io.improbable.keanu.vertices.intgr.probabilistic

Class MultinomialVertex

java.lang.Object

io.improbable.keanu.vertices.Vertex<IntegerTensor>

io.improbable.keanu.vertices.intgr.IntegerVertex

io.improbable.keanu.vertices.intgr.probabilistic.MultinomialVertex

All Implemented Interfaces:

Variable<IntegerTensor,VertexState<IntegerTensor>>, HasShape, io.improbable.keanu.kotlin.IntegerOperators<IntegerVertex>, io.improbable.keanu.kotlin.NumberOperators<IntegerVertex>, ProbabilisticInteger, Observable<IntegerTensor>, Probabilistic<IntegerTensor>, Samplable<IntegerTensor>, SamplableWithManyScalars<IntegerTensor>, SamplableWithShape<IntegerTensor>

public class MultinomialVertex
extends IntegerVertex
implements ProbabilisticInteger, SamplableWithManyScalars<IntegerTensor>

Constructor Summary

Constructors

Constructor and Description
MultinomialVertex(int n, DoubleVertex p)
MultinomialVertex(IntegerVertex n, DoubleVertex p)
MultinomialVertex(long[] tensorShape, IntegerVertex n, DoubleVertex p)

Method Summary

Modifier and Type	Method and Description
java.util.Map<Vertex,DoubleTensor>	dLogProb(IntegerTensor value, java.util.Set<? extends Vertex> withRespectTo) The partial derivatives of the natural log prob.
IntegerVertex	getN()
DoubleVertex	getP()
double	logProb(IntegerTensor kTensor) This is the natural log of the probability at the supplied value.
IntegerTensor	sampleWithShape(long[] shape, KeanuRandom random)

Methods inherited from class io.improbable.keanu.vertices.intgr.IntegerVertex

abs, concat, div, div, divideBy, divideBy, divideBy, equalTo, getValue, greaterThan, greaterThanOrEqualTo, lambda, lambda, lessThan, lessThanOrEqualTo, loadValue, max, min, minus, minus, minus, multiply, multiply, multiply, notEqualTo, observe, observe, plus, plus, plus, pow, pow, reshape, reverseDiv, reverseMinus, saveValue, setAndCascade, setAndCascade, setValue, setValue, slice, sum, sum, take, times, times, toDouble, unaryMinus

Methods inherited from class io.improbable.keanu.vertices.Vertex

addChild, addParent, addParents, equals, eval, getChildren, getConnectedGraph, getDegree, getId, getIndentation, getLabel, getObservedValue, getParents, getRank, getReference, getShape, getState, getValue, hashCode, hasValue, isDifferentiable, isObserved, isProbabilistic, lazyEval, observe, observeOwnValue, print, print, removeLabel, save, setAndCascade, setLabel, setLabel, setParents, setParents, setState, setValue, toString, unobserve

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface io.improbable.keanu.vertices.intgr.probabilistic.ProbabilisticInteger

dLogPmf, dLogPmf, dLogPmf, logPmf, logPmf, logPmf

Methods inherited from interface io.improbable.keanu.vertices.Probabilistic

dLogProb, dLogProbAtValue, dLogProbAtValue, getValue, keepOnlyProbabilisticVertices, logProbAtValue

Methods inherited from interface io.improbable.keanu.vertices.Observable

getObservedValue, isObserved, observe, unobserve

Methods inherited from interface io.improbable.keanu.vertices.Samplable

sample, sample

Methods inherited from interface io.improbable.keanu.vertices.SamplableWithManyScalars

sample, sampleManyScalars, sampleManyScalars

Methods inherited from interface io.improbable.keanu.vertices.SamplableWithShape

sampleWithShape

Methods inherited from interface io.improbable.keanu.algorithms.variational.optimizer.HasShape

getShape

Constructor Detail

MultinomialVertex

public MultinomialVertex(long[] tensorShape,
                         IntegerVertex n,
                         DoubleVertex p)

MultinomialVertex

public MultinomialVertex(IntegerVertex n,
                         DoubleVertex p)

MultinomialVertex

public MultinomialVertex(int n,
                         DoubleVertex p)

Method Detail

logProb

public double logProb(IntegerTensor kTensor)

Description copied from interface: Probabilistic

This is the natural log of the probability at the supplied value. In the case of continuous vertices, this is actually the log of the density, which will differ from the probability by a constant.

Specified by:

logProb in interface Probabilistic<IntegerTensor>

Parameters:

kTensor - The supplied value.

Returns:

The natural log of the probability function at the supplied value. For continuous variables this is called the PDF (probability density function). For discrete variables this is called the PMF (probability mass function).

dLogProb

public java.util.Map<Vertex,DoubleTensor> dLogProb(IntegerTensor value,
                                                   java.util.Set<? extends Vertex> withRespectTo)

Description copied from interface: Probabilistic

The partial derivatives of the natural log prob.

Specified by:

dLogProb in interface Probabilistic<IntegerTensor>

Parameters:

value - at a given value

withRespectTo - list of parents to differentiate with respect to

Returns:

the partial derivatives of the log of the probability function at the supplied value. For continuous variables this is called the PDF (probability density function). For discrete variables this is called the PMF (probability mass function).

sampleWithShape

public IntegerTensor sampleWithShape(long[] shape,
                                     KeanuRandom random)

Specified by:

sampleWithShape in interface SamplableWithShape<IntegerTensor>

getP

public DoubleVertex getP()

getN

public IntegerVertex getN()