org.apache.commons.math.random
Class EmpiricalDistributionImpl

java.lang.Object
  org.apache.commons.math.random.EmpiricalDistributionImpl

All Implemented Interfaces:

Serializable, EmpiricalDistribution

public class EmpiricalDistributionImpl
extends Object
implements Serializable, EmpiricalDistribution

Implements EmpiricalDistribution interface. This implementation uses what amounts to the Variable Kernel Method with Gaussian smoothing:

Digesting the input file

1. Pass the file once to compute min and max.
2. Divide the range from min-max into binCount "bins."
3. Pass the data file again, computing bin counts and univariate statistics (mean, std dev.) for each of the bins
4. Divide the interval (0,1) into subintervals associated with the bins, with the length of a bin's subinterval proportional to its count.

Generating random values from the distribution

1. Generate a uniformly distributed value in (0,1)
2. Select the subinterval to which the value belongs.
3. Generate a random Gaussian value with mean = mean of the associated bin and std dev = std dev of associated bin.

USAGE NOTES:

• The binCount is set by default to 1000. A good rule of thumb is to set the bin count to approximately the length of the input file divided by 10.
• The input file must be a plain text file containing one valid numeric entry per line.

Version:

$Revision: 925812 $ $Date: 2010-03-21 11:49:31 -0400 (Sun, 21 Mar 2010) $

See Also:

Serialized Form

Nested Class Summary

private class	EmpiricalDistributionImpl.ArrayDataAdapter DataAdapter for data provided as array of doubles.
private class	EmpiricalDistributionImpl.DataAdapter Provides methods for computing sampleStats and beanStats abstracting the source of data.
private class	EmpiricalDistributionImpl.DataAdapterFactory Factory of DataAdapter objects.
private class	EmpiricalDistributionImpl.StreamDataAdapter DataAdapter for data provided through some input stream

Field Summary

private int	binCount number of bins
private List<SummaryStatistics>	binStats List of SummaryStatistics objects characterizing the bins
private double	delta Grid size
private boolean	loaded is the distribution loaded?
private double	max Max loaded value
private double	min Min loaded value
private RandomData	randomData RandomData instance to use in repeated calls to getNext()
private SummaryStatistics	sampleStats Sample statistics
private static long	serialVersionUID Serializable version identifier
private double[]	upperBounds upper bounds of subintervals in (0,1) "belonging" to the bins

Constructor Summary

EmpiricalDistributionImpl()
Creates a new EmpiricalDistribution with the default bin count.

EmpiricalDistributionImpl(int binCount)
Creates a new EmpiricalDistribution with the specified bin count.

Method Summary

private void	fillBinStats(Object in) Fills binStats array (second pass through data file).
private int	findBin(double value) Returns the index of the bin to which the given value belongs
int	getBinCount() Returns the number of bins.
List<SummaryStatistics>	getBinStats() Returns a List of SummaryStatistics instances containing statistics describing the values in each of the bins.
double[]	getGeneratorUpperBounds() Returns a fresh copy of the array of upper bounds of the subintervals of [0,1] used in generating data from the empirical distribution.
double	getNextValue() Generates a random value from this distribution.
StatisticalSummary	getSampleStats() Returns a StatisticalSummary describing this distribution.
double[]	getUpperBounds() Returns a fresh copy of the array of upper bounds for the bins.
boolean	isLoaded() Property indicating whether or not the distribution has been loaded.
void	load(double[] in) Computes the empirical distribution from the provided array of numbers.
void	load(File file) Computes the empirical distribution from the input file.
void	load(URL url) Computes the empirical distribution using data read from a URL.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

serialVersionUID

private static final long serialVersionUID

Serializable version identifier

See Also:

Constant Field Values

binStats

private List<SummaryStatistics> binStats

List of SummaryStatistics objects characterizing the bins

sampleStats

private SummaryStatistics sampleStats

Sample statistics

max

private double max

Max loaded value

min

private double min

Min loaded value

delta

private double delta

Grid size

binCount

private int binCount

number of bins

loaded

private boolean loaded

is the distribution loaded?

upperBounds

private double[] upperBounds

upper bounds of subintervals in (0,1) "belonging" to the bins

randomData

private RandomData randomData

RandomData instance to use in repeated calls to getNext()

Constructor Detail

EmpiricalDistributionImpl

public EmpiricalDistributionImpl()

Creates a new EmpiricalDistribution with the default bin count.

