net.sf.tweety.logics.pcl.semantics

Class ProbabilityDistribution<T extends Interpretation<PlBeliefSet,PropositionalFormula>>

java.lang.Object

net.sf.tweety.commons.AbstractInterpretation<PclBeliefSet,ProbabilisticConditional>

net.sf.tweety.logics.pcl.semantics.ProbabilityDistribution<T>

Type Parameters:

T - The actual interpretation class used for this distribution.

All Implemented Interfaces:

java.util.Map<T,Probability>, Interpretation<PclBeliefSet,ProbabilisticConditional>

public class ProbabilityDistribution<T extends Interpretation<PlBeliefSet,PropositionalFormula>>
extends AbstractInterpretation<PclBeliefSet,ProbabilisticConditional>
implements java.util.Map<T,Probability>

This class represents a probability distribution on some logical language

Author:

Matthias Thimm

Nested Class Summary

Nested classes/interfaces inherited from interface java.util.Map

java.util.Map.Entry<K,V>

Field Summary

Fields

Modifier and Type	Field and Description
private java.util.Map<T,Probability>	probabilities The probabilities of the interpretations.
private Signature	signature The signature of the underlying language.

Constructor Summary

Constructors

Constructor and Description
ProbabilityDistribution(Signature signature) Creates a new probability distribution.

Method Summary

Modifier and Type	Method and Description
void	clear()
Probability	conditionalProbability(Conditional c) Returns the probability of the given conditional
boolean	containsKey(java.lang.Object key)
boolean	containsValue(java.lang.Object value)
static <S extends Interpretation<PlBeliefSet,PropositionalFormula>> ProbabilityDistribution<S>	convexCombination(double[] factors, ProbabilityDistribution<S>[] creators) Computes the convex combination of the given probability distributions P1,...,PN with parameters factors, i.e.
ProbabilityDistribution<T>	convexCombination(double d, ProbabilityDistribution<T> other) Computes the convex combination of this P1 and the given probability distribution P2 with parameter d, i.e.
double	entropy() Returns the entropy of this probability distribution.
java.util.Set<java.util.Map.Entry<T,Probability>>	entrySet()
Probability	get(java.lang.Object key)
Signature	getSignature() Returns the signature of the underlying language.
static <S extends Interpretation<PlBeliefSet,PropositionalFormula>> ProbabilityDistribution<S>	getUniformDistribution(java.util.Set<S> interpretations, Signature sig) Returns the uniform distribution on the given interpretations.
boolean	isEmpty()
java.util.Set<T>	keySet()
ProbabilityDistribution<T>	linearCombination(double d1, double d2, ProbabilityDistribution<T> other) Makes a linear combination of this distribution "p1" and the given distribution "other" and the given parameters, i.e.
static void	normalize(java.util.List<java.lang.Double> probabilities) Normalizes the given list of probabilities, i.e.
Probability	probability(Interpretation<PlBeliefSet,PropositionalFormula> w) Gets the probability of the given Herbrand interpretation (this is just an alias for get(Object o).
Probability	probability(PropositionalFormula f) Returns the probability of the given formula
Probability	put(T key, Probability value)
void	putAll(java.util.Map<? extends T,? extends Probability> m)
Probability	remove(java.lang.Object key)
boolean	satisfies(PclBeliefSet beliefBase) Checks whether this interpretation satisfies the given knowledge base.
boolean	satisfies(ProbabilisticConditional formula) Checks whether this interpretation satisfies the given formula.
int	size()
java.lang.String	toString()
java.util.Collection<Probability>	values()

Methods inherited from class net.sf.tweety.commons.AbstractInterpretation

satisfies

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.util.Map

compute, computeIfAbsent, computeIfPresent, equals, forEach, getOrDefault, hashCode, merge, putIfAbsent, remove, replace, replace, replaceAll

Field Detail

probabilities

private java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability> probabilities

The probabilities of the interpretations.

signature

private Signature signature

The signature of the underlying language.

Constructor Detail

ProbabilityDistribution

public ProbabilityDistribution(Signature signature)

Creates a new probability distribution.

Method Detail

getSignature

public Signature getSignature()

Returns the signature of the underlying language.

Returns:

the signature of the underlying language.

satisfies

public boolean satisfies(ProbabilisticConditional formula)
                  throws java.lang.IllegalArgumentException

Description copied from interface: Interpretation

Checks whether this interpretation satisfies the given formula.

Specified by:

satisfies in interface Interpretation<PclBeliefSet,ProbabilisticConditional>

Parameters:

formula - a formula .

Returns:

"true" if this interpretation satisfies the given formula.

Throws:

java.lang.IllegalArgumentException - if the formula does not correspond to the expected language.

satisfies

public boolean satisfies(PclBeliefSet beliefBase)
                  throws java.lang.IllegalArgumentException

Description copied from interface: Interpretation

Checks whether this interpretation satisfies the given knowledge base.

