[Serializable]
[Quality(QualityBand.Mature)]
[DataContract]
public class Discrete : IDistribution<int>, IDistribution, ICloneable, HasPoint<int>, CanGetLogProb<int>, SettableTo<Discrete>, SettableToProduct<Discrete>, SettableToProduct<Discrete, Discrete>, Diffable, SettableToUniform, SettableToPartialUniform<Discrete>, SettableToRatio<Discrete>, SettableToRatio<Discrete, Discrete>, SettableToPower<Discrete>, SettableToWeightedSumExact<Discrete>, SettableToWeightedSum<Discrete>, CanGetLogAverageOf<Discrete>, CanGetLogAverageOfPower<Discrete>, CanGetAverageLog<Discrete>, CanGetLogNormalizer, Sampleable<int>, CanGetMean<double>, CanGetVariance<double>, CanGetMode<int>

Remarks

The distribution is represented by a normalized Vector of length D. The Vector may be all zero to indicate an empty distribution such as the product of conflicting point masses. The probability of value x is available as this[x] or GetLogProb(x).

Constructors

Discrete(Discrete)

Copy constructor

Declaration

public Discrete(Discrete that)

Parameters

Type	Name	Description
Discrete	that	The discrete instance to copy

Discrete(Vector)

Creates a Discrete distribution from the given probabilities.

Declaration

[Construction(new string[]{"GetWorkspace"})]
public Discrete(Vector probs)

Parameters

Type	Name	Description
Vector	probs

Discrete(Double[])

Creates a Discrete distribution from the given probabilities.

Declaration

public Discrete(params double[] probs)

Parameters

Type	Name	Description
Double[]	probs

Discrete(Int32)

Creates a uniform Discrete distribution, from 0 to dimension-1.

Declaration

protected Discrete(int dimension)

Parameters

Type	Name	Description
Int32	dimension

Discrete(Int32, Sparsity)

Creates a uniform Discrete distribution with a specified sparsity, from 0 to dimension-1.

Declaration

protected Discrete(int dimension, Sparsity sparsity)

Parameters

Type	Name	Description
Int32	dimension	Dimension
Sparsity	sparsity	Sparsity

Fields

prob

Probability of each value (when not a point mass).

Declaration

[DataMember]
protected Vector prob

Field Value

Type	Description
Vector

Remarks

prob.Length == D. prob[i] >= 0. sum_i prob[i] = 1.

Properties

Dimension

Gets the dimension of this discrete distribution

Declaration

public int Dimension { get; }

Property Value

Type	Description
Int32

IsPointMass

Indicates whether or not this instance is a point mass.

Declaration

[IgnoreDataMember]
public bool IsPointMass { get; }

Property Value

Type	Description
Boolean

Item[Int32]

Gets or sets the probability at the given index.

Declaration

public double this[int index] { get; }

Parameters

Type	Name	Description
Int32	index

Property Value

Type	Description
Double

Point

Sets/gets this distribution as a point distribution

Declaration

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

Property Value

Type	Description
Int32

Sparsity

Gets the Sparsity specification of this Distribution.

Declaration

public Sparsity Sparsity { get; }

Property Value

Type	Description
Sparsity

Methods

Clone()

Clones this 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 Discrete type

Equals(Object)

Override of the Equals method

Declaration

public override bool Equals(object that)

Parameters

Type	Name	Description
Object	that	The instance to compare to

Returns

Type	Description
Boolean	True if the two distributions are the same in value, false otherwise

Overrides

Object.Equals(Object)

Evaluate(Int32)

Evaluates the density 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 density

GetAverageLog(Discrete)

The expected logarithm of that distribution under this distribution.

Declaration

public double GetAverageLog(Discrete that)

Parameters

Type	Name	Description
Discrete	that	The distribution to take the logarithm of.

Returns

Type	Description
Double	`sum_x this.Evaluate(x)*Math.Log(that.Evaluate(x))`

Remarks

This is also known as the cross entropy.

GetHashCode()

Override of GetHashCode method

Declaration

public override int GetHashCode()

Returns

Type	Description
Int32	The hash code for this instance

Overrides

Object.GetHashCode()

GetLogAverageOf(Discrete)

The log of the integral of the product of this discrete and that discrete

Declaration

public double GetLogAverageOf(Discrete that)

Parameters

Type	Name	Description
Discrete	that	That discrete distribution

Returns

Type	Description
Double	The log inner product

GetLogAverageOfPower(Discrete, Double)

Get the integral of this distribution times another distribution raised to a power.

Declaration

public double GetLogAverageOfPower(Discrete that, double power)

Parameters

Type	Name	Description
Discrete	that
Double	power

Returns

Type	Description
Double

GetLogNormalizer()

Gets the log normalizer of the distribution

Declaration

public double GetLogNormalizer()

Returns

Type	Description
Double

GetLogProb(Int32)

Evaluates the log 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 density

GetLogProbs()

Gets the vector of log probabilities for this distribution.

