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Reverted incompatible changes made in r1420006. 

Fixed javadoc error in EmpiricalDistribution class javadoc.
Deprecated constructors taking RandomDataImpl instances in EmpiricalDistribution, ValueServer.  These constructors predate RandomGenerator, which should be used directly as the source of random data for these classes.


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1421968 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Phil Steitz 2012-12-14 16:28:23 +00:00
parent 610b5d26c9
commit 2f33283981
2 changed files with 73 additions and 130 deletions
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168
src/main/java/org/apache/commons/math3/random/EmpiricalDistribution.java
View File

@ -29,8 +29,8 @@ import java.util.ArrayList;
import java.util.List;
import org.apache.commons.math3.distribution.AbstractRealDistribution;
import org.apache.commons.math3.distribution.RealDistribution;
import org.apache.commons.math3.distribution.NormalDistribution;
import org.apache.commons.math3.distribution.RealDistribution;
import org.apache.commons.math3.exception.MathIllegalStateException;
import org.apache.commons.math3.exception.MathInternalError;
import org.apache.commons.math3.exception.NullArgumentException;
@ -134,18 +134,14 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
/** upper bounds of subintervals in (0,1) "belonging" to the bins */
private double[] upperBounds = null;
/** Data generator. */
private final RandomDataGenerator randomDataGen;
/**
* XXX Enable backward-compatibility (to be removed in 4.0).
*/
private final boolean useRandomDataImpl;
/** RandomDataImpl instance to use in repeated calls to getNext() */
private final RandomDataImpl randomData;
/**
* Creates a new EmpiricalDistribution with the default bin count.
*/
public EmpiricalDistribution() {
this(DEFAULT_BIN_COUNT);
this(DEFAULT_BIN_COUNT, new RandomDataImpl());
}
/**
@ -154,7 +150,7 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
* @param binCount number of bins
*/
public EmpiricalDistribution(int binCount) {
this(binCount, (RandomGenerator) null);
this(binCount, new RandomDataImpl());
}
/**
@ -162,75 +158,20 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
* provided {@link RandomGenerator} as the source of random data.
*
* @param binCount number of bins
* @param randomData random data generator (may be null, resulting in a default generator)
* @deprecated As of 3.1. To be removed in 4.0. Please use
* {@link #EmpiricalDistribution(int,RandomDataGenerator)} instead.
*/
@Deprecated
public EmpiricalDistribution(int binCount, RandomDataImpl randomData) {
this.binCount = binCount;
this.randomData = randomData == null ?
new RandomDataImpl() :
randomData;
binStats = new ArrayList<SummaryStatistics>();
useRandomDataImpl = true;
randomDataGen = null;
}
/**
* Creates a new EmpiricalDistribution with the specified bin count using the
* provided {@link RandomGenerator} as the source of random data.
*
* @param randomData random data generator (may be null, resulting in a default generator)
* @deprecated As of 3.1. To be removed in 4.0. Please use
* {@link #EmpiricalDistribution(RandomDataGenerator)} instead.
*/
@Deprecated
public EmpiricalDistribution(RandomDataImpl randomData) {
this(DEFAULT_BIN_COUNT, randomData);
}
/**
* Creates a new EmpiricalDistribution with the specified bin count using the
* provided {@link RandomGenerator} as the source of random data.
*
* @param binCount number of bins
* @param randomData random data generator (may be null, resulting in a default generator)
*/
public EmpiricalDistribution(int binCount, RandomDataGenerator randomData) {
this.binCount = binCount;
this.randomDataGen = randomData == null ?
new RandomDataGenerator() :
randomData;
binStats = new ArrayList<SummaryStatistics>();
useRandomDataImpl = false; // XXX Remove in 4.0
}
/**
* Creates a new EmpiricalDistribution with the specified bin count using the
* provided {@link RandomGenerator} as the source of random data.
*
* @param randomData random data generator (may be null, resulting in a default generator)
*/
public EmpiricalDistribution(RandomDataGenerator randomData) {
this(DEFAULT_BIN_COUNT, randomData);
}
/**
* Creates a new EmpiricalDistribution with the specified bin count using the
* provided {@link RandomGenerator} as the source of random data.
*
* @param binCount number of bins
* @param generator random data generator (may be null, resulting in a default generator)
* @param generator random data generator (may be null, resulting in default JDK generator)
* @since 3.0
*/
public EmpiricalDistribution(int binCount, RandomGenerator generator) {
this(binCount, new RandomDataGenerator(generator));
this.binCount = binCount;
randomData = new RandomDataImpl(generator);
binStats = new ArrayList<SummaryStatistics>();
}
/**
* Creates a new EmpiricalDistribution with default bin count using the
* provided {@link RandomGenerator} as the source of random data.
*
* @param generator random data generator (may be null, resulting in default generator)
* @param generator random data generator (may be null, resulting in default JDK generator)
* @since 3.0
*/
public EmpiricalDistribution(RandomGenerator generator) {
@ -238,6 +179,31 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
}
/**
* Creates a new EmpiricalDistribution with the specified bin count using the
* provided {@link RandomDataImpl} instance as the source of random data.
*
* @param binCount number of bins
* @param randomData random data generator (may be null, resulting in default JDK generator)
* @since 3.0
*/
public EmpiricalDistribution(int binCount, RandomDataImpl randomData) {
this.binCount = binCount;
this.randomData = randomData;
binStats = new ArrayList<SummaryStatistics>();
}
/**
* Creates a new EmpiricalDistribution with default bin count using the
* provided {@link RandomDataImpl} as the source of random data.
*
* @param randomData random data generator (may be null, resulting in default JDK generator)
* @since 3.0
*/
public EmpiricalDistribution(RandomDataImpl randomData) {
this(DEFAULT_BIN_COUNT, randomData);
}
/**
* Computes the empirical distribution from the provided
* array of numbers.
*
@ -288,7 +254,7 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
} finally {
try {
in.close();
} catch (IOException ex) { // NOPMD
} catch (IOException ex) {
// ignore
}
}
@ -320,7 +286,7 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
} finally {
try {
in.close();
} catch (IOException ex) { // NOPMD
} catch (IOException ex) {
// ignore
}
}
@ -497,41 +463,22 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
throw new MathIllegalStateException(LocalizedFormats.DISTRIBUTION_NOT_LOADED);
}
if (useRandomDataImpl) {
// XXX backward compatibility.
// Start with a uniformly distributed random number in (0, 1)
final double x = randomData.nextUniform(0,1);
// Use this to select the bin and generate a Gaussian within the bin
for (int i = 0; i < binCount; i++) {
if (x <= upperBounds[i]) {
SummaryStatistics stats = binStats.get(i);
if (stats.getN() > 0) {
if (stats.getStandardDeviation() > 0) { // more than one obs
return randomData.nextGaussian(stats.getMean(),
stats.getStandardDeviation());
} else {
return stats.getMean(); // only one obs in bin
}
}
}
}
} else {
// Start with a uniformly distributed random number in (0, 1)
final double x = randomDataGen.nextUniform(0, 1);
// Use this to select the bin and generate a Gaussian within the bin
for (int i = 0; i < binCount; i++) {
if (x <= upperBounds[i]) {
SummaryStatistics stats = binStats.get(i);
if (stats.getN() > 0) {
if (stats.getStandardDeviation() > 0) { // more than one obs
return randomDataGen.nextGaussian(stats.getMean(),
stats.getStandardDeviation());
} else {
return stats.getMean(); // only one obs in bin
}
}
}
}
// Start with a uniformly distributed random number in (0,1)
final double x = randomData.nextUniform(0,1);
// Use this to select the bin and generate a Gaussian within the bin
for (int i = 0; i < binCount; i++) {
if (x <= upperBounds[i]) {
SummaryStatistics stats = binStats.get(i);
if (stats.getN() > 0) {
if (stats.getStandardDeviation() > 0) { // more than one obs
return randomData.nextGaussian(stats.getMean(),
stats.getStandardDeviation());
} else {
return stats.getMean(); // only one obs in bin
}
}
}
}
throw new MathIllegalStateException(LocalizedFormats.NO_BIN_SELECTED);
}
@ -624,12 +571,7 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
* @since 3.0
*/
public void reSeed(long seed) {
if (useRandomDataImpl) {
// XXX backward compatibility.
randomData.reSeed(seed);
} else {
randomDataGen.reSeed(seed);
}
randomData.reSeed(seed);
}
// Distribution methods ---------------------------
@ -819,7 +761,7 @@ public class EmpiricalDistribution extends AbstractRealDistribution {
*/
@Override
public void reseedRandomGenerator(long seed) {
reSeed(seed);
randomData.reSeed(seed);
}
/**

