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Posted to commits@commons.apache.org by ah...@apache.org on 2022/11/20 12:35:26 UTC
[commons-statistics] branch master updated (0de1692 -> c32aa22)
This is an automated email from the ASF dual-hosted git repository.
aherbert pushed a change to branch master
in repository https://gitbox.apache.org/repos/asf/commons-statistics.git
from 0de1692 STATISTICS-57: Add a trapezoidal distribution
new 962ddfc Use parameterized tests
new 280b177 Use assertEquals in place of using Precision with assertTrue
new e107d69 Use smaller test tolerance
new c32aa22 Use parameterized tests
The 4 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails. The revisions
listed as "add" were already present in the repository and have only
been added to this reference.
Summary of changes:
.../statistics/distribution/ArgumentUtilsTest.java | 50 +++---
.../distribution/BetaDistributionTest.java | 48 +++--
.../distribution/ChiSquaredDistributionTest.java | 63 ++++---
.../distribution/ExponentialDistributionTest.java | 27 +--
.../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 +++---
.../distribution/test.exponential.2.properties | 1 -
.../distribution/test.exponential.3.properties | 1 -
19 files changed, 393 insertions(+), 335 deletions(-)
[commons-statistics] 03/04: Use smaller test tolerance
Posted by ah...@apache.org.
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 e107d69a1dac8dfab7050d72ac6df00ce49c68f5
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Sat Nov 19 07:47:07 2022 +0000
Use smaller test tolerance
---
.../commons/statistics/distribution/ExponentialDistributionTest.java | 5 +++++
.../commons/statistics/distribution/test.exponential.2.properties | 1 -
.../commons/statistics/distribution/test.exponential.3.properties | 1 -
3 files changed, 5 insertions(+), 2 deletions(-)
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
index 6c8c4bf..50c3e1b 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
@@ -46,6 +46,11 @@ class ExponentialDistributionTest extends BaseContinuousDistributionTest {
return new String[] {"Mean"};
}
+ @Override
+ protected double getRelativeTolerance() {
+ return 5e-15;
+ }
+
//------------ Additional tests -------------------------------------------
@Test
diff --git a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.2.properties b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.2.properties
index 37ea897..a4cc936 100644
--- a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.2.properties
+++ b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.2.properties
@@ -18,7 +18,6 @@ parameters = 1.0
mean = 1.0
variance = 1.0
lower = 0
-tolerance.absolute = 1e-15
cdf.points = \
0.0000000000000000e+00, 1.0005003335835335e-03,\
1.0050335853501442e-02, 2.5317807984289876e-02,\
diff --git a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.3.properties b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.3.properties
index 504f6dd..51f870d 100644
--- a/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.3.properties
+++ b/commons-statistics-distribution/src/test/resources/org/apache/commons/statistics/distribution/test.exponential.3.properties
@@ -18,7 +18,6 @@ parameters = 1.5
mean = 1.5
variance = 2.25
lower = 0
-tolerance.absolute = 1e-14
cdf.points = \
0.0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.1, 0.25, 0.5, 0.75, \
1.0, 1.25, 1.5, 1.75, \
[commons-statistics] 04/04: Use parameterized tests
Posted by ah...@apache.org.
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 <ah...@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);
}
}
[commons-statistics] 01/04: Use parameterized tests
Posted by ah...@apache.org.
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 962ddfc467c0488948439528a21445422e6a4dc5
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Thu Nov 17 15:58:45 2022 +0000
Use parameterized tests
---
.../statistics/distribution/ArgumentUtilsTest.java | 50 ++++++++---------
.../distribution/BetaDistributionTest.java | 48 ++++++++---------
.../distribution/ChiSquaredDistributionTest.java | 63 ++++++++++++----------
3 files changed, 84 insertions(+), 77 deletions(-)
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ArgumentUtilsTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ArgumentUtilsTest.java
index 82c09f9..59a33f1 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ArgumentUtilsTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ArgumentUtilsTest.java
@@ -17,37 +17,37 @@
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.ValueSource;
/**
* Test for {@link ArgumentUtils}.
