org.apache.commons.math3.stat.descriptive

## Class SynchronizedMultivariateSummaryStatistics

• All Implemented Interfaces:
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
Serialized Form
• ### Constructor Summary

Constructors
Constructor and Description
SynchronizedMultivariateSummaryStatistics(int k, boolean isCovarianceBiasCorrected)
Construct a SynchronizedMultivariateSummaryStatistics instance
• ### Method Summary

Methods
Modifier and Type Method and Description
void addValue(double[] value)
Add an n-tuple to the data
void clear()
Resets all statistics and storage
boolean equals(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.
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

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 ith entry is the sum of the ith 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 ith entry is the sum of squares of the ith 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 ith entry is the sum of logs of the ith 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 ith entry is the mean of the ith 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 ith entry is the standard deviation of the ith 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 ith entry is the maximum of the ith 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 ith entry is the minimum of the ith 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 ith entry is the geometric mean of the ith 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 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(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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)
• #### 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,
MathIllegalStateException

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
MathIllegalStateException - if data has already been added (i.e if n > 0)