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 c32aa226e55812280afb1fc82b3e996dd458220d
Author: Alex Herbert <aherb...@apache.org>
AuthorDate: Sat Nov 19 08:43:40 2022 +0000
Use parameterized tests
---
.../statistics/distribution/FDistributionTest.java | 196 ++++++++++++---------
.../distribution/GammaDistributionTest.java | 25 +--
.../distribution/GeometricDistributionTest.java | 32 ++--
.../HypergeometricDistributionTest.java | 40 +++--
.../distribution/ParetoDistributionTest.java | 26 ++-
.../distribution/PascalDistributionTest.java | 28 +--
.../statistics/distribution/TDistributionTest.java | 35 ++--
.../distribution/TrapezoidalDistributionTest.java | 6 +-
.../distribution/TriangularDistributionTest.java | 36 ++--
.../TruncatedNormalDistributionTest.java | 4 +-
.../UniformContinuousDistributionTest.java | 30 ++--
.../UniformDiscreteDistributionTest.java | 25 +--
.../distribution/WeibullDistributionTest.java | 55 +++---
13 files changed, 293 insertions(+), 245 deletions(-)
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/FDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/FDistributionTest.java
index a0371e9..43fcb13 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/FDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/FDistributionTest.java
@@ -16,8 +16,12 @@
*/
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link FDistribution}.
@@ -53,21 +57,22 @@ class FDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testAdditionalMoments() {
- FDistribution dist;
-
- dist = FDistribution.of(1, 2);
- Assertions.assertEquals(Double.NaN, dist.getMean());
- Assertions.assertEquals(Double.NaN, dist.getVariance());
-
- dist = FDistribution.of(1, 3);
- Assertions.assertEquals(3d / (3d - 2d), dist.getMean());
- Assertions.assertEquals(Double.NaN, dist.getVariance());
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double numeratorDegreesOfFreedom,
+ double denominatorDegreesOfFreedom,
+ double mean,
+ double variance) {
+ final FDistribution dist = FDistribution.of(numeratorDegreesOfFreedom,
denominatorDegreesOfFreedom);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
- dist = FDistribution.of(1, 5);
- Assertions.assertEquals(5d / (5d - 2d), dist.getMean());
- Assertions.assertEquals((2d * 5d * 5d * 4d) / 9d, dist.getVariance());
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(1, 2, Double.NaN, Double.NaN),
+ Arguments.of(1, 3, 3.0 / (3 - 2), Double.NaN),
+ Arguments.of(1, 5, 5.0 / (5 - 2), (2 * 5 * 5 * 4) / 9.0)
+ );
}
@Test
@@ -102,82 +107,105 @@ class FDistributionTest extends
BaseContinuousDistributionTest {
Assertions.assertTrue(result < 1.0, "Failing to calculate inverse
cumulative probability");
}
- @Test
- void testAdditionalLogDensity() {
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalLogDensity(double numeratorDegreesOfFreedom,
+ double denominatorDegreesOfFreedom,
+ double[] points,
+ double[] values) {
+ testLogDensity(FDistribution.of(numeratorDegreesOfFreedom,
denominatorDegreesOfFreedom),
+ points, values, DoubleTolerances.relative(1e-15));
+ }
+
+ static Stream<Arguments> testAdditionalLogDensity() {
// Computed using Boost multiprecision to 100 digits (output 25
digits).
// Edge cases when the standard density is sub-normal or zero.
