Class GetItemsFromJaggedPointOp<T>

Provides outgoing messages for GetItemsFromJagged<T>(IReadOnlyList<IReadOnlyList<T>>, IReadOnlyList<Int32>, IReadOnlyList<Int32>), given random arguments to the function.

Inheritance

Object

GetItemsFromJaggedPointOp<T>

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(Collection), "GetItemsFromJagged<>", new Type[]{}, Default = false)]
[Quality(QualityBand.Experimental)]
public static class GetItemsFromJaggedPointOp<T>

Type Parameters

Name	Description
T	The type of an item.

Methods

ItemsAverageConditional<DistributionArrayType, DistributionType>(IList<DistributionArrayType>, IList<Int32>, IList<Int32>, Int32, DistributionType)

EP message to items.

Declaration

public static DistributionType ItemsAverageConditional<DistributionArrayType, DistributionType>([SkipIfAllUniform] IList<DistributionArrayType> array, IList<int> indices, IList<int> indices2, int resultIndex, DistributionType result)
    where DistributionArrayType : IList<DistributionType> where DistributionType : SettableTo<DistributionType>

Parameters

Type	Name	Description
IList<DistributionArrayType>	array	Incoming message from array. Must be a proper distribution. If all elements are uniform, the result will be uniform.
IList<Int32>	indices	Incoming message from indices.
IList<Int32>	indices2	Incoming message from indices2.
Int32	resultIndex	Index of the items for which a message is desired.
DistributionType	result	Modified to contain the outgoing message.

Returns

Type	Description
DistributionType	result

Type Parameters

Name	Description
DistributionArrayType	The type of a distribution over array elements.
DistributionType	The type of a distribution over inner array elements.

Remarks

The outgoing message is a distribution matching the moments of items as the random arguments are varied. The formula is proj[p(items) sum_(array,indices,indices2) p(array,indices,indices2) factor(items,array,indices,indices2)]/p(items).

Exceptions

Type	Condition
ImproperMessageException	array is not a proper distribution.