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-rng.git
commit 2b24bf79a3bb119cb0389771971b32e2a5a796e4
Author: aherbert <aherb...@apache.org>
AuthorDate: Thu Feb 14 12:26:03 2019 +0000
Formatted code and javadoc
---
.../distribution/GeometricSamplersPerformance.java | 5 ++--
.../sampling/distribution/GeometricSampler.java | 14 +++++----
.../distribution/GeometricSamplerTest.java | 33 ++++++++++++----------
3 files changed, 29 insertions(+), 23 deletions(-)
diff --git
a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/distribution/GeometricSamplersPerformance.java
b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/distribution/GeometricSamplersPerformance.java
index 60e86ad..bf3cdf9 100644
---
a/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/distribution/GeometricSamplersPerformance.java
+++
b/commons-rng-examples/examples-jmh/src/main/java/org/apache/commons/rng/examples/jmh/distribution/GeometricSamplersPerformance.java
@@ -134,8 +134,9 @@ public class GeometricSamplersPerformance {
// ---
// Note: if cumulativeProbability == 0 then log1p(-0) is zero and
the result
// after the range check is 0.
- // Note: if cumulativeProbability == 1 then log1p(-1) is negative
infinity, the result of
- // the divide is positive infinity and the result after the range
check is Integer.MAX_VALUE.
+ // Note: if cumulativeProbability == 1 then log1p(-1) is negative
infinity, the result
+ // of the divide is positive infinity and the result after the
range check is
+ // Integer.MAX_VALUE.
return Math.max(0, (int)
Math.ceil(Math.log1p(-cumulativeProbability) / log1mProbabilityOfSuccess - 1));
}
}
diff --git
a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
index ba62ac4..2197d4c 100644
---
a/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
+++
b/commons-rng-sampling/src/main/java/org/apache/commons/rng/sampling/distribution/GeometricSampler.java
@@ -78,7 +78,8 @@ public class GeometricSampler implements DiscreteSampler {
/**
* @param rng Generator of uniformly distributed random numbers
- * @param probabilityOfSuccess The probability of success (must be
{@code 0<p<1})
+ * @param probabilityOfSuccess The probability of success (must be in
the range
+ * {@code [0 < probabilityOfSuccess < 1]})
*/
GeometricExponentialSampler(UniformRandomProvider rng, double
probabilityOfSuccess) {
this.rng = rng;
@@ -116,13 +117,14 @@ public class GeometricSampler implements DiscreteSampler {
*
* @param rng Generator of uniformly distributed random numbers
* @param probabilityOfSuccess The probability of success
- * @throws IllegalArgumentException if {@code probabilityOfSuccess} is not
in the range [0 <
- * probabilityOfSuccess <= 1]
+ * @throws IllegalArgumentException if {@code probabilityOfSuccess} is not
in the range
+ * {@code [0 < probabilityOfSuccess <= 1]})
*/
public GeometricSampler(UniformRandomProvider rng, double
probabilityOfSuccess) {
if (probabilityOfSuccess <= 0 || probabilityOfSuccess > 1) {
throw new IllegalArgumentException(
- "Probability of success must be in the range [0 < p <= 1]: " +
probabilityOfSuccess);
+ "Probability of success (p) must be in the range [0 < p <= 1]:
"
+ + probabilityOfSuccess);
}
delegate = probabilityOfSuccess == 1 ?
GeometricP1Sampler.INSTANCE :
@@ -132,8 +134,8 @@ public class GeometricSampler implements DiscreteSampler {
/**
* Create a sample from a geometric distribution.
*
- * <p>The sample will take the values in the set {@code [0, 1, 2, ...]},
equivalent to the number of
- * failures before the first success.
+ * <p>The sample will take the values in the set {@code [0, 1, 2, ...]},
equivalent to the
+ * number of failures before the first success.
