PLearn 0.1
Public Types | Public Member Functions | Static Public Member Functions | Public Attributes | Static Public Attributes
PLearn::ConditionalDistribution Class Reference

#include <ConditionalDistribution.h>

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List of all members.

Public Types

typedef Distribution inherited

Public Member Functions

 ConditionalDistribution ()
virtual void makeDeepCopyFromShallowCopy (CopiesMap &copies)
 Transforms a shallow copy into a deep copy.
virtual string classname () const
virtual OptionListgetOptionList () const
virtual OptionMapgetOptionMap () const
virtual RemoteMethodMapgetRemoteMethodMap () const
virtual ConditionalDistributiondeepCopy (CopiesMap &copies) const
virtual void setInput (const Vec &input)
 Set the input part before using the inherited methods.
virtual void use (const Vec &input, Vec &output)
 computes the ouptu of a trained model

Static Public Member Functions

static string _classname_ ()
 Declares name and deepCopy methods.
static OptionList_getOptionList_ ()
static RemoteMethodMap_getRemoteMethodMap_ ()
static Object_new_instance_for_typemap_ ()
static bool _isa_ (const Object *o)
static void _static_initialize_ ()
static const PPathdeclaringFile ()

Public Attributes

int input_part_size

Static Public Attributes

static StaticInitializer _static_initializer_

Detailed Description

Definition at line 49 of file ConditionalDistribution.h.


Member Typedef Documentation

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 61 of file ConditionalDistribution.h.


Constructor & Destructor Documentation

PLearn::ConditionalDistribution::ConditionalDistribution ( )

Definition at line 44 of file ConditionalDistribution.cc.

    :inherited()
{
   
}

Member Function Documentation

string PLearn::ConditionalDistribution::_classname_ ( ) [static]

Declares name and deepCopy methods.

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

OptionList & PLearn::ConditionalDistribution::_getOptionList_ ( ) [static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

RemoteMethodMap & PLearn::ConditionalDistribution::_getRemoteMethodMap_ ( ) [static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

bool PLearn::ConditionalDistribution::_isa_ ( const Object o) [static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

Object * PLearn::ConditionalDistribution::_new_instance_for_typemap_ ( ) [static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

StaticInitializer ConditionalDistribution::_static_initializer_ & PLearn::ConditionalDistribution::_static_initialize_ ( ) [static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

string PLearn::ConditionalDistribution::classname ( ) const [virtual]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

static const PPath& PLearn::ConditionalDistribution::declaringFile ( ) [inline, static]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 79 of file ConditionalDistribution.h.

ConditionalDistribution * PLearn::ConditionalDistribution::deepCopy ( CopiesMap copies) const [virtual]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

OptionList & PLearn::ConditionalDistribution::getOptionList ( ) const [virtual]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

OptionMap & PLearn::ConditionalDistribution::getOptionMap ( ) const [virtual]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

RemoteMethodMap & PLearn::ConditionalDistribution::getRemoteMethodMap ( ) const [virtual]

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 52 of file ConditionalDistribution.cc.

void PLearn::ConditionalDistribution::makeDeepCopyFromShallowCopy ( CopiesMap copies) [virtual]

Transforms a shallow copy into a deep copy.

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 55 of file ConditionalDistribution.cc.

References PLearn::Distribution::makeDeepCopyFromShallowCopy().

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void PLearn::ConditionalDistribution::setInput ( const Vec input) [virtual]

Set the input part before using the inherited methods.

Definition at line 61 of file ConditionalDistribution.cc.

References PLERROR.

Referenced by use().

{ PLERROR("setInput must be implemented for this ConditionalDistribution"); }

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void PLearn::ConditionalDistribution::use ( const Vec input,
Vec output 
) [virtual]

computes the ouptu of a trained model

Reimplemented from PLearn::Distribution.

Definition at line 65 of file ConditionalDistribution.cc.

References PLearn::Distribution::cdf(), PLearn::Distribution::density(), PLearn::Distribution::expectation(), input_part_size, PLearn::TVec< T >::length(), PLearn::Distribution::log_density(), setInput(), PLearn::TVec< T >::subVec(), PLearn::Distribution::survival_fn(), PLearn::TMat< T >::toVec(), PLearn::Distribution::use_returns_what, PLearn::Distribution::variance(), and x.

{
    Vec x = input.subVec(0,input_part_size);
    Vec y = input.subVec(input_part_size,input.length()-input_part_size);
    setInput(x);
    if (use_returns_what=="l")
        output[0]=log_density(y);
    else if (use_returns_what=="d")
        output[0]=density(y);
    else if (use_returns_what=="c")
        output[0]=cdf(y);
    else if (use_returns_what=="s")
        output[0]=survival_fn(y);
    else if (use_returns_what=="e")
        output << expectation();
    else if (use_returns_what=="v")
        output << variance().toVec();
}

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Member Data Documentation

Reimplemented from PLearn::Distribution.

Reimplemented in PLearn::ConditionalGaussianDistribution.

Definition at line 79 of file ConditionalDistribution.h.

Definition at line 65 of file ConditionalDistribution.h.

Referenced by use().


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