Class DoublePlusVmpOp

Provides outgoing messages for Plus(Double, Double), given random arguments to the function.

Inheritance

Object

DoublePlusVmpOp

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(Factor), "Plus", new Type[]{typeof(double), typeof(double)})]
[Quality(QualityBand.Stable)]
public static class DoublePlusVmpOp

Methods

AAverageLogarithm(Gaussian, Gaussian)

VMP message to A.

Declaration

public static Gaussian AAverageLogarithm(Gaussian Sum, Gaussian b)

Parameters

Type	Name	Description
Gaussian	Sum	Incoming message from Sum. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	b	Incoming message from B. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the A argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except A. Because the factor is deterministic, Sum is integrated out before taking the logarithm. The formula is exp(sum_(B) p(B) log(sum_Sum p(Sum) factor(Sum,A,B))).

Exceptions

Type	Condition
ImproperMessageException	Sum is not a proper distribution.
ImproperMessageException	b is not a proper distribution.

AAverageLogarithm(Gaussian, Gaussian, Gaussian, Gaussian, Gaussian, Gaussian, Gaussian)

VMP message to A.

Declaration

public static Gaussian AAverageLogarithm(Gaussian Sum, Gaussian a, Gaussian a_deriv, Gaussian to_a, Gaussian b, Gaussian b_deriv, Gaussian to_b)

Parameters

Type	Name	Description
Gaussian	Sum	Incoming message from Sum. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	a	Incoming message from A.
Gaussian	a_deriv
Gaussian	to_a	Previous outgoing message to a.
Gaussian	b	Incoming message from B. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	b_deriv
Gaussian	to_b	Previous outgoing message to b.

Returns

Type	Description
Gaussian	The outgoing VMP message to the A argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except A. Because the factor is deterministic, Sum is integrated out before taking the logarithm. The formula is exp(sum_(B) p(B) log(sum_Sum p(Sum) factor(Sum,A,B))).

Exceptions

Type	Condition
ImproperMessageException	Sum is not a proper distribution.
ImproperMessageException	b is not a proper distribution.

AAverageLogarithm(Gaussian, Double)

VMP message to A.

Declaration

public static Gaussian AAverageLogarithm(Gaussian Sum, double b)

Parameters

Type	Name	Description
Gaussian	Sum	Incoming message from Sum. Must be a proper distribution. If uniform, the result will be uniform.
Double	b	Constant value for B.

Returns

Type	Description
Gaussian	The outgoing VMP message to the A argument.

Remarks

The outgoing message is the factor viewed as a function of A with Sum integrated out. The formula is sum_Sum p(Sum) factor(Sum,A,B).

Exceptions

Type	Condition
ImproperMessageException	Sum is not a proper distribution.

AAverageLogarithm(Double, Gaussian)

VMP message to A.

Declaration

[NotSupported("Variational Message Passing does not support a Plus factor with fixed output and two random inputs.")]
public static Gaussian AAverageLogarithm(double Sum, Gaussian b)

Parameters

Type	Name	Description
Double	Sum	Constant value for Sum.
Gaussian	b	Incoming message from B. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the A argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except A. The formula is exp(sum_(B) p(B) log(factor(Sum,A,B))).

Exceptions

Type	Condition
ImproperMessageException	b is not a proper distribution.

AAverageLogarithm(Double, Double)

VMP message to A.

Declaration

public static Gaussian AAverageLogarithm(double Sum, double b)

Parameters

Type	Name	Description
Double	Sum	Constant value for Sum.
Double	b	Constant value for B.

Returns

Type	Description
Gaussian	The outgoing VMP message to the A argument.

Remarks

The outgoing message is the factor viewed as a function of A conditioned on the given values.

AverageLogFactor(Gaussian)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(Gaussian sum)

Parameters

Type	Name	Description
Gaussian	sum	Incoming message from Sum.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Gaussian)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sum, Gaussian a)

Parameters

Type	Name	Description
Double	sum	Constant value for Sum.
Gaussian	a	Incoming message from A.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Double, Gaussian)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sum, double a, Gaussian b)

Parameters

Type	Name	Description
Double	sum	Constant value for Sum.
Double	a	Constant value for A.
Gaussian	b	Incoming message from B.

Returns

Type	Description
Double	Zero.

Remarks

In Variational Message Passing, the evidence contribution of a deterministic factor is zero. Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

AverageLogFactor(Double, Double, Double)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(double sum, double a, double b)

Parameters

Type	Name	Description
Double	sum	Constant value for Sum.
Double	a	Constant value for A.
Double	b	Constant value for B.

Returns

Type	Description
Double	Zero.

Remarks

The formula for the result is log(factor(Sum,A,B)). Adding up these values across all factors and variables gives the log-evidence estimate for VMP.

BAverageLogarithm(Gaussian, Gaussian)

VMP message to B.

Declaration

public static Gaussian BAverageLogarithm(Gaussian Sum, Gaussian a)

Parameters

Type	Name	Description
Gaussian	Sum	Incoming message from Sum. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	a	Incoming message from A. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the B argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except B. Because the factor is deterministic, Sum is integrated out before taking the logarithm. The formula is exp(sum_(A) p(A) log(sum_Sum p(Sum) factor(Sum,A,B))).

