[commons-statistics] 16/35: Increase LaplaceDistribution test coverage.

[ah...@apache.org]

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

commit 4b859983f87086a71a4aef3d07e73c3c61934f8a
Author: aherbert <ah...@apache.org>
AuthorDate: Tue Jun 23 14:46:43 2020 +0100

    Increase LaplaceDistribution test coverage.
---
 .../distribution/LaplaceDistributionTest.java      | 27 ++++++++++++++++++++++
 1 file changed, 27 insertions(+)

diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/LaplaceDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/LaplaceDistributionTest.java
index 827dfa5..80a5fb6 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/LaplaceDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/LaplaceDistributionTest.java
@@ -67,4 +67,31 @@ public class LaplaceDistributionTest extends ContinuousDistributionAbstractTest
             0.500000000, 0.816060279, 0.932332358, 0.975106466, 0.990842181, 0.996631027
         };
     }
+
+    // ----------------- Additional test cases ---------------------------------
+
+    @Test
+    public void testInverseCumulativeProbabilityExtremes() {
+        setInverseCumulativeTestPoints(new double[] {0.0, 1.0});
+        setInverseCumulativeTestValues(new double[] {Double.NEGATIVE_INFINITY, Double.POSITIVE_INFINITY});
+        verifyInverseCumulativeProbabilities();
+    }
+
+    @Test
+    public void testConstructorPrecondition1() {
+        Assertions.assertThrows(IllegalArgumentException.class, () -> new LaplaceDistribution(0, -0.1));
+    }
+
+    @Test
+    public void testMoments() {
+        LaplaceDistribution dist;
+
+        dist = new LaplaceDistribution(0.5, 1.0);
+        Assertions.assertEquals(0.5, dist.getMean());
+        Assertions.assertEquals(2.0 * 1.0 * 1.0, dist.getVariance());
+
+        dist = new LaplaceDistribution(-0.3, 2.5);
+        Assertions.assertEquals(-0.3, dist.getMean());
+        Assertions.assertEquals(2.0 * 2.5 * 2.5, dist.getVariance());
+    }
 }