final double[] x = new double[] {1e1, 1e2, 1e3, 1e4, 1e5, 1e6, 1e7,
1e8, 1e9};
- testLogDensity(FDistribution.of(100, 100), x,
- new double[] {-56.96014024624318913110565,
- -165.8559950938238412964495,
- -282.3927517845117162132265,
- -399.7346409939330236149964,
- -517.157481231596055999464,
- -634.5884209792423525846316,
- -752.0201707219881824362492,
- -869.4520014646850073211334,
- -986.883840307381342156051},
- DoubleTolerances.relative(1e-15));
-
- testLogDensity(FDistribution.of(952, 912), x,
- new double[] {-509.5128641158461391223255,
- -1485.417858108384337659572,
- -2529.705750311339816652123,
- -3581.184004620825529681231,
- -4633.385040722443349533971,
- -5685.658392700035382988623,
- -6737.938976642435125691553,
- -7790.220283785087985050541,
- -8842.501663247803879775318},
- DoubleTolerances.relative(1e-15));
-
- // This causes intermediate overflow of the density function
- testLogDensity(FDistribution.of(1e-100, 1),
- new double[] {1e-200, 1e-250, 1e-300},
- new double[] {229.5653621188446231302736,
- 344.6946167685469072592738,
- 459.8238714182491914891139},
- DoubleTolerances.relative(1e-15));
+ return Stream.of(
+ Arguments.of(100, 100, x,
+ new double[] {
+ -56.96014024624318913110565,
+ -165.8559950938238412964495,
+ -282.3927517845117162132265,
+ -399.7346409939330236149964,
+ -517.157481231596055999464,
+ -634.5884209792423525846316,
+ -752.0201707219881824362492,
+ -869.4520014646850073211334,
+ -986.883840307381342156051}),
+ Arguments.of(952, 912, x,
+ new double[] {
+ -509.5128641158461391223255,
+ -1485.417858108384337659572,
+ -2529.705750311339816652123,
+ -3581.184004620825529681231,
+ -4633.385040722443349533971,
+ -5685.658392700035382988623,
+ -6737.938976642435125691553,
+ -7790.220283785087985050541,
+ -8842.501663247803879775318}),
+ // This causes intermediate overflow of the density function
+ Arguments.of(1e-100, 1,
+ new double[] {1e-200, 1e-250, 1e-300},
+ new double[] {
+ 229.5653621188446231302736,
+ 344.6946167685469072592738,
+ 459.8238714182491914891139})
+ );
}
- @Test
- void testAdditionalDensity() {
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalDensity(double numeratorDegreesOfFreedom,
+ double denominatorDegreesOfFreedom,
+ double[] points,
+ double[] values,
+ double relativeError) {
+ testDensity(FDistribution.of(numeratorDegreesOfFreedom,
denominatorDegreesOfFreedom),
+ points, values, DoubleTolerances.relative(relativeError));
+ }
+
+ static Stream<Arguments> testAdditionalDensity() {
+ // Computed using Boost multiprecision to 100 digits (output 25
digits).
+
// Edge cases when the standard density is sub-normal.
- testDensity(FDistribution.of(100, 100),
- new double[] {1e1, 1e2, 1e3, 1e4, 1e5, 1e6, 3e6, 4e6,
4.5e6, 5e6, 1e7},
- new double[] {1.830313161302986740491046e-25,
- 9.325165326363852979476269e-73,
- 2.282370632180103030176872e-123,
- 2.49718772086196154389661e-174,
- 2.51976260334572601372639e-225,
- 2.522031398014840106819471e-276,
- 1.171103964711921105069224e-300,
- 4.97420298008526384736197e-307,
- 1.224464123468993962344698e-309,
- 5.679564178845752345371413e-312,
- 0},
- DoubleTolerances.relative(3e-13));
-
- testDensity(FDistribution.of(952, 912),
- new double[] {10, 11, 12, 13, 14, 15, 16, 17, 18},
- new double[] {5.264712450643104177155291e-222,
- 1.083049754753448067375765e-237,
- 2.996024821196787172008532e-252,
- 7.919262482129153149257417e-266,
- 1.511696585130734458293958e-278,
- 1.652611434344889324846565e-290,
- 8.522337060963566999523664e-302,
- 1.760000675560273604454495e-312,
- 1.266172656954210816606837e-322},
- DoubleTolerances.relative(2e-13));
-
- // This causes intermediate overflow of the density function
- testDensity(FDistribution.of(1e-100, 1),
- new double[] {1e-200, 1e-250, 1e-300},
- new double[] {5.000000000000000189458187e+99,
- 4.999999999999999829961813e+149,
- 4.99999999999999997466404e+199},
