Package org.tweetyproject.math.norm

Class EntropyNorm<T extends Comparable<T>>

java.lang.Object

org.tweetyproject.math.func.EntropyFunction

org.tweetyproject.math.norm.EntropyNorm<T>

Type Parameters:

T - The class of the objects used.

All Implemented Interfaces:

SimpleFunction<Vector<Double>,Double>, SimpleRealValuedFunction, Norm<Vector<Double>>, RealVectorNorm

public class EntropyNorm<T extends 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	Description
EntropyNorm()	Constructor

Method Summary

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

Methods inherited from class org.tweetyproject.math.func.EntropyFunction

eval, getTerm

Methods inherited from class java.lang.Object

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

Constructor Details

EntropyNorm

public EntropyNorm()

Constructor

Method Details

norm

public double norm(Vector<Double> obj)

Description copied from interface: Norm

Returns the norm of the given object

Specified by:

norm in interface Norm<T extends Comparable<T>>

Parameters:

obj - some object

Returns:

the norm of the object

norm

public double norm(ProbabilityFunction<T> prob)

norm

Parameters:

prob - problem

Returns:

Probability Vector As Doubles

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(Vector<Double> obj1,
 Vector<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<T extends Comparable<T>>

Parameters:

obj1 - some object

obj2 - some object

Returns:

the distance between the two objects

distance

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

distance between problems

Parameters:

prob1 - problem 1

prob2 - problem 2

Returns:

distance

normTerm

public Term normTerm(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(Vector<Term> obj1,
 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