Package org.apache.commons.math.stat.descriptive

Class SynchronizedMultivariateSummaryStatistics

java.lang.Object

org.apache.commons.math.stat.descriptive.MultivariateSummaryStatistics

org.apache.commons.math.stat.descriptive.SynchronizedMultivariateSummaryStatistics

All Implemented Interfaces:

java.io.Serializable, StatisticalMultivariateSummary

public class SynchronizedMultivariateSummaryStatistics
extends MultivariateSummaryStatistics

Implementation of MultivariateSummaryStatistics that is safe to use in a multithreaded environment. Multiple threads can safely operate on a single instance without causing runtime exceptions due to race conditions. In effect, this implementation makes modification and access methods atomic operations for a single instance. That is to say, as one thread is computing a statistic from the instance, no other thread can modify the instance nor compute another statistic.

Since:

1.2

Version:

$Revision: 811685 $ $Date: 2009-09-05 19:36:48 +0200 (sam. 05 sept. 2009) $

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor	Description
SynchronizedMultivariateSummaryStatistics(int k, boolean isCovarianceBiasCorrected)	Construct a SynchronizedMultivariateSummaryStatistics instance

Method Summary

Modifier and Type	Method	Description
void	addValue(double[] value)	Add an n-tuple to the data
void	clear()	Resets all statistics and storage
boolean	equals(java.lang.Object object)	Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.
RealMatrix	getCovariance()	Returns the covariance matrix of the values that have been added.
int	getDimension()	Returns the dimension of the data
StorelessUnivariateStatistic[]	getGeoMeanImpl()	Returns the currently configured geometric mean implementation
double[]	getGeometricMean()	Returns an array whose ith entry is the geometric mean of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
double[]	getMax()	Returns an array whose ith entry is the maximum of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getMaxImpl()	Returns the currently configured maximum implementation
double[]	getMean()	Returns an array whose ith entry is the mean of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getMeanImpl()	Returns the currently configured mean implementation
double[]	getMin()	Returns an array whose ith entry is the minimum of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getMinImpl()	Returns the currently configured minimum implementation
long	getN()	Returns the number of available values
double[]	getStandardDeviation()	Returns an array whose ith entry is the standard deviation of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
double[]	getSum()	Returns an array whose ith entry is the sum of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getSumImpl()	Returns the currently configured Sum implementation
double[]	getSumLog()	Returns an array whose ith entry is the sum of logs of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getSumLogImpl()	Returns the currently configured sum of logs implementation
double[]	getSumSq()	Returns an array whose ith entry is the sum of squares of the ith entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])
StorelessUnivariateStatistic[]	getSumsqImpl()	Returns the currently configured sum of squares implementation
int	hashCode()	Returns hash code based on values of statistics
void	setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl)	Sets the implementation for the geometric mean.
void	setMaxImpl(StorelessUnivariateStatistic[] maxImpl)	Sets the implementation for the maximum.
void	setMeanImpl(StorelessUnivariateStatistic[] meanImpl)	Sets the implementation for the mean.
void	setMinImpl(StorelessUnivariateStatistic[] minImpl)	Sets the implementation for the minimum.
void	setSumImpl(StorelessUnivariateStatistic[] sumImpl)	Sets the implementation for the Sum.
void	setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)	Sets the implementation for the sum of logs.
void	setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl)	Sets the implementation for the sum of squares.
java.lang.String	toString()	Generates a text report displaying summary statistics from values that have been added.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

SynchronizedMultivariateSummaryStatistics

public SynchronizedMultivariateSummaryStatistics(int k,
                                                 boolean isCovarianceBiasCorrected)

Construct a SynchronizedMultivariateSummaryStatistics instance

Parameters:

k - dimension of the data

isCovarianceBiasCorrected - if true, the unbiased sample covariance is computed, otherwise the biased population covariance is computed

Method Detail

addValue

public void addValue(double[] value)
              throws DimensionMismatchException

Add an n-tuple to the data

Overrides:

addValue in class MultivariateSummaryStatistics

Parameters:

value - the n-tuple to add

Throws:

DimensionMismatchException - if the length of the array does not match the one used at construction

getDimension

public int getDimension()

Returns the dimension of the data

Specified by:

getDimension in interface StatisticalMultivariateSummary

Overrides:

getDimension in class MultivariateSummaryStatistics

Returns:

The dimension of the data

getN

public long getN()

Returns the number of available values

Specified by:

getN in interface StatisticalMultivariateSummary

Overrides:

getN in class MultivariateSummaryStatistics

Returns:

The number of available values

getSum

public double[] getSum()

Returns an array whose i^th entry is the sum of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getSum in interface StatisticalMultivariateSummary

Overrides:

getSum in class MultivariateSummaryStatistics

Returns:

the array of component sums

getSumSq

public double[] getSumSq()

Returns an array whose i^th entry is the sum of squares of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getSumSq in interface StatisticalMultivariateSummary

Overrides:

getSumSq in class MultivariateSummaryStatistics

Returns:

the array of component sums of squares

getSumLog

public double[] getSumLog()

Returns an array whose i^th entry is the sum of logs of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getSumLog in interface StatisticalMultivariateSummary

Overrides:

getSumLog in class MultivariateSummaryStatistics

Returns:

the array of component log sums

getMean

public double[] getMean()

Returns an array whose i^th entry is the mean of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getMean in interface StatisticalMultivariateSummary

Overrides:

getMean in class MultivariateSummaryStatistics

Returns:

the array of component means

getStandardDeviation

public double[] getStandardDeviation()

Returns an array whose i^th entry is the standard deviation of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getStandardDeviation in interface StatisticalMultivariateSummary

Overrides:

getStandardDeviation in class MultivariateSummaryStatistics

Returns:

the array of component standard deviations

getCovariance

public RealMatrix getCovariance()

Returns the covariance matrix of the values that have been added.

