[jira] [Commented] (RNG-146) GaussianSampler should not allow infinite standard deviation

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

    [ https://issues.apache.org/jira/browse/RNG-146?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17377989#comment-17377989 ] 

Alex Herbert commented on RNG-146:
----------------------------------

Added detection of infinite and NaN values for both the mean and standard deviation. I have added javadoc to indicate the use of finite values for the mean and standard deviation will avoid NaN (e.g. by avoiding inf * 0 and inf - inf). The javadoc states that detection of a truncated distribution is not performed.

Commit:
6edeb102c5310895480781e14c14facaf12ed864

> GaussianSampler should not allow infinite standard deviation
> ------------------------------------------------------------
>
>                 Key: RNG-146
>                 URL: https://issues.apache.org/jira/browse/RNG-146
>             Project: Commons RNG
>          Issue Type: Bug
>          Components: sampling
>    Affects Versions: 1.3
>            Reporter: Alex Herbert
>            Priority: Trivial
>
> The GaussianSampler requires the standard deviation is strictly positive. It allows an infinite value. This will produce a NaN output if the NormalizedGaussianSampler returns 0:
> {code:java}
> @Test
> public void testInfiniteStdDev() {
>     NormalizedGaussianSampler gauss = new NormalizedGaussianSampler() {
>         @Override
>         public double sample() {
>             return 0;
>         }
>     };
>     GaussianSampler s = new GaussianSampler(gauss, 0, Double.POSITIVE_INFINITY);
>     Assert.assertEquals(Double.NaN, s.sample(), 0.0);
> }
> {code}
> A fix is to require the standard deviation is finite.



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