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Posted to commits@commons.apache.org by er...@apache.org on 2021/08/02 00:39:01 UTC
[commons-math] 02/03: Adapt to "Commons Statistics" API change.
This is an automated email from the ASF dual-hosted git repository.
erans pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/commons-math.git
commit 8e63d421bff30f6ab69d731f93b9ca8fc3fb95ba
Author: Gilles Sadowski <gi...@gmail.com>
AuthorDate: Mon Aug 2 01:17:48 2021 +0200
Adapt to "Commons Statistics" API change.
---
.../math4/legacy/distribution/AbstractRealDistribution.java | 11 -----------
.../math4/legacy/distribution/EmpiricalDistribution.java | 9 ---------
.../math4/legacy/distribution/EnumeratedRealDistribution.java | 10 +---------
.../legacy/distribution/AbstractRealDistributionTest.java | 10 ----------
.../legacy/distribution/EnumeratedRealDistributionTest.java | 4 ++--
5 files changed, 3 insertions(+), 41 deletions(-)
diff --git a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistribution.java b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistribution.java
index afedfae..e422e17 100644
--- a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistribution.java
+++ b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistribution.java
@@ -204,17 +204,6 @@ public abstract class AbstractRealDistribution
/**
* {@inheritDoc}
- *
- * @return zero.
- * @since 3.1
- */
- @Override
- public double probability(double x) {
- return 0d;
- }
-
- /**
- * {@inheritDoc}
* <p>
* The default implementation simply computes the logarithm of {@code density(x)}.
*/
diff --git a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java
index 3fd8bbf..9e473e8 100644
--- a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java
+++ b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EmpiricalDistribution.java
@@ -305,15 +305,6 @@ public final class EmpiricalDistribution extends AbstractRealDistribution
/**
* {@inheritDoc}
- * @since 3.1
- */
- @Override
- public double probability(double x) {
- return 0;
- }
-
- /**
- * {@inheritDoc}
*
* Returns the kernel density normalized so that its integral over each bin
* equals the bin mass.
diff --git a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistribution.java b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistribution.java
index f907894..bae7540 100644
--- a/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistribution.java
+++ b/commons-math-legacy/src/main/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistribution.java
@@ -123,14 +123,6 @@ public class EnumeratedRealDistribution
}
/**
- * {@inheritDoc}
- */
- @Override
- public double probability(final double x) {
- return innerDistribution.probability(x);
- }
-
- /**
* For a random variable {@code X} whose values are distributed according to
* this distribution, this method returns {@code P(X = x)}. In other words,
* this method represents the probability mass function (PMF) for the
@@ -141,7 +133,7 @@ public class EnumeratedRealDistribution
*/
@Override
public double density(final double x) {
- return probability(x);
+ return innerDistribution.probability(x);
}
/**
diff --git a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistributionTest.java b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistributionTest.java
index a836f14..c750037 100644
--- a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistributionTest.java
+++ b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/AbstractRealDistributionTest.java
@@ -96,11 +96,6 @@ public class AbstractRealDistributionTest {
public boolean isSupportConnected() {
return false;
}
-
- @Override
- public double probability(final double x) {
- throw new UnsupportedOperationException();
- }
};
final double expected = x1;
final double actual = distribution.inverseCumulativeProbability(p12);
@@ -196,11 +191,6 @@ public class AbstractRealDistributionTest {
public boolean isSupportConnected() {
return false;
}
-
- @Override
- public double probability(final double x) {
- throw new UnsupportedOperationException();
- }
};
final double expected = x2;
final double actual = distribution.inverseCumulativeProbability(p23);
diff --git a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistributionTest.java b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistributionTest.java
index 96414d1..e7fc63c 100644
--- a/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistributionTest.java
+++ b/commons-math-legacy/src/test/java/org/apache/commons/math4/legacy/distribution/EnumeratedRealDistributionTest.java
@@ -99,7 +99,7 @@ public class EnumeratedRealDistributionTest {
double[] points = new double[]{-2.0, -1.0, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0};
double[] results = new double[]{0, 0.2, 0, 0, 0, 0.5, 0, 0, 0, 0.3, 0};
for (int p = 0; p < points.length; p++) {
- double density = testDistribution.probability(points[p]);
+ double density = testDistribution.density(points[p]);
Assert.assertEquals(results[p], density, 0.0);
}
}
@@ -248,7 +248,7 @@ public class EnumeratedRealDistributionTest {
public void testCreateFromDoubles() {
final double[] data = new double[] {0, 1, 1, 2, 2, 2};
EnumeratedRealDistribution distribution = new EnumeratedRealDistribution(data);
- assertEquals(0.5, distribution.probability(2), 0);
+ assertEquals(0.5, distribution.density(2), 0);
assertEquals(0.5, distribution.cumulativeProbability(1), 0);
}
}