PLearn 0.1
Public Member Functions
PLearn::ElementWiseDivisionRandomVariable Class Reference

#include <RandomVar.h>

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List of all members.

Public Member Functions

 ElementWiseDivisionRandomVariable (RandomVar input1, RandomVar input2)
 RandomVariable ElementWiseDivision.
virtual char * classname ()
void setValueFromParentsValue ()
 set the field value from the values of the parents
bool invertible (const Var &obs, RVInstanceArray &unobserved_parents, Var **JacobianCorrection)
 functions specific to FunctionalRandomVariable's
void EMBprop (const Vec obs, real post)
void EMTrainingInitialize (const RVArray &parameters_to_learn)
 Initialization of EM training (before all the iterations start).
void EMEpochInitialize ()
 Initialization of an individual EMEpoch.
void EMUpdate ()
const RandomVarX0 ()
 convenience inline's
const RandomVarX1 ()

Detailed Description

Y = X0 / X1

Definition at line 1364 of file RandomVar.h.


Constructor & Destructor Documentation

PLearn::ElementWiseDivisionRandomVariable::ElementWiseDivisionRandomVariable ( RandomVar  input1,
RandomVar  input2 
)

RandomVariable ElementWiseDivision.

Definition at line 1538 of file RandomVar.cc.

References PLERROR.

    : FunctionalRandomVariable(input1 & input2, 
                               MAX(input1->length(),input2->length()))
{
    if(input1->length() != input2->length() &&
       input1->length() !=1 && input2->length()!=1)
        PLERROR("ElementWiseDivisionRandomVariable(RandomVariable* in1, RandomVariable* in2) in1 and"
                "in2 must have the same length or one of them must be of length 1");
}

Member Function Documentation

virtual char* PLearn::ElementWiseDivisionRandomVariable::classname ( ) [inline, virtual]

Implements PLearn::RandomVariable.

Definition at line 1369 of file RandomVar.h.

{ return "ElementWiseDivisionRandomVariable"; }
void PLearn::ElementWiseDivisionRandomVariable::EMBprop ( const Vec  obs,
real  posterior 
) [virtual]

************ EM STUFF ********** propagate posterior information to parents in order to perform an EMupdate at the end of an EMEpoch. In the case of mixture-like RVs and their components, the posterior is the probability of the component "this" given the observation "obs".

Implements PLearn::RandomVariable.

Definition at line 1576 of file RandomVar.cc.

{
}
void PLearn::ElementWiseDivisionRandomVariable::EMEpochInitialize ( ) [virtual]

Initialization of an individual EMEpoch.

the default just propagates to the unmarked parents

Reimplemented from PLearn::RandomVariable.

Definition at line 1572 of file RandomVar.cc.

{
}
void PLearn::ElementWiseDivisionRandomVariable::EMTrainingInitialize ( const RVArray parameters_to_learn) [virtual]

Initialization of EM training (before all the iterations start).

the default just propagates to the unmarked parents

Reimplemented from PLearn::RandomVariable.

Definition at line 1568 of file RandomVar.cc.

{
}
void PLearn::ElementWiseDivisionRandomVariable::EMUpdate ( ) [virtual]

update the fixed (non-random) parameters using internal learning mechanism, at end of an EMEpoch. the default just propagates to the unmarked parents.

Reimplemented from PLearn::RandomVariable.

Definition at line 1580 of file RandomVar.cc.

References PLERROR.

{
    PLERROR("ElementWiseDivisionRandomVariable::EMUpdate() not implemented");
}
bool PLearn::ElementWiseDivisionRandomVariable::invertible ( const Var obs,
RVInstanceArray unobserved_parents,
Var **  JacobianCorrection 
) [virtual]

functions specific to FunctionalRandomVariable's

!< SUBCLASS WRITERS: IMPLEMENT FUNCTIONS BELOW //!<

check whether it is possible to invert the function which maps the given unobserved parents to the observed value of the RV (obs). If invertible, do the inversion, and set the value fields of the RVInstances to Var's which are functionally dependent on obs. If the absolute value of the Jacobian of the map from the unobserved parents to this R.V.'s value is different from 1, then JacobianCorrection should point to a Var that is the logarithm of the determinant of this Jacobian (first derivatives) matrix. If the function is not invertible but it is possible to write P(Y==obs | unobserved_parents) in terms of the unobserved_parents logP functions, then the sub-class writer should instead redefine the logP function appropriately.

Reimplemented from PLearn::FunctionalRandomVariable.

Definition at line 1554 of file RandomVar.cc.

References PLearn::TVec< T >::size(), X0(), and X1().

{
    if (unobserved_parents.size()==2)
        return false; // can't invert if two parents are unobserved
    if (unobserved_parents[0].V == X0())
        unobserved_parents[0].v = obs * X1()->value;
    else
        unobserved_parents[0].v = X0()->value / obs;
    return true;
}

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void PLearn::ElementWiseDivisionRandomVariable::setValueFromParentsValue ( ) [virtual]

set the field value from the values of the parents

Implements PLearn::FunctionalRandomVariable.

Definition at line 1548 of file RandomVar.cc.

References PLearn::RandomVariable::marked, PLearn::RandomVariable::value, X0(), and X1().

{
    if (marked) return;
    value = X0()->value / X1()->value;
}

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const RandomVar& PLearn::ElementWiseDivisionRandomVariable::X0 ( ) [inline]

convenience inline's

Definition at line 1380 of file RandomVar.h.

Referenced by invertible(), and setValueFromParentsValue().

{ return parents[0]; }

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const RandomVar& PLearn::ElementWiseDivisionRandomVariable::X1 ( ) [inline]

Definition at line 1381 of file RandomVar.h.

Referenced by invertible(), and setValueFromParentsValue().

{ return parents[1]; }

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The documentation for this class was generated from the following files:
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