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Posted to commits@commons.apache.org by ah...@apache.org on 2022/11/21 19:23:24 UTC
[commons-statistics] 11/12: Reinstate disabled test
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
commit 00979a549aa7d3b82741f64923256a813577efdd
Author: Alex Herbert <ah...@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));
}
}