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The EmpiricalDistributionImpl that submitted yesterday assumed the "old" 

Univariate interface, in which getN() returned a double.  The attached patch
inserts the necessary casts to avoid the rounding/truncation errors that were
causing the EmpiricalDistribution and ValueServer unit tests to fail.

The patch also adds a RandomData member variable so that getNext() does not
instantiate a new RandomData instance for each activation

PR: Bugzilla #20149
Obtained from: Issue Patch
Submitted by: Phil Steitz
Reviewed by: Tim O'Brien


git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140853 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Tim O'Brien 2003-05-22 15:19:32 +00:00
parent 1376d960b5
commit ca304541d8
1 changed files with 10 additions and 6 deletions
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16
src/java/org/apache/commons/math/EmpiricalDistributionImpl.java
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@ -87,7 +87,7 @@ import java.io.IOException;
* </ol></p>
*
* @author Phil Steitz
* @version $Revision: 1.1 $
* @version $Revision: 1.2 $
*/
public class EmpiricalDistributionImpl implements Serializable,EmpiricalDistribution {
@ -107,6 +107,9 @@ public class EmpiricalDistributionImpl implements Serializable,EmpiricalDistribu
/** upper bounds of subintervals in (0,1) "belonging" to the bins */
private double[] upperBounds = null;
/** RandomData instance to use in repeated calls to getNext() */
private RandomData randomData = new RandomDataImpl();
/**
* Creates a new EmpiricalDistribution with the default bin count
*/
@ -200,10 +203,12 @@ public class EmpiricalDistributionImpl implements Serializable,EmpiricalDistribu
// Assign upperBounds based on bin counts
upperBounds = new double[binCount];
upperBounds[0] =
(((Univariate)binStats.get(0)).getN())/sampleStats.getN();
((double)((Univariate)binStats.get(0)).getN())/
(double)sampleStats.getN();
for (int i = 1; i < binCount-1; i++) {
upperBounds[i] = upperBounds[i-1] +
(((Univariate)binStats.get(i)).getN())/sampleStats.getN();
((double)((Univariate)binStats.get(i)).getN())/
(double)sampleStats.getN();
}
upperBounds[binCount-1] = 1.0d;
@ -221,13 +226,12 @@ public class EmpiricalDistributionImpl implements Serializable,EmpiricalDistribu
double x = Math.random();
// Use this to select the bin and generate a Gaussian within the bin
RandomData rd = new RandomDataImpl();
for (int i = 0; i < binCount; i++) {
if (x <= upperBounds[i]) {
Univariate stats = (Univariate)binStats.get(i);
if (stats.getN() > 0.5) { // really mean > 0, but avoid fp error
if (stats.getN() > 0) {
if (stats.getStandardDeviation() > 0) { // more than one obs
return rd.nextGaussian
return randomData.nextGaussian
(stats.getMean(),stats.getStandardDeviation());
} else {
return stats.getMean(); // only one obs in bin