org.matheclipse.core.stat.descriptive.summary

Class SymbolicSumOfLogs

java.lang.Object

org.matheclipse.core.stat.descriptive.AbstractSymbolicStorelessUnivariateStatistic

org.matheclipse.core.stat.descriptive.summary.SymbolicSumOfLogs

All Implemented Interfaces:

java.io.Serializable, StorelessSymbolicUnivariateStatistic, SymbolicUnivariateStatistic

public class SymbolicSumOfLogs
extends AbstractSymbolicStorelessUnivariateStatistic
implements java.io.Serializable

Returns the sum of the natural logs for this collection of values.

Therefore,

• If any of values are < 0, the result is NaN.
• If all values are non-negative and less than Double.POSITIVE_INFINITY, but at least one value is 0, the result is Double.NEGATIVE_INFINITY.
• If both Double.POSITIVE_INFINITY and Double.NEGATIVE_INFINITY are among the values, the result is NaN.

Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
SymbolicSumOfLogs() Create a SumOfLogs instance

Method Summary

Modifier and Type	Method and Description
void	clear() Clears the internal state of the Statistic
IExpr	evaluate(IAST values, int begin, int length) Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.
long	getN() Returns the number of values that have been added.
IExpr	getResult() Returns the current value of the Statistic.
void	increment(IExpr d) Updates the internal state of the statistic to reflect the addition of the new value.

Methods inherited from class org.matheclipse.core.stat.descriptive.AbstractSymbolicStorelessUnivariateStatistic

evaluate, incrementAll, incrementAll, test, test, test, test

Methods inherited from class java.lang.Object

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

Constructor Detail

SymbolicSumOfLogs

public SymbolicSumOfLogs()

Create a SumOfLogs instance

Method Detail

increment

public void increment(IExpr d)

Updates the internal state of the statistic to reflect the addition of the new value.

Specified by:

increment in interface StorelessSymbolicUnivariateStatistic

Specified by:

increment in class AbstractSymbolicStorelessUnivariateStatistic

Parameters:

d - the new value.

getResult

public IExpr getResult()

Returns the current value of the Statistic.

Specified by:

getResult in interface StorelessSymbolicUnivariateStatistic

Specified by:

getResult in class AbstractSymbolicStorelessUnivariateStatistic

Returns:

value of the statistic, Double.NaN if it has been cleared or just instantiated.

getN

public long getN()

Returns the number of values that have been added.

Specified by:

getN in interface StorelessSymbolicUnivariateStatistic

Specified by:

getN in class AbstractSymbolicStorelessUnivariateStatistic

Returns:

the number of values.

clear

public void clear()

Clears the internal state of the Statistic

Specified by:

clear in interface StorelessSymbolicUnivariateStatistic

Specified by:

clear in class AbstractSymbolicStorelessUnivariateStatistic

evaluate

public IExpr evaluate(IAST values,
                      int begin,
                      int length)

Returns the sum of the natural logs of the entries in the specified portion of the input array, or Double.NaN if the designated subarray is empty.

Throws IllegalArgumentException if the array is null.

See SymbolicSumOfLogs.

Specified by:

evaluate in interface SymbolicUnivariateStatistic

Overrides:

evaluate in class AbstractSymbolicStorelessUnivariateStatistic

Parameters:

values - the input array

begin - index of the first array element to include

length - the number of elements to include

Returns:

the sum of the natural logs of the values or 0 if length = 0

Throws:

java.lang.IllegalArgumentException - if the array is null or the array index parameters are not valid

See Also:

UnivariateStatistic.evaluate(double[], int, int)