Specified by:

satisfies in interface Interpretation<PclBeliefSet,ProbabilisticConditional>

Parameters:

beliefBase - a knowledge base.

Returns:

"true" if this interpretation satisfies the given knowledge base.

Throws:

java.lang.IllegalArgumentException - IllegalArgumentException if the knowledgebase does not correspond to the expected language.

probability

public Probability probability(Interpretation<PlBeliefSet,PropositionalFormula> w)
                        throws java.lang.IllegalArgumentException

Gets the probability of the given Herbrand interpretation (this is just an alias for get(Object o).

Parameters:

w - a Herbrand interpretation.

Returns:

the probability of the given Herbrand interpretation.

Throws:

java.lang.IllegalArgumentException

probability

public Probability probability(PropositionalFormula f)

Returns the probability of the given formula

Parameters:

f - a formula

Returns:

a probability.

conditionalProbability

public Probability conditionalProbability(Conditional c)

Returns the probability of the given conditional

Parameters:

c - a conditional

Returns:

a probability.

normalize

public static void normalize(java.util.List<java.lang.Double> probabilities)

Normalizes the given list of probabilities, i.e. divides each probability by the sum of all probabilities.

entropy

public double entropy()

Returns the entropy of this probability distribution.

Returns:

the entropy of this probability distribution.

convexCombination

public ProbabilityDistribution<T> convexCombination(double d,
                                                    ProbabilityDistribution<T> other)

Computes the convex combination of this P1 and the given probability distribution P2 with parameter d, i.e. it returns a P with P(i)=d P1(i) + (1-d) P2(i) for every interpretation i.

Parameters:

d - a double

other - a probability distribution

Returns:

the convex combination of this P1 and the given probability distribution P2 with parameter d.

Throws:

java.lang.IllegalArgumentException - if either d is not in [0,1] or this and the given probability distribution are not defined on the same set of interpretations.

linearCombination

public ProbabilityDistribution<T> linearCombination(double d1,
                                                    double d2,
                                                    ProbabilityDistribution<T> other)

Makes a linear combination of this distribution "p1" and the given distribution "other" and the given parameters, i.e. it returns a P with P(i)=d1 P1(i) + d2 P2(i) for every interpretation i. NOTE: P is normalized after combination.

Parameters:

d1 - a double.

d2 - a double.

other - a probability distribution.

Returns:

a probability distribution.

convexCombination

public static <S extends Interpretation<PlBeliefSet,PropositionalFormula>> ProbabilityDistribution<S> convexCombination(double[] factors,
                                                                                                                        ProbabilityDistribution<S>[] creators)
                                                                                                                 throws java.lang.IllegalArgumentException

Computes the convex combination of the given probability distributions P1,...,PN with parameters factors, i.e. it returns a P with P(i)=d1 P1(i) + d2 P2(i)+ ... + dN PN(i) for every interpretation i (with d1,...,dN=factors).

Type Parameters:

S - The interpretation class

Parameters:

factors - a vector of doubles.

creators - a vector of probability distributions.

Returns:

the convex combination of the given distributions with parameters factors.

Throws:

java.lang.IllegalArgumentException - if either the sum of factors d is not in 1, or this and the given probability distributions are not defined on the same set of interpretations, or the lengths of creators and factors differ.

getUniformDistribution

public static <S extends Interpretation<PlBeliefSet,PropositionalFormula>> ProbabilityDistribution<S> getUniformDistribution(java.util.Set<S> interpretations,
                                                                                                                             Signature sig)

Returns the uniform distribution on the given interpretations.

Type Parameters:

S - The interpretation class

Parameters:

interpretations - some interpretations.

sig - a signature

Returns:

the uniform distribution on the given interpretations.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

clear

public void clear()

Specified by:

clear in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

containsKey

public boolean containsKey(java.lang.Object key)

Specified by:

containsKey in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

containsValue

public boolean containsValue(java.lang.Object value)

Specified by:

containsValue in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

entrySet

public java.util.Set<java.util.Map.Entry<T,Probability>> entrySet()

Specified by:

entrySet in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

get

public Probability get(java.lang.Object key)

Specified by:

get in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

isEmpty

public boolean isEmpty()

Specified by:

isEmpty in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

put

public Probability put(T key,
                       Probability value)

Specified by:

put in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

putAll

public void putAll(java.util.Map<? extends T,? extends Probability> m)

Specified by:

putAll in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

remove

public Probability remove(java.lang.Object key)

Specified by:

remove in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

size

public int size()

Specified by:

size in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

values

public java.util.Collection<Probability> values()

Specified by:

values in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>

keySet

public java.util.Set<T> keySet()

Specified by:

keySet in interface java.util.Map<T extends Interpretation<PlBeliefSet,PropositionalFormula>,Probability>