- DoubleTolerances.relative(5e-14));
+ return Stream.of(
+ Arguments.of(100, 100,
+ new double[] {1e1, 1e2, 1e3, 1e4, 1e5, 1e6, 3e6, 4e6, 4.5e6,
5e6, 1e7},
+ new double[] {
+ 1.830313161302986740491046e-25,
+ 9.325165326363852979476269e-73,
+ 2.282370632180103030176872e-123,
+ 2.49718772086196154389661e-174,
+ 2.51976260334572601372639e-225,
+ 2.522031398014840106819471e-276,
+ 1.171103964711921105069224e-300,
+ 4.97420298008526384736197e-307,
+ 1.224464123468993962344698e-309,
+ 5.679564178845752345371413e-312,
+ 0
+ }, 3e-13),
+ Arguments.of(952, 912,
+ new double[] {10, 11, 12, 13, 14, 15, 16, 17, 18},
+ new double[] {5.264712450643104177155291e-222,
+ 1.083049754753448067375765e-237,
+ 2.996024821196787172008532e-252,
+ 7.919262482129153149257417e-266,
+ 1.511696585130734458293958e-278,
+ 1.652611434344889324846565e-290,
+ 8.522337060963566999523664e-302,
+ 1.760000675560273604454495e-312,
+ 1.266172656954210816606837e-322
+ }, 2e-13),
+ // This causes intermediate overflow of the density function
+ Arguments.of(1e-100, 1,
+ new double[] {1e-200, 1e-250, 1e-300},
+ new double[] {
+ 5.000000000000000189458187e+99,
+ 4.999999999999999829961813e+149,
+ 4.99999999999999997466404e+199
+ }, 5e-14)
+ );
}
}
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GammaDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GammaDistributionTest.java
index 6b56fec..7c5ae4b 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GammaDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GammaDistributionTest.java
@@ -21,10 +21,14 @@ import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
+import java.util.stream.Stream;
import org.apache.commons.math3.stat.descriptive.SummaryStatistics;
import org.apache.commons.numbers.gamma.LanczosApproximation;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link GammaDistribution}.
@@ -62,17 +66,18 @@ class GammaDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testAdditionalMoments() {
- GammaDistribution dist;
-
- dist = GammaDistribution.of(1, 2);
- Assertions.assertEquals(2, dist.getMean());
- Assertions.assertEquals(4, dist.getVariance());
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double shape, double scale, double mean, double
variance) {
+ final GammaDistribution dist = GammaDistribution.of(shape, scale);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
- dist = GammaDistribution.of(1.1, 4.2);
- Assertions.assertEquals(1.1 * 4.2, dist.getMean());
- Assertions.assertEquals(1.1 * 4.2 * 4.2, dist.getVariance());
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(1, 2, 2, 4),
+ Arguments.of(1.1, 4.2, 1.1 * 4.2, 1.1 * 4.2 * 4.2)
+ );
}
@Test
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GeometricDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GeometricDistributionTest.java
index 7931147..1c47922 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GeometricDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/GeometricDistributionTest.java
@@ -17,9 +17,12 @@
package org.apache.commons.statistics.distribution;
import java.util.Arrays;
+import java.util.stream.Stream;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
import org.junit.jupiter.params.provider.ValueSource;
/**
@@ -49,6 +52,20 @@ class GeometricDistributionTest extends
BaseDiscreteDistributionTest {
//-------------------- Additional test cases
-------------------------------
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double p, double mean, double variance) {
+ final GeometricDistribution dist = GeometricDistribution.of(p);
+ testMoments(dist, mean, variance, DoubleTolerances.ulps(1));
+ }
+
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(0.5, (1.0 - 0.5) / 0.5, (1.0 - 0.5) / (0.5 * 0.5)),
+ Arguments.of(0.3, (1.0 - 0.3) / 0.3, (1.0 - 0.3) / (0.3 * 0.3))
+ );
+ }
+
/**
* Test the PMF is computed using the power function when p is above 0.5.