Declaration

public Vector GetLogProbs()

Returns

Type	Description
Vector

GetMean()

Gets the mean of the distribution

Declaration

public double GetMean()

Returns

Type	Description
Double

GetMedian()

Gets the median of the distribution

Declaration

public int GetMedian()

Returns

Type	Description
Int32	The median

GetMode()

Gets the mode of the distribution

Declaration

public int GetMode()

Returns

Type	Description
Int32

GetProbs()

Gets the probability at each index.

Declaration

public Vector GetProbs()

Returns

Type	Description
Vector	The vector of probabilities

GetProbs(Vector)

Gets the probability at each index.

Declaration

public Vector GetProbs(Vector result)

Parameters

Type	Name	Description
Vector	result	When used internally, can be the same object as prob.

Returns

Type	Description
Vector	result

GetVariance()

Gets the variance of the distribution

Declaration

public double GetVariance()

Returns

Type	Description
Double

GetWorkspace()

Gets a Vector of size this.Dimension.

Declaration

public Vector GetWorkspace()

Returns

Type	Description
Vector	A pointer to the internal probs Vector of the object.

Remarks

This function is intended to be used with SetProbs, 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 SetProbs is called, the distribution object is invalid once this workspace is modified.

IsPartialUniform()

Checks whether the distribution is uniform over its support.

Declaration

public bool IsPartialUniform()

Returns

Type	Description
Boolean	True if the distribution is uniform over its support, false otherwise.

IsUniform()

Returns whether the discrete distribution is uniform or not

Declaration

public bool IsUniform()

Returns

Type	Description
Boolean	True if uniform

IsZero()

Declaration

public bool IsZero()

Returns

Type	Description
Boolean

MaxDiff(Object)

Gets 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

Normalize()

Normalizes this distribution - i.e. sets the probabilities to sum to 1. This is called internally after product operations, sum operations etc.

Declaration

protected double Normalize()

Returns

Type	Description
Double	The normalizing factor

PointMass(Int32, Int32)

Creates a Discrete distribution which allows only one value.

Declaration

[Construction(new string[]{"Point", "Dimension"}, UseWhen = "IsPointMass")]
public static Discrete PointMass(int value, int numValues)

Parameters

Type	Name	Description
Int32	value	The allowed value.
Int32	numValues	The number of values in the domain.

Returns

Type	Description
Discrete

ProbEqual(Discrete)

The integral of the product between this discrete and that discrete. This is the probability that samples from this instance and that instance are equal

Declaration

public double ProbEqual(Discrete that)

Parameters

Type	Name	Description
Discrete	that	That discrete distribution

Returns

Type	Description
Double	The inner product

Sample()

Returns a sample from this discrete distribution

Declaration

public int Sample()

Returns

Type	Description
Int32	The sample value

Sample(Vector)

Returns a sample from a discrete distribution with the specified probabilities

Declaration

public static int Sample(Vector probs)

Parameters

Type	Name	Description
Vector	probs	The parameters of the discrete distribution

Returns

Type	Description
Int32	The sample value

Sample(Int32)

Returns a sample from this discrete distribution

Declaration

public int Sample(int result)

Parameters

Type	Name	Description
Int32	result	This parameter is ignored and is only present to support the Sampleable interface

Returns

Type	Description
Int32	The sample value

SetProbs(Vector)

Sets the probability of each index.

Declaration

public void SetProbs(Vector probs)

Parameters

Type	Name	Description
Vector	probs	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.

SetTo(Discrete)

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

Declaration

public void SetTo(Discrete value)

Parameters

Type	Name	Description
Discrete	value	That instance

SetToPadded(Discrete)

Set this distribution to match the given distribution, but possibly over a larger domain

Declaration

public void SetToPadded(Discrete value)

Parameters

Type	Name	Description
Discrete	value

SetToPartialUniform()

Sets the distribution to be uniform over its support.

Declaration

public void SetToPartialUniform()

SetToPartialUniformOf(Discrete)

Sets the distribution to be uniform over the support of a given distribution.

Declaration

public void SetToPartialUniformOf(Discrete dist)

Parameters

Type	Name	Description
Discrete	dist	The distribution which support will be used to setup the current distribution.

SetToPower(Discrete, Double)

Sets the parameters to represent the power of a discrete distributions.

Declaration

public void SetToPower(Discrete dist, double exponent)

Parameters

Type	Name	Description
Discrete	dist	The discrete distribution
Double	exponent	The exponent

SetToProduct(Discrete, Discrete)

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

Declaration

public void SetToProduct(Discrete a, Discrete b)

Parameters

Type	Name	Description
Discrete	a	The first discrete distribution
Discrete	b	The second discrete distribution

SetToRatio(Discrete, Discrete, Boolean)

Declaration

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

Parameters

Type	Name	Description
Discrete	numerator
Discrete	denominator
Boolean	forceProper

SetToSum(Double, Discrete, Double, Discrete)

Sets the parameters to represent the weighted sum of two discrete distributions.