EmpiricalDistributionImpl

public EmpiricalDistributionImpl(int binCount)

Creates a new EmpiricalDistribution with the specified bin count.

Parameters:

binCount - number of bins

Method Detail

load

public void load(double[] in)

Computes the empirical distribution from the provided array of numbers.

Specified by:

load in interface EmpiricalDistribution

Parameters:

in - the input data array

load

public void load(URL url)
          throws IOException

Computes the empirical distribution using data read from a URL.

Specified by:

load in interface EmpiricalDistribution

Parameters:

url - url of the input file

Throws:

IOException - if an IO error occurs

load

public void load(File file)
          throws IOException

Computes the empirical distribution from the input file.

Specified by:

load in interface EmpiricalDistribution

Parameters:

file - the input file

Throws:

IOException - if an IO error occurs

fillBinStats

private void fillBinStats(Object in)
                   throws IOException

Fills binStats array (second pass through data file).

Parameters:

in - object providing access to the data

Throws:

IOException - if an IO error occurs

findBin

private int findBin(double value)

Returns the index of the bin to which the given value belongs

Parameters:

value - the value whose bin we are trying to find

Returns:

the index of the bin containing the value

getNextValue

public double getNextValue()
                    throws IllegalStateException

Generates a random value from this distribution.

Specified by:

getNextValue in interface EmpiricalDistribution

Returns:

the random value.

Throws:

IllegalStateException - if the distribution has not been loaded

getSampleStats

public StatisticalSummary getSampleStats()

Returns a StatisticalSummary describing this distribution. Preconditions:

• the distribution must be loaded before invoking this method

Specified by:

getSampleStats in interface EmpiricalDistribution

Returns:

the sample statistics

Throws:

IllegalStateException - if the distribution has not been loaded

getBinCount

public int getBinCount()

Returns the number of bins.

Specified by:

getBinCount in interface EmpiricalDistribution

Returns:

the number of bins.

getBinStats

public List<SummaryStatistics> getBinStats()

Returns a List of SummaryStatistics instances containing statistics describing the values in each of the bins. The list is indexed on the bin number.

Specified by:

getBinStats in interface EmpiricalDistribution

Returns:

List of bin statistics.

getUpperBounds

public double[] getUpperBounds()

Returns a fresh copy of the array of upper bounds for the bins. Bins are:
[min,upperBounds[0]],(upperBounds[0],upperBounds[1]],..., (upperBounds[binCount-2], upperBounds[binCount-1] = max].

Note: In versions 1.0-2.0 of commons-math, this method incorrectly returned the array of probability generator upper bounds now returned by getGeneratorUpperBounds().

Specified by:

getUpperBounds in interface EmpiricalDistribution

Returns:

array of bin upper bounds

Since:

2.1

getGeneratorUpperBounds

public double[] getGeneratorUpperBounds()

Returns a fresh copy of the array of upper bounds of the subintervals of [0,1] used in generating data from the empirical distribution. Subintervals correspond to bins with lengths proportional to bin counts.

In versions 1.0-2.0 of commons-math, this array was (incorrectly) returned by getUpperBounds().

Returns:

array of upper bounds of subintervals used in data generation

Since:

2.1

isLoaded

public boolean isLoaded()

Property indicating whether or not the distribution has been loaded.

Specified by:

isLoaded in interface EmpiricalDistribution

Returns:

true if the distribution has been loaded