*/
@Override
public int sample() {
diff --git
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/GeometricSamplerTest.java
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/GeometricSamplerTest.java
index 00f1000..c3267bf 100644
---
a/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/GeometricSamplerTest.java
+++
b/commons-rng-sampling/src/test/java/org/apache/commons/rng/sampling/distribution/GeometricSamplerTest.java
@@ -17,6 +17,7 @@
package org.apache.commons.rng.sampling.distribution;
import org.apache.commons.rng.UniformRandomProvider;
+import org.apache.commons.rng.core.source64.SplitMix64;
import org.apache.commons.rng.simple.RandomSource;
import org.junit.Assert;
import org.junit.Test;
@@ -26,8 +27,8 @@ import org.junit.Test;
*/
public class GeometricSamplerTest {
/**
- * Test the edge case where the probability of success is 1. This is a
valid geometric distribution
- * where the sample should always be 0.
+ * Test the edge case where the probability of success is 1. This is a
valid geometric
+ * distribution where the sample should always be 0.
*/
@Test
public void testProbabilityOfSuccessIsOneGeneratesZeroForSamples() {
@@ -45,18 +46,20 @@ public class GeometricSamplerTest {
*/
@Test
public void testProbabilityOfSuccessIsOneSamplerToString() {
- final UniformRandomProvider rng =
RandomSource.create(RandomSource.SPLIT_MIX_64);
- final GeometricSampler sampler = new GeometricSampler(rng, 1);
- Assert.assertTrue("Missing 'Geometric' from toString",
sampler.toString().contains("Geometric"));
+ final UniformRandomProvider unusedRng = new SplitMix64(0L);
+ final GeometricSampler sampler = new GeometricSampler(unusedRng, 1);
+ Assert.assertTrue("Missing 'Geometric' from toString",
+ sampler.toString().contains("Geometric"));
}
/**
* Test the edge case where the probability of success is nearly 0. This
is a valid geometric
- * distribution but the sample is clipped to max integer value because the
underlying exponential
- * has a mean of positive infinity (effectively the sample is from a
truncated distribution).
+ * distribution but the sample is clipped to max integer value because the
underlying
+ * exponential has a mean of positive infinity (effectively the sample is
from a truncated
+ * distribution).
*
- * <p>This test can be changed in future if a lower bound limit for the
probability of success is
- * introduced.
+ * <p>This test can be changed in future if a lower bound limit for the
probability of success
+ * is introduced.
*/
@Test
public void
testProbabilityOfSuccessIsAlmostZeroGeneratesMaxValueForSamples() {
@@ -64,8 +67,8 @@ public class GeometricSamplerTest {
final GeometricSampler sampler = new GeometricSampler(rng,
Double.MIN_VALUE);
// All samples should be max value
for (int i = 0; i < 10; i++) {
- Assert.assertEquals("p=(almost 0) should have Integer.MAX_VALUE
for all samples", Integer.MAX_VALUE,
- sampler.sample());
+ Assert.assertEquals("p=(almost 0) should have Integer.MAX_VALUE
for all samples",
+ Integer.MAX_VALUE, sampler.sample());
}
}
@@ -75,8 +78,8 @@ public class GeometricSamplerTest {
@SuppressWarnings("unused")
@Test(expected = IllegalArgumentException.class)
public void testProbabilityOfSuccessAboveOneThrows() {
- final UniformRandomProvider rng =
RandomSource.create(RandomSource.SPLIT_MIX_64, Long.valueOf(0));
- new GeometricSampler(rng, Math.nextUp(1.0));
+ final UniformRandomProvider unusedRng = new SplitMix64(0L);
+ new GeometricSampler(unusedRng, Math.nextUp(1.0));
}
/**
@@ -85,7 +88,7 @@ public class GeometricSamplerTest {
@SuppressWarnings("unused")
@Test(expected = IllegalArgumentException.class)
public void testProbabilityOfSuccessIsZeroThrows() {
- final UniformRandomProvider rng =
RandomSource.create(RandomSource.SPLIT_MIX_64, Long.valueOf(0));
- new GeometricSampler(rng, 0);
+ final UniformRandomProvider unusedRng = new SplitMix64(0L);
+ new GeometricSampler(unusedRng, 0);
}
}
