[commons-statistics] 11/12: Reinstate disabled test

[aherbert]

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aherbert pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-statistics.git

commit 00979a549aa7d3b82741f64923256a813577efdd
Author: Alex Herbert <aherb...@apache.org>
AuthorDate: Mon Nov 21 19:10:08 2022 +0000

    Reinstate disabled test
    
    The sampler is now created and all sample values asserted to be
    positive.
---
 .../commons/statistics/distribution/PoissonDistributionTest.java   | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git 
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
 
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
index 7e39964..095de50 100644
--- 
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
+++ 
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PoissonDistributionTest.java
@@ -19,7 +19,6 @@ package org.apache.commons.statistics.distribution;
 import org.apache.commons.rng.UniformRandomProvider;
 import org.apache.commons.rng.simple.RandomSource;
 import org.junit.jupiter.api.Assertions;
-import org.junit.jupiter.api.Disabled;
 import org.junit.jupiter.api.Test;
 import org.junit.jupiter.params.ParameterizedTest;
 import org.junit.jupiter.params.provider.CsvSource;
@@ -138,14 +137,14 @@ class PoissonDistributionTest extends 
BaseDiscreteDistributionTest {
      * Test creation of a sampler with a large mean that computes valid 
probabilities.
      */
     @Test
-    @Disabled("Commons RNG does not allow truncated Poisson distribution")
     void testCreateSamplerWithLargeMean() {
         final int mean = Integer.MAX_VALUE;
         final PoissonDistribution dist = PoissonDistribution.of(mean);
         // The mean is roughly the median for large mean
         Assertions.assertEquals(0.5, dist.cumulativeProbability(mean), 0.05);
         final UniformRandomProvider rng = RandomSource.SPLIT_MIX_64.create();
-        Assertions.assertDoesNotThrow(() -> dist.createSampler(rng),
-                "This distribution can be computed so should allow sampling");
+        dist.createSampler(rng)
+            .samples(50)
+            .forEach(i -> Assertions.assertTrue(i >= 0, () -> "Bad sample: " + 
i));
     }
 }