Declaration

public void SetToSum(double weight1, Discrete dist1, double weight2, Discrete dist2)

Parameters

Type	Name	Description
Double	weight1	The first weight
Discrete	dist1	The first discrete distribution. Can be the same object as `this`
Double	weight2	The second weight
Discrete	dist2	The second discrete distribution. Cannot be the same object as `this`

SetToUniform()

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

Declaration

public void SetToUniform()

ToString()

Override of ToString method

Declaration

public override string ToString()

Returns

Type	Description
String	String representation of this instance

Overrides

Object.ToString()

ToString(String)

Declaration

public virtual string ToString(string format)

Parameters

Type	Name	Description
String	format

Returns

Type	Description
String

ToString(String, String)

Declaration

public virtual string ToString(string format, string delimiter)

Parameters

Type	Name	Description
String	format
String	delimiter

Returns

Type	Description
String

Uniform(Int32)

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

Declaration

public static Discrete Uniform(int numValues)

Parameters

Type	Name	Description
Int32	numValues

Returns

Type	Description
Discrete

Uniform(Int32, Sparsity)

Creates a uniform Discrete distribution with a specified sparsity over the values from 0 to numValues-1

Declaration

[Construction(new string[]{"Dimension", "Sparsity"}, UseWhen = "IsUniform")]
public static Discrete Uniform(int numValues, Sparsity sparsity)

Parameters

Type	Name	Description
Int32	numValues	Number of values
Sparsity	sparsity	Sparsity

Returns

Type	Description
Discrete

UniformInRange(Int32, Int32, Int32)

Creates a Discrete distribution which is uniform over values from start to end inclusive.

Declaration

public static Discrete UniformInRange(int numValues, int start, int end)

Parameters

Type	Name	Description
Int32	numValues	Number of values
Int32	start	The first value included in the distribution
Int32	end	The last value included in the distribution

Returns

Type	Description
Discrete	Discrete which is uniform over the specified range (and zero elsewhere).

UniformInRanges(Int32, IEnumerable<Int32>)

Creates a Discrete distribution which is uniform over values in multiple ranges specified by pairs of start and end values. These pairs are specified as adjacent values in an enumerable whose length must therefore be even.

Declaration

public static Discrete UniformInRanges(int numValues, IEnumerable<int> startEndPairs)

Parameters

Type	Name	Description
Int32	numValues	Number of values
IEnumerable<Int32>	startEndPairs	Sequence of start and end pairs

Returns

Type	Description
Discrete	Discrete which is uniform over the specified ranges (and zero elsewhere).

UniformInRanges(Int32, Int32[])

Creates a Discrete distribution which is uniform over values in multiple ranges specified by pairs of start and end values. These pairs are specified as adjacent values in an array whose length must therefore be even.

Declaration

public static Discrete UniformInRanges(int numValues, params int[] startEndPairs)

Parameters

Type	Name	Description
Int32	numValues	Number of values
Int32[]	startEndPairs	Sequence of start and end pairs

Returns

Type	Description
Discrete	Discrete which is uniform over the specified ranges (and zero elsewhere).

Zero(Int32)

Declaration

public static Discrete Zero(int numValues)

Parameters

Type	Name	Description
Int32	numValues

Returns

Type	Description
Discrete

Operators

Division(Discrete, Discrete)

Creates a Discrete distribution which is the ratio of two Discrete distributions

Declaration

public static Discrete operator /(Discrete numerator, Discrete denominator)

Parameters

Type	Name	Description
Discrete	numerator	The numerator distribution
Discrete	denominator	The denominator distribution

Returns

Type	Description
Discrete	The resulting Discrete distribution

ExclusiveOr(Discrete, Double)

Raises a distribution to a power.

Declaration

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

Parameters

Type	Name	Description
Discrete	dist	The distribution.
Double	exponent	The power to raise to.

Returns

Type	Description
Discrete	`dist` raised to power `exponent`.

Multiply(Discrete, Discrete)

Creates a Discrete distribution which is the product of two Discrete distributions

Declaration

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

Parameters

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

Returns

Type	Description
Discrete	The resulting Discrete distribution

Implements

IDistribution<T>

IDistribution

System.ICloneable

HasPoint<T>

CanGetLogProb<T>

SettableTo<T>

SettableToProduct<T>

SettableToProduct<T, U>

Diffable

SettableToUniform

SettableToPartialUniform<TDist>

SettableToRatio<T>

SettableToRatio<T, U>

SettableToPower<T>

SettableToWeightedSumExact<T>

SettableToWeightedSum<T>

CanGetLogAverageOf<T>

CanGetLogAverageOfPower<T>

CanGetAverageLog<T>

CanGetLogNormalizer

Sampleable<T>

CanGetMean<MeanType>

CanGetVariance<VarType>

CanGetMode<ModeType>