Exceptions

Type	Condition
ImproperMessageException	Sum is not a proper distribution.
ImproperMessageException	a is not a proper distribution.

BAverageLogarithm(Gaussian, Double)

VMP message to B.

Declaration

public static Gaussian BAverageLogarithm(Gaussian Sum, double a)

Parameters

Type	Name	Description
Gaussian	Sum	Incoming message from Sum. Must be a proper distribution. If uniform, the result will be uniform.
Double	a	Constant value for A.

Returns

Type	Description
Gaussian	The outgoing VMP message to the B argument.

Remarks

The outgoing message is the factor viewed as a function of B with Sum integrated out. The formula is sum_Sum p(Sum) factor(Sum,A,B).

Exceptions

Type	Condition
ImproperMessageException	Sum is not a proper distribution.

BAverageLogarithm(Double, Gaussian)

VMP message to B.

Declaration

[NotSupported("Variational Message Passing does not support a Plus factor with fixed output and two random inputs.")]
public static Gaussian BAverageLogarithm(double Sum, Gaussian a)

Parameters

Type	Name	Description
Double	Sum	Constant value for Sum.
Gaussian	a	Incoming message from A. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the B argument.

Remarks

The outgoing message is the exponential of the average log-factor value, where the average is over all arguments except B. The formula is exp(sum_(A) p(A) log(factor(Sum,A,B))).

Exceptions

Type	Condition
ImproperMessageException	a is not a proper distribution.

BAverageLogarithm(Double, Double)

VMP message to B.

Declaration

public static Gaussian BAverageLogarithm(double Sum, double a)

Parameters

Type	Name	Description
Double	Sum	Constant value for Sum.
Double	a	Constant value for A.

Returns

Type	Description
Gaussian	The outgoing VMP message to the B argument.

Remarks

The outgoing message is the factor viewed as a function of B conditioned on the given values.

SumAverageLogarithm(Gaussian, Gaussian)

VMP message to Sum.

Declaration

public static Gaussian SumAverageLogarithm(Gaussian a, Gaussian b)

Parameters

Type	Name	Description
Gaussian	a	Incoming message from A. Must be a proper distribution. If uniform, the result will be uniform.
Gaussian	b	Incoming message from B. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the Sum argument.

Remarks

The outgoing message is a distribution matching the moments of Sum as the random arguments are varied. The formula is proj[sum_(A,B) p(A,B) factor(Sum,A,B)].

Exceptions

Type	Condition
ImproperMessageException	a is not a proper distribution.
ImproperMessageException	b is not a proper distribution.

SumAverageLogarithm(Gaussian, Double)

VMP message to Sum.

Declaration

public static Gaussian SumAverageLogarithm(Gaussian a, double b)

Parameters

Type	Name	Description
Gaussian	a	Incoming message from A. Must be a proper distribution. If uniform, the result will be uniform.
Double	b	Constant value for B.

Returns

Type	Description
Gaussian	The outgoing VMP message to the Sum argument.

Remarks

The outgoing message is a distribution matching the moments of Sum as the random arguments are varied. The formula is proj[sum_(A) p(A) factor(Sum,A,B)].

Exceptions

Type	Condition
ImproperMessageException	a is not a proper distribution.

SumAverageLogarithm(Double, Gaussian)

VMP message to Sum.

Declaration

public static Gaussian SumAverageLogarithm(double a, Gaussian b)

Parameters

Type	Name	Description
Double	a	Constant value for A.
Gaussian	b	Incoming message from B. Must be a proper distribution. If uniform, the result will be uniform.

Returns

Type	Description
Gaussian	The outgoing VMP message to the Sum argument.

Remarks

The outgoing message is a distribution matching the moments of Sum as the random arguments are varied. The formula is proj[sum_(B) p(B) factor(Sum,A,B)].

Exceptions

Type	Condition
ImproperMessageException	b is not a proper distribution.

SumAverageLogarithm(Double, Double)

VMP message to Sum.

Declaration

public static Gaussian SumAverageLogarithm(double a, double b)

Parameters

Type	Name	Description
Double	a	Constant value for A.
Double	b	Constant value for B.

Returns

Type	Description
Gaussian	The outgoing VMP message to the Sum argument.

Remarks

The outgoing message is the factor viewed as a function of Sum conditioned on the given values.

SumDeriv(Gaussian, Gaussian, Gaussian, Gaussian, Gaussian, Gaussian, Gaussian)

Declaration

public static Gaussian SumDeriv(Gaussian Sum, Gaussian a, Gaussian a_deriv, Gaussian to_a, Gaussian b, Gaussian b_deriv, Gaussian to_b)

Parameters

Type	Name	Description
Gaussian	Sum
Gaussian	a
Gaussian	a_deriv
Gaussian	to_a
Gaussian	b
Gaussian	b_deriv
Gaussian	to_b

Returns

Type	Description
Gaussian

SumDeriv(Gaussian, Double)

Declaration

public static Gaussian SumDeriv(Gaussian a, double b)

Parameters

Type	Name	Description
Gaussian	a
Double	b

Returns

Type	Description
Gaussian

SumDeriv(Double, Gaussian)

Declaration

public static Gaussian SumDeriv(double a, Gaussian b)

Parameters

Type	Name	Description
Double	a
Gaussian	b

Returns

Type	Description
Gaussian