Class BooleanAndOp

Provides outgoing messages for And(Boolean, Boolean), given random arguments to the function.

Inheritance

Object

BooleanAndOp

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), "And", new Type[]{})]
[Quality(QualityBand.Mature)]
public static class BooleanAndOp

Methods

AAverageConditional(Bernoulli, Bernoulli)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(Bernoulli and, Bernoulli B)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing EP message to the a argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

AAverageConditional(Bernoulli, Boolean)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(Bernoulli and, bool B)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the a argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

AAverageConditional(Boolean, Bernoulli)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(bool and, Bernoulli B)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the a argument.

Remarks

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

AAverageConditional(Boolean, Boolean)

EP message to a.

Declaration

public static Bernoulli AAverageConditional(bool and, bool B)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the a argument.

Remarks

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

AAverageLogarithm(Bernoulli, Bernoulli)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(Bernoulli and, Bernoulli B)

Parameters

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

Returns

Type	Description
Bernoulli	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, and is integrated out before taking the logarithm. The formula is exp(sum_(b) p(b) log(sum_and p(and) factor(and,a,b))).

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

AAverageLogarithm(Bernoulli, Boolean)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(Bernoulli and, bool B)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the a argument.

Remarks

The outgoing message is the factor viewed as a function of a with and integrated out. The formula is sum_and p(and) factor(and,a,b).

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

AAverageLogarithm(Boolean, Bernoulli)

VMP message to a.

Declaration

[NotSupported("Variational Message Passing does not support an And factor with fixed output.")]
public static Bernoulli AAverageLogarithm(bool and, Bernoulli B)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	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(and,a,b))).

AAverageLogarithm(Boolean, Boolean)

VMP message to a.

Declaration

public static Bernoulli AAverageLogarithm(bool and, bool B)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	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.

AndAverageConditional(Bernoulli, Bernoulli)

EP message to and.

Declaration

public static Bernoulli AndAverageConditional(Bernoulli A, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from a.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the and argument.

Remarks

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

AndAverageConditional(Bernoulli, Boolean)

EP message to and.

Declaration

public static Bernoulli AndAverageConditional(Bernoulli A, bool B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from a.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the and argument.

Remarks

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

AndAverageConditional(Boolean, Bernoulli)

EP message to and.

Declaration

public static Bernoulli AndAverageConditional(bool A, Bernoulli B)

Parameters

Type	Name	Description
Boolean	A	Constant value for a.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing EP message to the and argument.

Remarks

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

AndAverageLogarithm(Bernoulli, Bernoulli)

VMP message to and.

Declaration

public static Bernoulli AndAverageLogarithm(Bernoulli A, Bernoulli B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from a.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the and argument.

Remarks

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

AndAverageLogarithm(Bernoulli, Boolean)

VMP message to and.

Declaration

public static Bernoulli AndAverageLogarithm(Bernoulli A, bool B)

Parameters

Type	Name	Description
Bernoulli	A	Incoming message from a.
Boolean	B	Constant value for b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the and argument.

Remarks

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

AndAverageLogarithm(Boolean, Bernoulli)

VMP message to and.

Declaration

public static Bernoulli AndAverageLogarithm(bool A, Bernoulli B)

Parameters

Type	Name	Description
Boolean	A	Constant value for a.
Bernoulli	B	Incoming message from b.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the and argument.

Remarks

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

AverageLogFactor()

Evidence message for VMP.

Declaration

public static double AverageLogFactor()

Returns

Type	Description
Double	Zero.

Remarks

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

AverageLogFactor(Boolean, Boolean, Boolean)

Evidence message for VMP.

Declaration

public static double AverageLogFactor(bool and, bool a, bool b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	a	Constant value for a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Zero.

Remarks

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

BAverageConditional(Bernoulli, Bernoulli)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(Bernoulli and, Bernoulli A)

Parameters

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

Returns

Type	Description
Bernoulli	The outgoing EP message to the b argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

BAverageConditional(Bernoulli, Boolean)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(Bernoulli and, bool A)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	A	Constant value for a.

Returns

Type	Description
Bernoulli	The outgoing EP message to the b argument.

Remarks

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

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

BAverageConditional(Boolean, Bernoulli)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(bool and, Bernoulli A)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	A	Incoming message from a.

Returns

Type	Description
Bernoulli	The outgoing EP message to the b argument.

