de.up.ling.irtg.laboratory

Class BasicOperations

java.lang.Object

de.up.ling.irtg.laboratory.BasicOperations

public class BasicOperations
extends Object

This class contains static methods for Alto Lab that don't necessarily fit anywhere else.

Author:

koller

Constructor Summary

Constructors

Constructor and Description
BasicOperations()

Method Summary

Modifier and Type	Method and Description
static double	average(Object[] values) Computes the average value of the doubles.
static DoubleList	averageLists(Object[] list) The input list must be a list of DoubleList entries, each of equal size -- if that is the case, returns a DoubleList with i-th entry the average of the i-th entries of the input lists.
static Double	div(Object denominator, Object divisor) Standard division.
static double	equals(Object object, Object other) Returns 1 if object and other are both null, or both not null and equal.
static double	f1(double precision, double recall) Computes F1-score (standard F-score) from precision and recall.
static double	isNotNull(Object object) Returns 0 if object is null, and 1 if it is not null.
static double	percent(double x, double y)
static double	selfNormDifference(Object d1, Object d2) Returns the absolute value of (d1-d2)/d1.
static DoubleList	sumLists(Object[] list) The input list must be a list of DoubleList entries, each of equal size -- if that is the case, returns a DoubleList with i-th entry the sum of the i-th entries of the input lists.
static Double	weightedAverageWithIntWeights(Object[] values, Object[] weights) Computes the average of values, weighted by weights.

Methods inherited from class java.lang.Object

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

Constructor Detail

BasicOperations

public BasicOperations()

Method Detail

percent

public static double percent(double x,
                             double y)

weightedAverageWithIntWeights

public static Double weightedAverageWithIntWeights(Object[] values,
                                                   Object[] weights)

Computes the average of values, weighted by weights. The arrays must be of equal length and must contain Doubles.

Parameters:

values -

weights -

Returns:

average

public static double average(Object[] values)

Computes the average value of the doubles. The entries in values must be Integer, Long, Short, Float, Byte or Double.

Parameters:

values -

Returns:

div

public static Double div(Object denominator,
                         Object divisor)

Standard division. Both denominator and divisor must be Doubles.

Parameters:

denominator -

divisor -

Returns:

f1

public static double f1(double precision,
                        double recall)

Computes F1-score (standard F-score) from precision and recall.

Parameters:

precision -

recall -

Returns:

isNotNull

public static double isNotNull(Object object)

Returns 0 if object is null, and 1 if it is not null.

Parameters:

object -

Returns:

equals

public static double equals(Object object,
                            Object other)

Returns 1 if object and other are both null, or both not null and equal. Returns 0 otherwise.

Parameters:

object -

other -

Returns:

selfNormDifference

public static double selfNormDifference(Object d1,
                                        Object d2)

Returns the absolute value of (d1-d2)/d1. Both d1 and d2 must be numbers. If either is null, it is replaced by 0. If d1 is 0 or null, returns 0.

Parameters:

d1 -

d2 -

Returns:

sumLists

public static DoubleList sumLists(Object[] list)

The input list must be a list of DoubleList entries, each of equal size -- if that is the case, returns a DoubleList with i-th entry the sum of the i-th entries of the input lists. returns

Parameters:

list -

Returns:

averageLists

public static DoubleList averageLists(Object[] list)

The input list must be a list of DoubleList entries, each of equal size -- if that is the case, returns a DoubleList with i-th entry the average of the i-th entries of the input lists. returns

Parameters:

list -

Returns: