io.improbable.keanu.vertices.intgr.probabilistic

Class GeometricVertex

java.lang.Object

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

io.improbable.keanu.vertices.intgr.IntegerVertex

io.improbable.keanu.vertices.intgr.probabilistic.GeometricVertex

All Implemented Interfaces:

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

public class GeometricVertex
extends IntegerVertex
implements ProbabilisticInteger, SamplableWithManyScalars<IntegerTensor>, LogProbGraphSupplier

Constructor Summary

Constructors

Constructor and Description
GeometricVertex(double p)
GeometricVertex(DoubleVertex p)
GeometricVertex(long[] tensorShape, double p)
GeometricVertex(long[] tensorShape, DoubleVertex p) A Vertex representing a Geometrically distributed random variable.

Method Summary

Modifier and Type	Method and Description
java.util.Map<Vertex,DoubleTensor>	dLogProb(IntegerTensor atValue, java.util.Set<? extends Vertex> withRespectTo) The partial derivatives of the natural log prob.
DoubleVertex	getP()
double	logProb(IntegerTensor value) This is the natural log of the probability at the supplied value.
LogProbGraph	logProbGraph()
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

GeometricVertex

public GeometricVertex(long[] tensorShape,
                       DoubleVertex p)

A Vertex representing a Geometrically distributed random variable.

The Keanu Implementation has a support of {1, 2, 3, ...} ie it produces the number of tests until success (not the number of failures until success which has a support {0, 1, 2, ...}

If all provided parameters are scalar then the proposed shape determines the shape

Parameters:

tensorShape - the desired shape of the tensor in this vertex

p - the probability that an individual test is a success

GeometricVertex

public GeometricVertex(long[] tensorShape,
                       double p)

GeometricVertex

public GeometricVertex(DoubleVertex p)

GeometricVertex

public GeometricVertex(double p)

Method Detail

sampleWithShape

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

Specified by:

sampleWithShape in interface SamplableWithShape<IntegerTensor>

logProb

public double logProb(IntegerTensor value)

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:

value - 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).

logProbGraph

public LogProbGraph logProbGraph()

Specified by:

logProbGraph in interface LogProbGraphSupplier

dLogProb

public java.util.Map<Vertex,DoubleTensor> dLogProb(IntegerTensor atValue,
                                                   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:

atValue - 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).

getP

public DoubleVertex getP()