* <p>Note: The geometric distribution PMF is defined as:
@@ -129,21 +146,6 @@ class GeometricDistributionTest extends
BaseDiscreteDistributionTest {
testSurvivalProbabilityInverseMapping(dist, x);
}
- @Test
- void testAdditionalMoments() {
- GeometricDistribution dist;
-
- final DoubleTolerance tol = DoubleTolerances.ulps(1);
-
- dist = GeometricDistribution.of(0.5);
- TestUtils.assertEquals((1.0d - 0.5d) / 0.5d, dist.getMean(), tol);
- TestUtils.assertEquals((1.0d - 0.5d) / (0.5d * 0.5d),
dist.getVariance(), tol);
-
- dist = GeometricDistribution.of(0.3);
- TestUtils.assertEquals((1.0d - 0.3d) / 0.3d, dist.getMean(), tol);
- TestUtils.assertEquals((1.0d - 0.3d) / (0.3d * 0.3d),
dist.getVariance(), tol);
- }
-
/**
* Test the most extreme parameters. Uses a small enough value of p that
the distribution is
* truncated by the maximum integer value. This creates a case where (x+1)
will overflow.
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
index d4ab2d1..34ecdb6 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/HypergeometricDistributionTest.java
@@ -17,10 +17,14 @@
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.apache.commons.numbers.core.Precision;
import org.apache.commons.rng.simple.RandomSource;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link HypergeometricDistribution}.
@@ -54,23 +58,21 @@ class HypergeometricDistributionTest extends
BaseDiscreteDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testAdditionalMoments() {
- HypergeometricDistribution dist;
-
- final DoubleTolerance tol = DoubleTolerances.ulps(1);
-
- dist = HypergeometricDistribution.of(1500, 40, 100);
- TestUtils.assertEquals(40d * 100d / 1500d,
- dist.getMean(), tol);
- TestUtils.assertEquals((100d * 40d * (1500d - 100d) * (1500d - 40d)) /
((1500d * 1500d * 1499d)),
- dist.getVariance(), tol);
-
- dist = HypergeometricDistribution.of(3000, 55, 200);
- TestUtils.assertEquals(55d * 200d / 3000d,
- dist.getMean(), tol);
- TestUtils.assertEquals((200d * 55d * (3000d - 200d) * (3000d - 55d)) /
((3000d * 3000d * 2999d)),
- dist.getVariance(), tol);
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(int populationSize,
+ int numberOfSuccesses,
+ int sampleSize,
+ double mean, double variance) {
+ final HypergeometricDistribution dist =
HypergeometricDistribution.of(populationSize, numberOfSuccesses, sampleSize);
+ testMoments(dist, mean, variance, DoubleTolerances.ulps(1));
+ }
+
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(1500, 40, 100, 40d * 100d / 1500d, (100d * 40d *
(1500d - 100d) * (1500d - 40d)) / ((1500d * 1500d * 1499d))),
+ Arguments.of(3000, 55, 200, 55d * 200d / 3000d, (200d * 55d *
(3000d - 200d) * (3000d - 55d)) / ((3000d * 3000d * 2999d)))
+ );
}
@Test
@@ -107,8 +109,8 @@ class HypergeometricDistributionTest extends
BaseDiscreteDistributionTest {
}
private static void testHypergeometricDistributionProbabilities(int
populationSize, int sampleSize,
- int numberOfSucceses, double[][] data) {
- final HypergeometricDistribution dist =
HypergeometricDistribution.of(populationSize, numberOfSucceses, sampleSize);
+ int numberOfSuccesses, double[][] data) {
+ final HypergeometricDistribution dist =
HypergeometricDistribution.of(populationSize, numberOfSuccesses, sampleSize);
for (int i = 0; i < data.length; ++i) {
final int x = (int)data[i][0];
final double pmf = data[i][1];
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
index d3539ab..38450cf 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ParetoDistributionTest.java
@@ -19,6 +19,8 @@ package org.apache.commons.statistics.distribution;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.CsvSource;
/**
* Test cases for {@link ParetoDistribution}.
