Class BeliefPropagationGateEnterOp

Provides outgoing messages for the following factors:

, given random arguments to the function.

Inheritance

Object

BeliefPropagationGateEnterOp

Inherited Members

Object.Equals(Object)

Object.Equals(Object, Object)

Object.GetHashCode()

Object.GetType()

Object.MemberwiseClone()

Object.ReferenceEquals(Object, Object)

Object.ToString()

Namespace: Microsoft.ML.Probabilistic.Factors

Assembly: Microsoft.ML.Probabilistic.dll

Syntax

[FactorMethod(typeof(Gate), "Enter<>", new Type[]{null, typeof(bool), null})]
[FactorMethod(typeof(Gate), "Enter<>", new Type[]{null, typeof(int), null})]
[Quality(QualityBand.Stable)]
public static class BeliefPropagationGateEnterOp

Remarks

The message operators contained in this class assume that the distribution of the variable entering the gate can represent mixtures exactly.

Methods

ValueAverageConditional<TDist>(IList<TDist>, Discrete, TDist, TDist)

EP message to value.

Declaration

public static TDist ValueAverageConditional<TDist>([SkipIfAllUniform] IList<TDist> enter, Discrete selector, TDist value, TDist result)
    where TDist : SettableTo<TDist>, SettableToWeightedSum<TDist>, CanGetLogAverageOf<TDist>

Parameters

Type	Name	Description
IList<TDist>	enter	Incoming message from `enter`. Must be a proper distribution. If all elements are uniform, the result will be uniform.
Discrete	selector	Incoming message from `selector`.
TDist	value	Incoming message from `value`.
TDist	result	Modified to contain the outgoing message.

Returns

Type	Description
TDist	`result`

Type Parameters

Name	Description
TDist	The type of the distribution over the variable entering the gate.

Remarks

The outgoing message is a distribution matching the moments of value as the random arguments are varied. The formula is proj[p(value) sum_(enter,selector) p(enter,selector) factor(enter,selector,value)]/p(value).

Exceptions

Type	Condition
ImproperMessageException	`enter` is not a proper distribution.