This is an automated email from the ASF dual-hosted git repository. aherbert pushed a commit to branch master in repository https://gitbox.apache.org/repos/asf/commons-statistics.git
The following commit(s) were added to refs/heads/master by this push: new 3d2cc5e Add comment that RNG 1.6 will not be affected by the change 3d2cc5e is described below commit 3d2cc5e959641b4de3725134d36163e927a1e15b Author: aherbert <aherb...@apache.org> AuthorDate: Wed Nov 30 14:13:58 2022 +0000 Add comment that RNG 1.6 will not be affected by the change --- .../org/apache/commons/statistics/distribution/ParetoDistribution.java | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java index 41877c1..ce4415b 100644 --- a/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java +++ b/commons-statistics-distribution/src/main/java/org/apache/commons/statistics/distribution/ParetoDistribution.java @@ -296,12 +296,13 @@ public final class ParetoDistribution extends AbstractContinuousDistribution { @Override public ContinuousDistribution.Sampler createSampler(final UniformRandomProvider rng) { // Pareto distribution sampler. - // Commons RNG v1.5 uses nextDouble() for (1 - p) effectively sampling from p in (0, 1]. + // Commons RNG v1.5 uses nextDouble for (1 - p) effectively sampling from p in (0, 1]. // Ensure sampling is concentrated at the lower / upper bound at extreme shapes: // Large shape should sample using p in [0, 1) (lower bound) // Small shape should sample using p in (0, 1] (upper bound) // Note: For small shape the input RNG is also wrapped to use nextLong as the source of // randomness; this ensures the nextDouble method uses the interface output of [0, 1). + // Commons RNG v1.6 uses nextLong and will not be affected changes to nextDouble. final UniformRandomProvider wrappedRng = shape >= 1 ? new InvertedRNG(rng) : rng::nextLong; return InverseTransformParetoSampler.of(wrappedRng, scale, shape)::sample; }