@@ -56,6 +58,16 @@ class ParetoDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
+ @ParameterizedTest
+ @CsvSource({
+ "1, 1, Infinity, Infinity",
+ "2.2, 2.4, 3.771428571428, 14.816326530",
+ })
+ void testAdditionalMoments(double scale, double shape, double mean, double
variance) {
+ final ParetoDistribution dist = ParetoDistribution.of(scale, shape);
+ testMoments(dist, mean, variance, DoubleTolerances.relative(1e-9));
+ }
+
@Test
void testHighPrecision() {
final ParetoDistribution dist = ParetoDistribution.of(2.1, 1.4);
@@ -91,20 +103,6 @@ class ParetoDistributionTest extends
BaseContinuousDistributionTest {
testCumulativeProbabilityHighPrecision(dist2, x, values2,
DoubleTolerances.absolute(8e-17));
}
- @Test
- void testAdditionalMoments() {
- final double tol = 1e-9;
- ParetoDistribution dist;
-
- dist = ParetoDistribution.of(1, 1);
- Assertions.assertEquals(Double.POSITIVE_INFINITY, dist.getMean(), tol);
- Assertions.assertEquals(Double.POSITIVE_INFINITY, dist.getVariance(),
tol);
-
- dist = ParetoDistribution.of(2.2, 2.4);
- Assertions.assertEquals(3.771428571428, dist.getMean(), tol);
- Assertions.assertEquals(14.816326530, dist.getVariance(), tol);
- }
-
/**
* Check to make sure top-coding of extreme values works correctly.
*/
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PascalDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PascalDistributionTest.java
index b428f29..e2847e4 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PascalDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/PascalDistributionTest.java
@@ -16,7 +16,10 @@
*/
package org.apache.commons.statistics.distribution;
-import org.junit.jupiter.api.Test;
+import java.util.stream.Stream;
+import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link PascalDistribution}.
@@ -49,18 +52,17 @@ class PascalDistributionTest extends
BaseDiscreteDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testAdditionalMoments() {
- PascalDistribution dist;
-
- DoubleTolerance tol = DoubleTolerances.ulps(1);
-
- dist = PascalDistribution.of(10, 0.5);
- TestUtils.assertEquals((10d * 0.5d) / 0.5, dist.getMean(), tol);
- TestUtils.assertEquals((10d * 0.5d) / (0.5d * 0.5d),
dist.getVariance(), tol);
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(int r, double p, double mean, double variance) {
+ final PascalDistribution dist = PascalDistribution.of(r, p);
+ testMoments(dist, mean, variance, DoubleTolerances.ulps(1));
+ }
- dist = PascalDistribution.of(25, 0.7);
- TestUtils.assertEquals((25d * 0.3d) / 0.7, dist.getMean(), tol);
- TestUtils.assertEquals((25d * 0.3d) / (0.7d * 0.7d),
dist.getVariance(), tol);
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(10, 0.5, (10d * 0.5d) / 0.5, (10d * 0.5d) / (0.5d *
0.5d)),
+ Arguments.of(25, 0.7, (25d * 0.3d) / 0.7, (25d * 0.3d) / (0.7d *
0.7d))
+ );
}
}
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TDistributionTest.java
index c862342..c67bc49 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TDistributionTest.java
@@ -16,10 +16,13 @@
*/
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link TDistribution}.