35
src/main/java/org/apache/commons/math3/random/ValueServer.java
View File

@ -88,35 +88,36 @@ public class ValueServer {
private BufferedReader filePointer = null;
/** RandomDataImpl to use for random data generation. */
private final RandomDataGenerator randomData;
private final RandomDataImpl randomData;
// Data generation modes ======================================
/** Creates new ValueServer */
public ValueServer() {
randomData = new RandomDataGenerator();
randomData = new RandomDataImpl();
}
/**
* Construct a ValueServer instance using a RandomDataGenerator as its source
* of random data.
*
* @param randomData random data source
* @since 3.0
*/
public ValueServer(RandomDataGenerator randomData) {
this.randomData = randomData;
}
/**
* Construct a ValueServer instance using a RandomDataImpl as its source
* of random data.
*
* @param randomData random data source
* @deprecated As of 3.1. Use {@link #ValueServer(RandomDataGenerator)} instead.
* @param randomData the RandomDataImpl instance used to source random data
* @since 3.0
* @deprecated use {@link #ValueServer(RandomGenerator)}
*/
@Deprecated
public ValueServer(RandomDataImpl randomData) {
this(randomData.getDelegate());
this.randomData = randomData;
}
/**
* Construct a ValueServer instance using a RandomGenerator as its source
* of random data.
*
* @since 3.1
* @param generator source of random data
*/
public ValueServer(RandomGenerator generator) {
this.randomData = new RandomDataImpl(generator);
}
/**
@ -288,7 +289,7 @@ public class ValueServer {
try {
filePointer.close();
filePointer = null;
} catch (IOException ex) { // NOPMD
} catch (IOException ex) {
// ignore
}
}