[Serializable]
[Quality(QualityBand.Experimental)]
[DataContract]
public class UnnormalizedDiscrete : IDistribution<int>, IDistribution, ICloneable, Diffable, SettableToUniform, HasPoint<int>, CanGetLogProb<int>, SettableTo<UnnormalizedDiscrete>, Sampleable<int>, SettableToProduct<UnnormalizedDiscrete>, SettableToProduct<UnnormalizedDiscrete, UnnormalizedDiscrete>, SettableToRatio<UnnormalizedDiscrete>, SettableToRatio<UnnormalizedDiscrete, UnnormalizedDiscrete>, SettableToPower<UnnormalizedDiscrete>, SettableToWeightedSum<UnnormalizedDiscrete>, CanGetLogAverageOf<UnnormalizedDiscrete>, CanGetAverageLog<UnnormalizedDiscrete>

Fields

logProb

Log probability of each value (when not a point mass). Since the distribution is unnormalized, these may be shifted by an arbitrary constant.

Declaration

[DataMember]
protected DenseVector logProb

Field Value

Type	Description
DenseVector

Remarks

logprob.Length == D.

Properties

Dimension

Dimension of the unnormalised discrete distribution

Declaration

[IgnoreDataMember]
public int Dimension { get; }

Property Value

Type	Description
Int32

IsPointMass

Whether or not this instance is a point mass.

Declaration

[IgnoreDataMember]
public bool IsPointMass { get; }

Property Value

Type	Description
Boolean

Point

Sets/gets this distribution as a point distribution

Declaration

[IgnoreDataMember]
public int Point { get; set; }

Property Value

Type	Description
Int32

Methods

Clone()

Clones this unnormalised discrete distribution.

Declaration

public object Clone()

Returns

Type	Description
Object	An object which is a clone of the current instance. This must be cast if you want to assign the result to a UnnormalizedDiscrete type

Evaluate(Int32)

Evaluates the unnormalized probability at the specified domain value

Declaration

public double Evaluate(int value)

Parameters

Type	Name	Description
Int32	value	The point at which to evaluate

Returns

Type	Description
Double	The unnormalized probability

FromDiscrete(Discrete)

Creates an unnormalized discrete distribution from a normal discrete distribution.

Declaration

public static UnnormalizedDiscrete FromDiscrete(Discrete d)

Parameters

Type	Name	Description
Discrete	d	The discrete distribution

Returns

Type	Description
UnnormalizedDiscrete

FromLogProbs(DenseVector)

Creates an unnormalized discrete distribution from a vector of log probabilities.

Declaration

public static UnnormalizedDiscrete FromLogProbs(DenseVector logProb)

Parameters

Type	Name	Description
DenseVector	logProb

Returns

Type	Description
UnnormalizedDiscrete

GetAverageLog(UnnormalizedDiscrete)

Declaration

public double GetAverageLog(UnnormalizedDiscrete that)

Parameters

Type	Name	Description
UnnormalizedDiscrete	that

Returns

Type	Description
Double

GetLogAverageOf(UnnormalizedDiscrete)

Declaration

public double GetLogAverageOf(UnnormalizedDiscrete that)

Parameters

Type	Name	Description
UnnormalizedDiscrete	that

Returns

Type	Description
Double

GetLogProb(Int32)

Evaluates the log of the unnormalized density at the specified domain value

Declaration

public double GetLogProb(int value)

Parameters

Type	Name	Description
Int32	value	The point at which to evaluate

Returns

Type	Description
Double	The log unnormalized density

GetProbs()

Gets the unnormalized probability vector for this distribution.

Declaration

public DenseVector GetProbs()

Returns

Type	Description
DenseVector

GetWorkspace()

Gets a Vector of size this.Dimension.

Declaration

public DenseVector GetWorkspace()

Returns

Type	Description
DenseVector	A pointer to the internal log prob Vector of the object.

Remarks

This function is intended to be used with SetLogProbs, to avoid allocating a new Vector. The return value should not be interpreted as a probs vector, but only a workspace filled with unknown data that can be overwritten. Until SetLogProbs is called, the distribution object is invalid once this workspace is modified.

IsUniform()

Returns whether the distribution is uniform or not

Declaration

public bool IsUniform()

Returns

Type	Description
Boolean	True if uniform

MaxDiff(Object)

The maximum difference between the parameters of this discrete and that discrete

Declaration

public double MaxDiff(object that)

Parameters

Type	Name	Description
Object	that	That discrete

Returns

Type	Description
Double	The maximum difference

Sample()

Declaration

public int Sample()

Returns

Type	Description
Int32

Sample(Int32)

Declaration

public int Sample(int result)

Parameters

Type	Name	Description
Int32	result

Returns

Type	Description
Int32

SetLogProbs(DenseVector)

Sets the log probability vector for this distribution.

Declaration

public void SetLogProbs(DenseVector logProbs)

Parameters

Type	Name	Description
DenseVector	logProbs	A vector of non-negative, finite numbers. Need not sum to 1.