@@ -52,6 +55,21 @@ class TDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double df, double mean, double variance) {
+ final TDistribution dist = TDistribution.of(df);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
+
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(1.5, 0, Double.POSITIVE_INFINITY),
+ Arguments.of(2.1, 0, 2.1 / (2.1 - 2.0)),
+ Arguments.of(12.1, 0, 12.1 / (12.1 - 2.0))
+ );
+ }
+
/**
* @see <a
href="https://issues.apache.orgg/bugzilla/show_bug.cgi?id=27243";>
* Bug report that prompted this unit test.</a>
@@ -65,23 +83,6 @@ class TDistributionTest extends
BaseContinuousDistributionTest {
});
}
- @Test
- void testAdditionalMoments() {
- TDistribution dist;
-
- dist = TDistribution.of(1.5);
- Assertions.assertEquals(0, dist.getMean());
- Assertions.assertEquals(Double.POSITIVE_INFINITY, dist.getVariance());
-
- dist = TDistribution.of(2.1);
- Assertions.assertEquals(0, dist.getMean());
- Assertions.assertEquals(2.1 / (2.1 - 2.0), dist.getVariance());
-
- dist = TDistribution.of(12.1);
- Assertions.assertEquals(0, dist.getMean());
- Assertions.assertEquals(12.1 / (12.1 - 2.0), dist.getVariance());
- }
-
/*
* Adding this test to benchmark against tables published by NIST
* http://itl.nist.gov/div898/handbook/eda/section3/eda3672.htm
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TrapezoidalDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TrapezoidalDistributionTest.java
index 5578cf4..2670124 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TrapezoidalDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TrapezoidalDistributionTest.java
@@ -75,11 +75,9 @@ class TrapezoidalDistributionTest extends
BaseContinuousDistributionTest {
@ParameterizedTest
@MethodSource
- void testAdditionalMoments(double a, double b, double c, double d, double
mean, double var) {
+ void testAdditionalMoments(double a, double b, double c, double d, double
mean, double variance) {
final TrapezoidalDistribution dist = TrapezoidalDistribution.of(a, b,
c, d);
- final DoubleTolerance tol = DoubleTolerances.ulps(8);
- TestUtils.assertEquals(mean, dist.getMean(), tol);
- TestUtils.assertEquals(var, dist.getVariance(), tol);
+ testMoments(dist, mean, variance, DoubleTolerances.ulps(8));
}
static Stream<Arguments> testAdditionalMoments() {
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TriangularDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TriangularDistributionTest.java
index 8dd4b44..80d2393 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TriangularDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TriangularDistributionTest.java
@@ -17,10 +17,12 @@
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.junit.jupiter.api.Assertions;
-import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link TriangularDistribution}.
@@ -58,6 +60,21 @@ class TriangularDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double a, double b, double c, double mean,
double variance) {
+ final TriangularDistribution dist = TriangularDistribution.of(a, b, c);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
+
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(0, 0.5, 1.0, 0.5, 1 / 24.0),
+ Arguments.of(0, 1, 1, 2 / 3.0, 1 / 18.0),
+ Arguments.of(-3, 2, 12, 3 + (2 / 3.0), 175 / 18.0)
+ );
+ }
+
@ParameterizedTest
@CsvSource({
"1, 2, 3",
@@ -69,21 +86,4 @@ class TriangularDistributionTest extends
BaseContinuousDistributionTest {
Assertions.assertEquals(mode, dist.getMode());
Assertions.assertEquals(upper, dist.getSupportUpperBound());
}
-
- @Test
- void testAdditionalMoments() {
- TriangularDistribution dist;
-
- dist = TriangularDistribution.of(0, 0.5, 1.0);
- Assertions.assertEquals(0.5, dist.getMean());
- Assertions.assertEquals(1 / 24.0, dist.getVariance());
-
- dist = TriangularDistribution.of(0, 1, 1);
- Assertions.assertEquals(2 / 3.0, dist.getMean());
- Assertions.assertEquals(1 / 18.0, dist.getVariance());
-
- dist = TriangularDistribution.of(-3, 2, 12);
- Assertions.assertEquals(3 + (2 / 3.0), dist.getMean());
- Assertions.assertEquals(175 / 18.0, dist.getVariance());
- }
}
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.java
index 2d8290e..0dbf539 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/TruncatedNormalDistributionTest.java
@@ -57,6 +57,8 @@ class TruncatedNormalDistributionTest extends
BaseContinuousDistributionTest {
return new String[] {null, null, "SupportLowerBound",
"SupportUpperBound"};
}
+ //-------------------- Additional test cases
-------------------------------
+
/**
* Hit the edge cases where the lower and upper bound are not infinite but
the
* CDF of the parent distribution is either 0 or 1. This is effectively no
truncation.