Specified by:

getCovariance in interface StatisticalMultivariateSummary

Overrides:

getCovariance in class MultivariateSummaryStatistics

Returns:

the covariance matrix

getMax

public double[] getMax()

Returns an array whose i^th entry is the maximum of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getMax in interface StatisticalMultivariateSummary

Overrides:

getMax in class MultivariateSummaryStatistics

Returns:

the array of component maxima

getMin

public double[] getMin()

Returns an array whose i^th entry is the minimum of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getMin in interface StatisticalMultivariateSummary

Overrides:

getMin in class MultivariateSummaryStatistics

Returns:

the array of component minima

getGeometricMean

public double[] getGeometricMean()

Returns an array whose i^th entry is the geometric mean of the i^th entries of the arrays that have been added using MultivariateSummaryStatistics.addValue(double[])

Specified by:

getGeometricMean in interface StatisticalMultivariateSummary

Overrides:

getGeometricMean in class MultivariateSummaryStatistics

Returns:

the array of component geometric means

toString

public java.lang.String toString()

Generates a text report displaying summary statistics from values that have been added.

Overrides:

toString in class MultivariateSummaryStatistics

Returns:

String with line feeds displaying statistics

clear

public void clear()

Resets all statistics and storage

Overrides:

clear in class MultivariateSummaryStatistics

equals

public boolean equals(java.lang.Object object)

Returns true iff object is a MultivariateSummaryStatistics instance and all statistics have the same values as this.

Overrides:

equals in class MultivariateSummaryStatistics

Parameters:

object - the object to test equality against.

Returns:

true if object equals this

hashCode

public int hashCode()

Returns hash code based on values of statistics

Overrides:

hashCode in class MultivariateSummaryStatistics

Returns:

hash code

getSumImpl

public StorelessUnivariateStatistic[] getSumImpl()

Returns the currently configured Sum implementation

Overrides:

getSumImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the sum

setSumImpl

public void setSumImpl(StorelessUnivariateStatistic[] sumImpl)
                throws DimensionMismatchException

Sets the implementation for the Sum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setSumImpl in class MultivariateSummaryStatistics

Parameters:

sumImpl - the StorelessUnivariateStatistic instance to use for computing the Sum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getSumsqImpl

public StorelessUnivariateStatistic[] getSumsqImpl()

Returns the currently configured sum of squares implementation

Overrides:

getSumsqImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the sum of squares

setSumsqImpl

public void setSumsqImpl(StorelessUnivariateStatistic[] sumsqImpl)
                  throws DimensionMismatchException

Sets the implementation for the sum of squares.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setSumsqImpl in class MultivariateSummaryStatistics

Parameters:

sumsqImpl - the StorelessUnivariateStatistic instance to use for computing the sum of squares

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getMinImpl

public StorelessUnivariateStatistic[] getMinImpl()

Returns the currently configured minimum implementation

Overrides:

getMinImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the minimum

setMinImpl

public void setMinImpl(StorelessUnivariateStatistic[] minImpl)
                throws DimensionMismatchException

Sets the implementation for the minimum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setMinImpl in class MultivariateSummaryStatistics

Parameters:

minImpl - the StorelessUnivariateStatistic instance to use for computing the minimum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getMaxImpl

public StorelessUnivariateStatistic[] getMaxImpl()

Returns the currently configured maximum implementation

Overrides:

getMaxImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the maximum

setMaxImpl

public void setMaxImpl(StorelessUnivariateStatistic[] maxImpl)
                throws DimensionMismatchException

Sets the implementation for the maximum.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setMaxImpl in class MultivariateSummaryStatistics

Parameters:

maxImpl - the StorelessUnivariateStatistic instance to use for computing the maximum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getSumLogImpl

public StorelessUnivariateStatistic[] getSumLogImpl()

Returns the currently configured sum of logs implementation

Overrides:

getSumLogImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the log sum

setSumLogImpl

public void setSumLogImpl(StorelessUnivariateStatistic[] sumLogImpl)
                   throws DimensionMismatchException

Sets the implementation for the sum of logs.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setSumLogImpl in class MultivariateSummaryStatistics

Parameters:

sumLogImpl - the StorelessUnivariateStatistic instance to use for computing the log sum

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getGeoMeanImpl

public StorelessUnivariateStatistic[] getGeoMeanImpl()

Returns the currently configured geometric mean implementation

Overrides:

getGeoMeanImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the geometric mean

setGeoMeanImpl

public void setGeoMeanImpl(StorelessUnivariateStatistic[] geoMeanImpl)
                    throws DimensionMismatchException

Sets the implementation for the geometric mean.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setGeoMeanImpl in class MultivariateSummaryStatistics

Parameters:

geoMeanImpl - the StorelessUnivariateStatistic instance to use for computing the geometric mean

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction

getMeanImpl

public StorelessUnivariateStatistic[] getMeanImpl()

Returns the currently configured mean implementation

Overrides:

getMeanImpl in class MultivariateSummaryStatistics

Returns:

the StorelessUnivariateStatistic implementing the mean

setMeanImpl

public void setMeanImpl(StorelessUnivariateStatistic[] meanImpl)
                 throws DimensionMismatchException

Sets the implementation for the mean.

This method must be activated before any data has been added - i.e., before addValue has been used to add data; otherwise an IllegalStateException will be thrown.

Overrides:

setMeanImpl in class MultivariateSummaryStatistics

Parameters:

meanImpl - the StorelessUnivariateStatistic instance to use for computing the mean

Throws:

DimensionMismatchException - if the array dimension does not match the one used at construction