Remarks

Instead of allocating your own Vector to pass to SetProbs, you can call GetWorkspace(), fill in the resulting Vector, and then pass it to SetProbs.

SetMaxToZero()

Rescales the unnormalised distribution, so that the max log prob is zero i.e. the max unnormalised prob is 1.

Declaration

public void SetMaxToZero()

SetTo(UnnormalizedDiscrete)

Sets the parameters of this instance to the parameters of that instance

Declaration

public void SetTo(UnnormalizedDiscrete value)

Parameters

Type	Name	Description
UnnormalizedDiscrete	value	That instance

SetToPower(UnnormalizedDiscrete, Double)

Declaration

public void SetToPower(UnnormalizedDiscrete dist, double exponent)

Parameters

Type	Name	Description
UnnormalizedDiscrete	dist
Double	exponent

SetToProduct(UnnormalizedDiscrete, UnnormalizedDiscrete)

Sets the parameters to represent the product of two unnormalized discrete distributions.

Declaration

public void SetToProduct(UnnormalizedDiscrete a, UnnormalizedDiscrete b)

Parameters

Type	Name	Description
UnnormalizedDiscrete	a	The first unnormalized discrete distribution
UnnormalizedDiscrete	b	The second unnormalized discrete distribution

SetToRatio(UnnormalizedDiscrete, UnnormalizedDiscrete, Boolean)

Sets the parameters to represent the ratio of two unnormalized discrete distributions.

Declaration

public void SetToRatio(UnnormalizedDiscrete numerator, UnnormalizedDiscrete denominator, bool forceProper = false)

Parameters

Type	Name	Description
UnnormalizedDiscrete	numerator	The first unnormalized discrete distribution
UnnormalizedDiscrete	denominator	The second unnormalized discrete distribution
Boolean	forceProper	Ignored

SetToSum(Double, UnnormalizedDiscrete, Double, UnnormalizedDiscrete)

Declaration

public void SetToSum(double weight1, UnnormalizedDiscrete value1, double weight2, UnnormalizedDiscrete value2)

Parameters

Type	Name	Description
Double	weight1
UnnormalizedDiscrete	value1
Double	weight2
UnnormalizedDiscrete	value2

SetToUniform()

Sets this instance to a uniform distribution (i.e. probabilities all equal)

Declaration

public void SetToUniform()

ToDiscrete()

Declaration

public Discrete ToDiscrete()

Returns

Type	Description
Discrete

ToString()

Override of ToString method

Declaration

public override string ToString()

Returns

Type	Description
String	String representation of this instance

Overrides

Object.ToString()

ToString(String)

Override of ToString method which allows custom number formatting

Declaration

public string ToString(string format)

Parameters

Type	Name	Description
String	format

Returns

Type	Description
String	String representation of this instance

Uniform(Int32)

Creates a uniform unnormalized discrete distribution over the values from 0 to numValues-1

Declaration

public static UnnormalizedDiscrete Uniform(int numValues)

Parameters

Type	Name	Description
Int32	numValues

Returns

Type	Description
UnnormalizedDiscrete

Operators

Division(UnnormalizedDiscrete, UnnormalizedDiscrete)

Creates an unnormalized discrete distribution which is the ratio of two unnormalized discrete distributions

Declaration

public static UnnormalizedDiscrete operator /(UnnormalizedDiscrete a, UnnormalizedDiscrete b)

Parameters

Type	Name	Description
UnnormalizedDiscrete	a	The first distribution
UnnormalizedDiscrete	b	The second distribution

Returns

Type	Description
UnnormalizedDiscrete	The resulting unnormalized discrete distribution

ExclusiveOr(UnnormalizedDiscrete, Double)

Declaration

public static UnnormalizedDiscrete operator ^(UnnormalizedDiscrete dist, double exponent)

Parameters

Type	Name	Description
UnnormalizedDiscrete	dist
Double	exponent

Returns

Type	Description
UnnormalizedDiscrete

Multiply(UnnormalizedDiscrete, UnnormalizedDiscrete)

Creates an unnormalized discrete distribution which is the product of two unnormalized discrete distributions

Declaration

public static UnnormalizedDiscrete operator *(UnnormalizedDiscrete a, UnnormalizedDiscrete b)

Parameters

Type	Name	Description
UnnormalizedDiscrete	a	The first distribution
UnnormalizedDiscrete	b	The second distribution

Returns

Type	Description
UnnormalizedDiscrete	The resulting unnormalized discrete distribution

Implements

IDistribution<T>

IDistribution

System.ICloneable

Diffable

SettableToUniform

HasPoint<T>

CanGetLogProb<T>

SettableTo<T>

Sampleable<T>

SettableToProduct<T>

SettableToProduct<T, U>

SettableToRatio<T>

SettableToRatio<T, U>

SettableToPower<T>

SettableToWeightedSum<T>

CanGetLogAverageOf<T>

CanGetAverageLog<T>