@@ -73,7 +75,7 @@ class TruncatedNormalDistributionTest extends
BaseContinuousDistributionTest {
"1.0, 2.0, -4, 6",
"3.45, 6.78, -8, 10",
})
- void testEffectivelyNoTruncation(double mean, double sd, double lower,
double upper) {
+ void testMomentsEffectivelyNoTruncation(double mean, double sd, double
lower, double upper) {
double inf = Double.POSITIVE_INFINITY;
double max = Double.MAX_VALUE;
TruncatedNormalDistribution dist1;
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.java
index c56fde0..287d283 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformContinuousDistributionTest.java
@@ -17,6 +17,7 @@
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.apache.commons.rng.UniformRandomProvider;
import org.apache.commons.rng.sampling.distribution.ContinuousSampler;
import org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler;
@@ -24,7 +25,9 @@ import org.apache.commons.rng.simple.RandomSource;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link UniformContinuousDistribution}.
@@ -62,22 +65,19 @@ class UniformContinuousDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testAdditionalMoments() {
- UniformContinuousDistribution dist;
-
- dist = UniformContinuousDistribution.of(0, 1);
- Assertions.assertEquals(0.5, dist.getMean());
- Assertions.assertEquals(1 / 12.0, dist.getVariance());
-
- dist = UniformContinuousDistribution.of(-1.5, 0.6);
- Assertions.assertEquals(-0.45, dist.getMean());
- Assertions.assertEquals(0.3675, dist.getVariance());
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double lower, double upper, double mean, double
variance) {
+ final UniformContinuousDistribution dist =
UniformContinuousDistribution.of(lower, upper);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
- // Overflow of 0.5 * (lower + upper)
- dist = UniformContinuousDistribution.of(Double.MAX_VALUE / 2,
Double.MAX_VALUE);
- Assertions.assertEquals(Double.MAX_VALUE - Double.MAX_VALUE / 4,
dist.getMean());
- Assertions.assertEquals(Double.POSITIVE_INFINITY, dist.getVariance());
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(0, 1, 0.5, 1 / 12.0),
+ Arguments.of(-1.5, 0.6, -0.45, 0.3675),
+ Arguments.of(Double.MAX_VALUE / 2, Double.MAX_VALUE,
Double.MAX_VALUE - Double.MAX_VALUE / 4, Double.POSITIVE_INFINITY)
+ );
}
/**
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformDiscreteDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformDiscreteDistributionTest.java
index c8f6912..33d5ecb 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformDiscreteDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/UniformDiscreteDistributionTest.java
@@ -17,11 +17,14 @@
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.apache.commons.math3.util.MathArrays;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link UniformDiscreteDistribution}.
@@ -52,18 +55,18 @@ class UniformDiscreteDistributionTest extends
BaseDiscreteDistributionTest {
//-------------------- Additional test cases
-------------------------------
- /** Test mean/variance. */
- @Test
- void testAdditionalMoments() {
- UniformDiscreteDistribution dist;
-
- dist = UniformDiscreteDistribution.of(0, 5);
- Assertions.assertEquals(2.5, dist.getMean());
- Assertions.assertEquals(35 / 12.0, dist.getVariance());
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(int lower, int upper, double mean, double
variance) {
+ final UniformDiscreteDistribution dist =
UniformDiscreteDistribution.of(lower, upper);
+ testMoments(dist, mean, variance, DoubleTolerances.equals());
+ }
- dist = UniformDiscreteDistribution.of(0, 1);
- Assertions.assertEquals(0.5, dist.getMean());
- Assertions.assertEquals(3 / 12.0, dist.getVariance());
+ static Stream<Arguments> testAdditionalMoments() {
+ return Stream.of(
+ Arguments.of(0, 5, 2.5, 35 / 12.0),
+ Arguments.of(0, 1, 0.5, 3 / 12.0)
+ );
}
// MATH-1396
diff --git
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/WeibullDistributionTest.java
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/WeibullDistributionTest.java
index 1c10306..cb5ee80 100644
---
a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/WeibullDistributionTest.java
+++
b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/WeibullDistributionTest.java
@@ -17,11 +17,14 @@
package org.apache.commons.statistics.distribution;
+import java.util.stream.Stream;
import org.apache.commons.numbers.gamma.LogGamma;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
+import org.junit.jupiter.params.provider.Arguments;
import org.junit.jupiter.params.provider.CsvSource;
+import org.junit.jupiter.params.provider.MethodSource;
/**
* Test cases for {@link WeibullDistribution}.