Remarks

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

BAverageConditional(Boolean, Boolean)

EP message to b.

Declaration

public static Bernoulli BAverageConditional(bool and, bool A)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	A	Constant value for a.

Returns

Type	Description
Bernoulli	The outgoing EP message to the b argument.

Remarks

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

BAverageLogarithm(Bernoulli, Bernoulli)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(Bernoulli and, Bernoulli A)

Parameters

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

Returns

Type	Description
Bernoulli	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, and is integrated out before taking the logarithm. The formula is exp(sum_(a) p(a) log(sum_and p(and) factor(and,a,b))).

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

BAverageLogarithm(Bernoulli, Boolean)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(Bernoulli and, bool A)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and. Must be a proper distribution. If uniform, the result will be uniform.
Boolean	A	Constant value for a.

Returns

Type	Description
Bernoulli	The outgoing VMP message to the b argument.

Remarks

The outgoing message is the factor viewed as a function of b with and integrated out. The formula is sum_and p(and) factor(and,a,b).

Exceptions

Type	Condition
ImproperMessageException	and is not a proper distribution.

BAverageLogarithm(Boolean, Bernoulli)

VMP message to b.

Declaration

[NotSupported("Variational Message Passing does not support an And factor with fixed output.")]
public static Bernoulli BAverageLogarithm(bool and, Bernoulli A)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	A	Incoming message from a.

Returns

Type	Description
Bernoulli	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(and,a,b))).

BAverageLogarithm(Boolean, Boolean)

VMP message to b.

Declaration

public static Bernoulli BAverageLogarithm(bool and, bool A)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	A	Constant value for a.

Returns

Type	Description
Bernoulli	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.

LogAverageFactor(Bernoulli, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli and, Bernoulli a, Bernoulli b)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and.
Bernoulli	a	Incoming message from a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(and,a,b) p(and,a,b) factor(and,a,b)).

LogAverageFactor(Bernoulli, Bernoulli, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli and, Bernoulli a, bool b)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and.
Bernoulli	a	Incoming message from a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(and,a) p(and,a) factor(and,a,b)).

LogAverageFactor(Bernoulli, Boolean, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli and, bool a, Bernoulli b)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and.
Boolean	a	Constant value for a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(and,b) p(and,b) factor(and,a,b)).

LogAverageFactor(Bernoulli, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(Bernoulli and, bool a, bool b)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and.
Boolean	a	Constant value for a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(and) p(and) factor(and,a,b)).

LogAverageFactor(Boolean, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool and, Bernoulli a, Bernoulli b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	a	Incoming message from a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(a,b) p(a,b) factor(and,a,b)).

LogAverageFactor(Boolean, Bernoulli, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool and, Bernoulli a, bool b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	a	Incoming message from a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(a) p(a) factor(and,a,b)).

LogAverageFactor(Boolean, Boolean, Bernoulli)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool and, bool a, Bernoulli b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	a	Constant value for a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(sum_(b) p(b) factor(and,a,b)).

LogAverageFactor(Boolean, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogAverageFactor(bool and, bool a, bool b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	a	Constant value for a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's average value across the given argument distributions.

Remarks

The formula for the result is log(factor(and,a,b)).

LogEvidenceRatio(Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(Bernoulli and)

Parameters

Type	Name	Description
Bernoulli	and	Incoming message from and.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(and) p(and) factor(and,a,b) / sum_and p(and) messageTo(and)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Bernoulli, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool and, Bernoulli a, Bernoulli b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	a	Incoming message from a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(a,b) p(a,b) factor(and,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Bernoulli, Boolean)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool and, Bernoulli a, bool b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Bernoulli	a	Incoming message from a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(a) p(a) factor(and,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Boolean, Bernoulli)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool and, bool a, Bernoulli b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	a	Constant value for a.
Bernoulli	b	Incoming message from b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(sum_(b) p(b) factor(and,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.

LogEvidenceRatio(Boolean, Boolean, Boolean)

Evidence message for EP.

Declaration

public static double LogEvidenceRatio(bool and, bool a, bool b)

Parameters

Type	Name	Description
Boolean	and	Constant value for and.
Boolean	a	Constant value for a.
Boolean	b	Constant value for b.

Returns

Type	Description
Double	Logarithm of the factor's contribution the EP model evidence.

Remarks

The formula for the result is log(factor(and,a,b)). Adding up these values across all factors and variables gives the log-evidence estimate for EP.