*/
class ArgumentUtilsTest {
- @Test
- void testIsFiniteStrictlyPositive() {
- final double[] good = {Double.MIN_VALUE, 1, 2, 3, Double.MAX_VALUE};
- final double[] bad = {0, -0.0, -Double.MIN_VALUE, -Double.MAX_VALUE,
- Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, Double.NaN};
- for (final double x : good) {
- Assertions.assertTrue(ArgumentUtils.isFiniteStrictlyPositive(x), () -> Double.toString(x));
- }
- for (final double x : bad) {
- Assertions.assertFalse(ArgumentUtils.isFiniteStrictlyPositive(x), () -> Double.toString(x));
- }
+ @ParameterizedTest
+ @ValueSource(doubles = {Double.MIN_VALUE, 1, 2, 3, Double.MAX_VALUE})
+ void testIsFiniteStrictlyPositiveTrue(double x) {
+ Assertions.assertTrue(ArgumentUtils.isFiniteStrictlyPositive(x), () -> Double.toString(x));
}
- @Test
- void testCheckProbability() {
- // Currently this allows -0.0
- final double[] good = {-0.0, 0.0, Double.MIN_VALUE, 1 - 0x1.0p-53, 1};
- final double[] bad = {-Double.MIN_VALUE, -0.1, -1, -2, Math.nextUp(1.0), 1.1, -Double.MAX_VALUE,
- Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, Double.NaN};
- for (final double p : good) {
- Assertions.assertDoesNotThrow(() -> ArgumentUtils.checkProbability(p), () -> Double.toString(p));
- }
- for (final double p : bad) {
- Assertions.assertThrows(IllegalArgumentException.class,
- () -> ArgumentUtils.checkProbability(p), () -> Double.toString(p));
- }
+ @ParameterizedTest
+ @ValueSource(doubles = {0, -0.0, -Double.MIN_VALUE, -Double.MAX_VALUE,
+ Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, Double.NaN})
+ void testIsFiniteStrictlyPositiveFalse(double x) {
+ Assertions.assertFalse(ArgumentUtils.isFiniteStrictlyPositive(x), () -> Double.toString(x));
+ }
+
+ @ParameterizedTest
+ @ValueSource(doubles = {-0.0, 0.0, Double.MIN_VALUE, 1 - 0x1.0p-53, 1})
+ void testCheckProbability(double p) {
+ Assertions.assertDoesNotThrow(() -> ArgumentUtils.checkProbability(p), () -> Double.toString(p));
+ }
+
+ @ParameterizedTest
+ @ValueSource(doubles = {-Double.MIN_VALUE, -0.1, -1, -2, 1.0 + 0x1.0p-52, 1.1, -Double.MAX_VALUE,
+ Double.POSITIVE_INFINITY, Double.NEGATIVE_INFINITY, Double.NaN})
+ void testCheckProbabilityThrows(double p) {
+ Assertions.assertThrows(IllegalArgumentException.class,
+ () -> ArgumentUtils.checkProbability(p), () -> Double.toString(p));
}
}
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BetaDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BetaDistributionTest.java
index 86984ac..30ec9fd 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BetaDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/BetaDistributionTest.java
@@ -73,31 +73,16 @@ class BetaDistributionTest extends BaseContinuousDistributionTest {
* Precision tests for verifying that CDF calculates accurately in cases
* where 1-cdf(x) is inaccurately 1.
*/
- @Test
- void testCumulativePrecision() {
- // Calculated using WolframAlpha
- checkCumulativePrecision(5.0, 5.0, 0.0001, 1.2595800539968654e-18);
- checkCumulativePrecision(4.0, 5.0, 0.00001, 6.999776002800025e-19);
- checkCumulativePrecision(5.0, 4.0, 0.0001, 5.598600119996539e-19);
- checkCumulativePrecision(6.0, 2.0, 0.001, 6.994000000000028e-18);
- checkCumulativePrecision(2.0, 6.0, 1e-9, 2.0999999930000014e-17);
- }
-
- /**
- * Precision tests for verifying that survival function calculates accurately in cases
- * where 1-sf(x) is inaccurately 1.
- */
- @Test
- void testSurvivalPrecision() {
+ @ParameterizedTest
+ @CsvSource({
// Calculated using WolframAlpha
- checkSurvivalPrecision(5.0, 5.0, 0.9999, 1.2595800539961496e-18);
- checkSurvivalPrecision(4.0, 5.0, 0.9999, 5.598600119993397e-19);
- checkSurvivalPrecision(5.0, 4.0, 0.99998, 1.1199283217964632e-17);
- checkSurvivalPrecision(6.0, 2.0, 0.999999999, 2.0999998742158932e-17);
- checkSurvivalPrecision(2.0, 6.0, 0.999, 6.994000000000077e-18);
- }
-
- private static void checkCumulativePrecision(double alpha, double beta, double value, double expected) {
+ "5.0, 5.0, 0.0001, 1.2595800539968654e-18",
+ "4.0, 5.0, 0.00001, 6.999776002800025e-19",
+ "5.0, 4.0, 0.0001, 5.598600119996539e-19",
+ "6.0, 2.0, 0.001, 6.994000000000028e-18",
+ "2.0, 6.0, 1e-9, 2.0999999930000014e-17",
+ })
+ void testCumulativePrecision(double alpha, double beta, double value, double expected) {
final double tolerance = 1e-22;
final BetaDistribution dist = BetaDistribution.of(alpha, beta);
Assertions.assertEquals(
@@ -107,7 +92,20 @@ class BetaDistributionTest extends BaseContinuousDistributionTest {
() -> "cumulative probability not precise at " + value + " for a=" + alpha + " & b=" + beta);
}
- private static void checkSurvivalPrecision(double alpha, double beta, double value, double expected) {
+ /**
+ * Precision tests for verifying that survival function calculates accurately in cases
+ * where 1-sf(x) is inaccurately 1.