@@ -53,14 +56,27 @@ class WeibullDistributionTest extends
BaseContinuousDistributionTest {
//-------------------- Additional test cases
-------------------------------
- @Test
- void testInverseCumulativeProbabilitySmallPAccuracy() {
- final WeibullDistribution dist = WeibullDistribution.of(2, 3);
- final double t = dist.inverseCumulativeProbability(1e-17);
- // Analytically, answer is solution to 1e-17 = 1-exp(-(x/3)^2)
- // x = sqrt(-9*log(1-1e-17))
- // If we're not careful, answer will be 0. Answer below is computed
with care in Octave:
- Assertions.assertEquals(9.48683298050514e-9, t, 1e-17);
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalMoments(double shape, double scale, double mean, double
variance) {
+ final WeibullDistribution dist = WeibullDistribution.of(shape, scale);
+ testMoments(dist, mean, variance, DoubleTolerances.absolute(1e-9));
+ }
+
+ static Stream<Arguments> testAdditionalMoments() {
+ // In R: 3.5*gamma(1+(1/2.5)) (or empirically: mean(rweibull(10000,
2.5, 3.5)))
+ double mu1 = 3.5 * Math.exp(LogGamma.value(1 + (1 / 2.5)));
+ double mu2 = 2.222 * Math.exp(LogGamma.value(1 + (1 / 10.4)));
+ return Stream.of(
+ Arguments.of(2.5, 3.5, mu1,
+ (3.5 * 3.5) *
+ Math.exp(LogGamma.value(1 + (2 / 2.5))) -
+ (mu1 * mu1)),
+ Arguments.of(10.4, 2.222, mu2,
+ (2.222 * 2.222) *
+ Math.exp(LogGamma.value(1 + (2 / 10.4))) -
+ (mu2 * mu2))
+ );
}
@ParameterizedTest
@@ -75,21 +91,12 @@ class WeibullDistributionTest extends
BaseContinuousDistributionTest {
}
@Test
- void testAdditionalMoments() {
- final double tol = 1e-9;
- WeibullDistribution dist;
-
- dist = WeibullDistribution.of(2.5, 3.5);
- // In R: 3.5*gamma(1+(1/2.5)) (or empirically: mean(rweibull(10000,
2.5, 3.5)))
- Assertions.assertEquals(3.5 * Math.exp(LogGamma.value(1 + (1 / 2.5))),
dist.getMean(), tol);
- Assertions.assertEquals((3.5 * 3.5) *
- Math.exp(LogGamma.value(1 + (2 / 2.5))) -
- (dist.getMean() * dist.getMean()), dist.getVariance(), tol);
-
- dist = WeibullDistribution.of(10.4, 2.222);
- Assertions.assertEquals(2.222 * Math.exp(LogGamma.value(1 + (1 /
10.4))), dist.getMean(), tol);
- Assertions.assertEquals((2.222 * 2.222) *
- Math.exp(LogGamma.value(1 + (2 / 10.4))) -
- (dist.getMean() * dist.getMean()), dist.getVariance(), tol);
+ void testInverseCumulativeProbabilitySmallPAccuracy() {
+ final WeibullDistribution dist = WeibullDistribution.of(2, 3);
+ final double t = dist.inverseCumulativeProbability(1e-17);
+ // Analytically, answer is solution to 1e-17 = 1-exp(-(x/3)^2)
+ // x = sqrt(-9*log(1-1e-17))
+ // If we're not careful, answer will be 0. Answer below is computed
with care in Octave:
+ Assertions.assertEquals(9.48683298050514e-9, t, 1e-17);
}
}
