> v = b - a
> w = c - a
> p = a + s * v + t * w
> with s and t uniform deviates in [0, 1] and s + t <= 1
> Note: When s + t > 1 then transform s = 1 - s and t = 1 - t.{noformat}
> This algorithm is described in:
>  Turk, G. Generating random points in triangles. Glassner, A. S. (ed) (1990).
>  Graphic Gems, Academic Press, pp. 24-28.
> The method is applicable to any number of dimensions for the vertices. The triangle defines the 2D Euclidean space (plane) for sampling.



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