+ */
+ @ParameterizedTest
+ @CsvSource({
+ // Calculated using WolframAlpha
+ "5.0, 5.0, 0.9999, 1.2595800539961496e-18",
+ "4.0, 5.0, 0.9999, 5.598600119993397e-19",
+ "5.0, 4.0, 0.99998, 1.1199283217964632e-17",
+ "6.0, 2.0, 0.999999999, 2.0999998742158932e-17",
+ "2.0, 6.0, 0.999, 6.994000000000077e-18",
+ })
+ void testSurvivalPrecision(double alpha, double beta, double value, double expected) {
final double tolerance = 1e-22;
final BetaDistribution dist = BetaDistribution.of(alpha, beta);
Assertions.assertEquals(
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ChiSquaredDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ChiSquaredDistributionTest.java
index 57daa18..6917a97 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ChiSquaredDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ChiSquaredDistributionTest.java
@@ -17,7 +17,10 @@
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 ChiSquaredDistribution}.
@@ -50,37 +53,43 @@ class ChiSquaredDistributionTest extends BaseContinuousDistributionTest {
//-------------------- Additional test cases -------------------------------
- @Test
- void testAdditionalDensity() {
+ @ParameterizedTest
+ @MethodSource
+ void testAdditionalDensity(double df, double[] points, double[] values) {
// Values have many digits above the decimal point so use relative tolerance
final DoubleTolerance tol = createRelTolerance(5e-14);
+ testDensity(ChiSquaredDistribution.of(df), points, values, tol);
+ }
- final double[] x = new double[]{-0.1, 1e-6, 0.5, 1, 2, 5};
+ static Stream<Arguments> testAdditionalDensity() {
// R 2.5:
// x <- c(-0.1, 1e-6, 0.5, 1, 2, 5)
- // print(dchisq(x, df=1), digits=17)
- testDensity(ChiSquaredDistribution.of(1), x, new double[] {
- 0.0, 398.942080930342626743, 0.439391289467722435, 0.241970724519143365,
- 0.103776874355148693, 0.014644982561926489}, tol);
- // print(dchisq(x, df=0.1), digits=17)
- testDensity(ChiSquaredDistribution.of(0.1), x, new double[]{
- 0, 2.4864539972849805e+04, 7.4642387316120481e-02,
- 3.0090777182393683e-02, 9.4472991589506262e-03, 8.8271993957607896e-04}, tol);
- // print(dchisq(x, df=2), digits=17)
- testDensity(ChiSquaredDistribution.of(2), x, new double[]{0,
- 0.49999975000006253, 0.38940039153570244,
- 0.30326532985631671, 0.18393972058572117, 0.04104249931194940}, tol);
- // print(dchisq(x, df=10), digits=17)
- testDensity(ChiSquaredDistribution.of(10), x, new double[]{0,
- 1.3020826822918329e-27, 6.3378969976514082e-05,
- 7.8975346316749191e-04, 7.6641550244050524e-03, 6.6800942890542614e-02}, tol);
- // print(dchisq(x, df=100), digits=17)
- testDensity(ChiSquaredDistribution.of(100), x, new double[]{0,
- 0.0000000000000000e+00, 2.0200026568141969e-93,
- 8.8562141121618944e-79, 3.0239224849774644e-64, 2.1290671364111626e-45}, tol);
+ final double[] x = new double[]{-0.1, 1e-6, 0.5, 1, 2, 5};
+ return Stream.of(
+ // print(dchisq(x, df=1), digits=17)
+ Arguments.of(1, x, new double[] {
+ 0, 398.942080930342626743, 0.439391289467722435, 0.241970724519143365,
+ 0.103776874355148693, 0.014644982561926489}),
+ // print(dchisq(x, df=0.1), digits=17)
+ Arguments.of(0.1, x, new double[] {
+ 0, 2.4864539972849805e+04, 7.4642387316120481e-02,
+ 3.0090777182393683e-02, 9.4472991589506262e-03, 8.8271993957607896e-04}),
+ // print(dchisq(x, df=2), digits=17)
+ Arguments.of(2, x, new double[] {
+ 0, 0.49999975000006253, 0.38940039153570244,
+ 0.30326532985631671, 0.18393972058572117, 0.04104249931194940}),
+ // print(dchisq(x, df=10), digits=17)
+ Arguments.of(10, x, new double[] {
+ 0, 1.3020826822918329e-27, 6.3378969976514082e-05,
+ 7.8975346316749191e-04, 7.6641550244050524e-03, 6.6800942890542614e-02}),
+ // print(dchisq(x, df=100), digits=17)
+ Arguments.of(100, x, new double[] {
+ 0, 0.0000000000000000e+00, 2.0200026568141969e-93,
+ 8.8562141121618944e-79, 3.0239224849774644e-64, 2.1290671364111626e-45})
- // TODO:
- // Add more density checks with large DF and x points around the mean
- // and into overflow for the underlying Gamma distribution.
