net.sf.tweety.math.norm

Class EntropyNorm<T extends java.lang.Comparable<T>>

java.lang.Object

net.sf.tweety.math.func.EntropyFunction

net.sf.tweety.math.norm.EntropyNorm<T>

All Implemented Interfaces:

SimpleFunction<java.util.Vector<java.lang.Double>,java.lang.Double>, SimpleRealValuedFunction, Norm<java.util.Vector<java.lang.Double>>, RealVectorNorm

public class EntropyNorm<T extends java.lang.Comparable<T>>
extends EntropyFunction
implements RealVectorNorm

The entropy norm. Uses the entropy of a vector of doubles (=probability function) as a measure of norm and the relative entropy of two probability distributions as distance. Note that entropy is not actually a norm!

Author:

Matthias Thimm

Constructor Summary

Constructors

Constructor and Description
EntropyNorm()

Method Summary

Modifier and Type	Method and Description
double	distance(ProbabilityFunction<T> prob1, ProbabilityFunction<T> prob2)
double	distance(java.util.Vector<java.lang.Double> obj1, java.util.Vector<java.lang.Double> obj2) The distance between the two object, i.e.
Term	distanceTerm(Term[] obj1, Term[] obj2) The distance between the two objects as a term.
Term	distanceTerm(java.util.Vector<Term> obj1, java.util.Vector<Term> obj2) The distance between the two objects as a term.
double	norm(ProbabilityFunction<T> prob)
double	norm(java.util.Vector<java.lang.Double> obj) Returns the norm of the given object
Term	normTerm(Term[] obj) Returns the norm as a term of the given terms
Term	normTerm(java.util.Vector<Term> obj) Returns the norm as a term of the given terms

Methods inherited from class net.sf.tweety.math.func.EntropyFunction

eval, getTerm

Methods inherited from class java.lang.Object

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

Constructor Detail

EntropyNorm

public EntropyNorm()

Method Detail

norm

public double norm(java.util.Vector<java.lang.Double> obj)

Description copied from interface: Norm

Returns the norm of the given object

Specified by:

norm in interface Norm<java.util.Vector<java.lang.Double>>

Parameters:

obj - some object

Returns:

the norm of the object

norm

public double norm(ProbabilityFunction<T> prob)

normTerm

public Term normTerm(Term[] obj)

Description copied from interface: RealVectorNorm

Returns the norm as a term of the given terms

Specified by:

normTerm in interface RealVectorNorm

Parameters:

obj - some term array

Returns:

the term of the norm

distanceTerm

public Term distanceTerm(Term[] obj1,
                         Term[] obj2)

Description copied from interface: RealVectorNorm

The distance between the two objects as a term.

Specified by:

distanceTerm in interface RealVectorNorm

Parameters:

obj1 - some terms

obj2 - some terms

Returns:

the distance between the two objects as a term

distance

public double distance(java.util.Vector<java.lang.Double> obj1,
                       java.util.Vector<java.lang.Double> obj2)

Description copied from interface: Norm

The distance between the two object, i.e. the norm of the difference vector.

Specified by:

distance in interface Norm<java.util.Vector<java.lang.Double>>

Parameters:

obj1 - some object

obj2 - some object

Returns:

the distance between the two objects

distance

public double distance(ProbabilityFunction<T> prob1,
                       ProbabilityFunction<T> prob2)

normTerm

public Term normTerm(java.util.Vector<Term> obj)

Description copied from interface: RealVectorNorm

Returns the norm as a term of the given terms

Specified by:

normTerm in interface RealVectorNorm

Parameters:

obj - some term vector

Returns:

the term of the norm

distanceTerm

public Term distanceTerm(java.util.Vector<Term> obj1,
                         java.util.Vector<Term> obj2)

Description copied from interface: RealVectorNorm

The distance between the two objects as a term.

Specified by:

distanceTerm in interface RealVectorNorm

Parameters:

obj1 - some terms

obj2 - some terms

Returns:

the distance between the two objects as a term