Package org.tweetyproject.math.probability

Class ProbabilityFunction<T extends Comparable<T>>

java.lang.Object

org.tweetyproject.math.probability.ProbabilityFunction<T>

Type Parameters:

T - The class of the objects used.

All Implemented Interfaces:

Map<T,Probability>

Direct Known Subclasses:

ProbabilisticExtension, SubgraphProbabilityFunction

public class ProbabilityFunction<T extends Comparable<T>>
extends Object
implements Map<T,Probability>

This class represents a probability distribution over some set of objects

Author:

Matthias Thimm

Nested Class Summary

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

Map.Entry<K,V>

Constructor Summary

Constructors

Constructor	Description
ProbabilityFunction()	Creates a new probability function.
ProbabilityFunction(ProbabilityFunction<T> other)	Creates a new probability function by copying the given one.

Method Summary

Modifier and Type	Method	Description
void	clear()
boolean	containsKey(Object key)
boolean	containsValue(Object value)
static <S extends Comparable<S>> ProbabilityFunction<S>	convexCombination(double[] factors, ProbabilityFunction<S>[] creators)	Computes the convex combination of the given probability distributions P1,...,PN with parameters factors, i.e.
ProbabilityFunction<T>	convexCombination(double d, ProbabilityFunction<T> other)	Computes the convex combination of this P1 and the given probability distribution P2 with parameter d, i.e.
Set<Map.Entry<T,Probability>>	entrySet()
boolean	equals(Object obj)
Probability	get(Object key)
Vector<Probability>	getProbabilityVector()	Returns the vector of probabilities, depending on the order of the domain elements (which can be ordered as they implement Comparable).
Vector<Double>	getProbabilityVectorAsDoubles()	Returns the vector of probabilities, depending on the order of the domain elements (which can be ordered as they implement Comparable).
static <S extends Comparable<S>> ProbabilityFunction<S>	getUniformDistribution(Set<S> objects)	Returns the uniform distribution on the given interpretations.
int	hashCode()
boolean	isEmpty()
boolean	isNormalized()	Checks whether this probability function is normalized, i.e.
Set<T>	keySet()
ProbabilityFunction<T>	linearCombination(double d1, double d2, ProbabilityFunction<T> other)	Makes a linear combination of this distribution "p1" and the given distribution "other" and the given parameters, i.e.
void	normalize()	Normalizes this probability function to have mass 1.
Probability	probability(Collection<? extends T> objects)	Gets the probability of the given object.
Probability	probability(T w)	Gets the probability of the given object.
Probability	put(T key, Probability value)
void	putAll(Map<? extends T,? extends Probability> m)
Probability	remove(Object key)
T	sample()	Samples one element from the domain of this probability function, depending on its probability.
T	sample(Random random)	Samples one element from the domain of this probability function, depending on its probability.
int	size()
String	toString()
Collection<Probability>	values()

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface java.util.Map

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

Constructor Details

ProbabilityFunction

public ProbabilityFunction()

Creates a new probability function.

ProbabilityFunction

public ProbabilityFunction(ProbabilityFunction<T> other)

Creates a new probability function by copying the given one.

Parameters:

other - another probability function

Method Details

probability

public Probability probability(T w)
                        throws IllegalArgumentException

Gets the probability of the given object.

Parameters:

w - some object.

Returns:

the probability of the given object.

Throws:

IllegalArgumentException - if the given object has no probability

probability

public Probability probability(Collection<? extends T> objects)
                        throws IllegalArgumentException

Gets the probability of the given object.

Parameters:

objects - some object.

Returns:

the probability of the given object.

Throws:

IllegalArgumentException - if the given object has no probability

isNormalized

public boolean isNormalized()

Checks whether this probability function is normalized, i.e. the sum of all probabilities is 1.

Returns:

"true" if this probability function is normalized.

normalize

public void normalize()

Normalizes this probability function to have mass 1.

convexCombination

public ProbabilityFunction<T> convexCombination(double d,
 ProbabilityFunction<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:

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 ProbabilityFunction<T> linearCombination(double d1,
 double d2,
 ProbabilityFunction<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 Comparable<S>>
ProbabilityFunction<S> convexCombination(double[] factors,
 ProbabilityFunction<S>[] creators)
                                  throws 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 object i (with d1,...,dN=factors).

Type Parameters:

S - The object 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:

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 objects, or the lengths of creators and factors differ.

getUniformDistribution

public static <S extends Comparable<S>>
ProbabilityFunction<S> getUniformDistribution(Set<S> objects)

Returns the uniform distribution on the given interpretations.

Type Parameters:

S - The interpretation class

Parameters:

objects - set of interpretations of type S.

Returns:

the uniform distribution on the given interpretations.

sample

public T sample()

Samples one element from the domain of this probability function, depending on its probability.

Returns:

a sample from this probability function.

sample

public T sample(Random random)

Samples one element from the domain of this probability function, depending on its probability.

Parameters:

random - the number generator used.

Returns:

a sample from this probability function.

toString

public String toString()

Overrides:

toString in class Object

clear

public void clear()

Specified by:

clear in interface Map<T extends Comparable<T>,Probability>

containsKey

public boolean containsKey(Object key)

Specified by:

containsKey in interface Map<T extends Comparable<T>,Probability>

containsValue

public boolean containsValue(Object value)

Specified by:

containsValue in interface Map<T extends Comparable<T>,Probability>

entrySet

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

Specified by:

entrySet in interface Map<T extends Comparable<T>,Probability>

get

public Probability get(Object key)

Specified by:

get in interface Map<T extends Comparable<T>,Probability>

isEmpty

public boolean isEmpty()

Specified by:

isEmpty in interface Map<T extends Comparable<T>,Probability>

put

public Probability put(T key,
 Probability value)

Specified by:

put in interface Map<T extends Comparable<T>,Probability>

putAll

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

Specified by:

putAll in interface Map<T extends Comparable<T>,Probability>

remove

public Probability remove(Object key)

Specified by:

remove in interface Map<T extends Comparable<T>,Probability>

size

public int size()

Specified by:

size in interface Map<T extends Comparable<T>,Probability>

values

public Collection<Probability> values()

Specified by:

values in interface Map<T extends Comparable<T>,Probability>

keySet

public Set<T> keySet()

Specified by:

keySet in interface Map<T extends Comparable<T>,Probability>

hashCode

public int hashCode()

Specified by:

hashCode in interface Map<T extends Comparable<T>,Probability>

Overrides:

hashCode in class Object

getProbabilityVector

public Vector<Probability> getProbabilityVector()

Returns the vector of probabilities, depending on the order of the domain elements (which can be ordered as they implement Comparable).

Returns:

the vector of probabilities

getProbabilityVectorAsDoubles

public Vector<Double> getProbabilityVectorAsDoubles()

Returns the vector of probabilities, depending on the order of the domain elements (which can be ordered as they implement Comparable).

Returns:

the vector of probabilities as doubles

equals

public boolean equals(Object obj)

Specified by:

equals in interface Map<T extends Comparable<T>,Probability>

Overrides:

equals in class Object