+ // TODO:
+ // Add more density checks with large DF and x points around the mean
+ // and into overflow for the underlying Gamma distribution.
+ );
}
}
[commons-statistics] 02/04: Use assertEquals in place of using Precision with assertTrue
Posted by ah...@apache.org.
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 280b177006b4e304dca162350a647d495e4261f7
Author: Alex Herbert <ah...@apache.org>
AuthorDate: Sat Nov 19 07:45:29 2022 +0000
Use assertEquals in place of using Precision with assertTrue
---
.../distribution/ExponentialDistributionTest.java | 22 +++++++++++-----------
1 file changed, 11 insertions(+), 11 deletions(-)
diff --git a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
index c52b350..6c8c4bf 100644
--- a/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
+++ b/commons-statistics-distribution/src/test/java/org/apache/commons/statistics/distribution/ExponentialDistributionTest.java
@@ -17,7 +17,6 @@
package org.apache.commons.statistics.distribution;
import java.math.BigDecimal;
-import org.apache.commons.numbers.core.Precision;
import org.junit.jupiter.api.Assertions;
import org.junit.jupiter.api.Test;
import org.junit.jupiter.params.ParameterizedTest;
@@ -58,19 +57,20 @@ class ExponentialDistributionTest extends BaseContinuousDistributionTest {
@Test
void testAdditionalDensity() {
final ExponentialDistribution d1 = ExponentialDistribution.of(1);
- Assertions.assertTrue(Precision.equals(0.0, d1.density(-1e-9), 1));
- Assertions.assertTrue(Precision.equals(1.0, d1.density(0.0), 1));
- Assertions.assertTrue(Precision.equals(0.0, d1.density(1000.0), 1));
- Assertions.assertTrue(Precision.equals(Math.exp(-1), d1.density(1.0), 1));
- Assertions.assertTrue(Precision.equals(Math.exp(-2), d1.density(2.0), 1));
+ Assertions.assertEquals(0.0, d1.density(-1e-9));
+ Assertions.assertEquals(1.0, d1.density(0.0));
+ Assertions.assertEquals(0.0, d1.density(1000.0));
+ Assertions.assertEquals(Math.exp(-1), d1.density(1.0));
+ Assertions.assertEquals(Math.exp(-2), d1.density(2.0));
final ExponentialDistribution d2 = ExponentialDistribution.of(3);
- Assertions.assertTrue(Precision.equals(1 / 3.0, d2.density(0.0), 1));
- // computed using print(dexp(1, rate=1/3), digits=10) in R 2.5
- Assertions.assertEquals(0.2388437702, d2.density(1.0), 1e-8);
+ Assertions.assertEquals(1 / 3.0, d2.density(0.0));
- // computed using print(dexp(2, rate=1/3), digits=10) in R 2.5
- Assertions.assertEquals(0.1711390397, d2.density(2.0), 1e-8);
+ // computed using R 3.4.0: print(dexp(1, rate=1/3), digits=20)
+ Assertions.assertEquals(0.23884377019126309949, d2.density(1.0), 1e-15);
+
+ // computed using R 3.4.0: print(dexp(2, rate=1/3), digits=20)
+ Assertions.assertEquals(0.17113903967753066326, d2.density(2.0), 1e-15);
}
@Test