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https://issues.apache.org/jira/browse/RNG-146?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17369134#comment-17369134
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Alex Herbert commented on RNG-146:
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I am undecided about whether to even limit the constructor to accept standard
deviations that would clip the distribution. This may set a precedent that we
should think about restricting the parameters for other distribution samplers.
Preventing non-finite input seems sensible. But preventing bad parameters
because we think they are bad may not be everyone's choice. I will look through
the other distribution samplers and check which of the distributions can be
truncated by ill chosen parameters.
> 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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