ConditionalPdf Class Template Reference

Abstract Class representing conditional Pdfs P(x | ...). More...

#include <conditionalpdf.h>

Inheritance diagram for ConditionalPdf:

Pdf< Var >

List of all members.

Public Member Functions

 ConditionalPdf (int dimension=0, unsigned int num_conditional_arguments=0)
 Constructor.
virtual ~ConditionalPdf ()
 Destructor.
virtual ConditionalPdf< Var,
CondArg > * 
Clone () const
 Clone function.
unsigned int NumConditionalArgumentsGet () const
 Get the Number of conditional arguments.
virtual void NumConditionalArgumentsSet (unsigned int numconditionalarguments)
 Set the Number of conditional arguments.
const std::vector< CondArg > & ConditionalArgumentsGet () const
 Get the whole list of conditional arguments.
void ConditionalArgumentsSet (std::vector< CondArg > ConditionalArguments)
 Set the whole list of conditional arguments.
const CondArg & ConditionalArgumentGet (unsigned int n_argument) const
 Get the n-th argument of the list.
void ConditionalArgumentSet (unsigned int n_argument, const CondArg &argument)
 Set the n-th argument of the list.
virtual bool SampleFrom (vector< Sample< Var > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const
 Draw multiple samples from the Pdf (overloaded).
virtual bool SampleFrom (Sample< Var > &one_sample, int method=DEFAULT, void *args=NULL) const
 Draw 1 sample from the Pdf:.
virtual Probability ProbabilityGet (const Var &input) const
 Get the probability of a certain argument.
unsigned int DimensionGet () const
 Get the dimension of the argument.
virtual void DimensionSet (unsigned int dim)
 Set the dimension of the argument.
virtual Var ExpectedValueGet () const
 Get the expected value E[x] of the pdf.
virtual
MatrixWrapper::SymmetricMatrix 
CovarianceGet () const
 Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.


Detailed Description

template<typename Var, typename CondArg>
class BFL::ConditionalPdf< Var, CondArg >

Abstract Class representing conditional Pdfs P(x | ...).

This class inherits from Pdf Virtual public because of the multiple inheritance that follows Two templates are here to allow a mixture of discrete and continu variables in the Pdf!

Bug:
All conditional arguments should be of the same type T for now!
Todo:
Investigate if we can allow. It is for sure that we'll need another class then the std::list to implement this!
See also:
Pdf

Definition at line 49 of file conditionalpdf.h.


Constructor & Destructor Documentation

ConditionalPdf ( int  dimension = 0,
unsigned int  num_conditional_arguments = 0 
) [inline]

Constructor.

Parameters:
dimension int representing the number of rows of the state vector
num_conditional_arguments the number of arguments behind the |

Definition at line 116 of file conditionalpdf.h.

Referenced by ConditionalPdf::Clone().


Member Function Documentation

unsigned int NumConditionalArgumentsGet (  )  const [inline]

Get the Number of conditional arguments.

Returns:
the number of conditional arguments

Definition at line 135 of file conditionalpdf.h.

void NumConditionalArgumentsSet ( unsigned int  numconditionalarguments  )  [inline, virtual]

Set the Number of conditional arguments.

Parameters:
numconditionalarguments the number of conditionalarguments
Bug:
will probably give rise to memory allocation problems if you herit from this class and do not redefine this method.

Reimplemented in LinearAnalyticConditionalGaussian.

Definition at line 141 of file conditionalpdf.h.

const std::vector< CondArg > & ConditionalArgumentsGet (  )  const [inline]

Get the whole list of conditional arguments.

Returns:
an STL-vector containing all the current values of the conditional arguments

Definition at line 152 of file conditionalpdf.h.

void ConditionalArgumentsSet ( std::vector< CondArg >  ConditionalArguments  )  [inline]

Set the whole list of conditional arguments.

Parameters:
ConditionalArguments an STL-vector of type
T
containing the condtional arguments

Definition at line 158 of file conditionalpdf.h.

const CondArg & ConditionalArgumentGet ( unsigned int  n_argument  )  const [inline]

Get the n-th argument of the list.

Returns:
The current value of the n-th conditional argument (starting from 0!)

Definition at line 165 of file conditionalpdf.h.

void ConditionalArgumentSet ( unsigned int  n_argument,
const CondArg &  argument 
) [inline]

Set the n-th argument of the list.

Parameters:
n_argument which one of the conditional arguments
argument value of the n-th argument

Definition at line 173 of file conditionalpdf.h.

virtual bool SampleFrom ( vector< Sample< Var > > &  list_samples,
const unsigned int  num_samples,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual, inherited]

Draw multiple samples from the Pdf (overloaded).

Parameters:
list_samples list of samples that will contain result of sampling
num_samples Number of Samples to be drawn (iid)
method Sampling method to be used. Each sampling method is currently represented by a define statement, eg. define BOXMULLER 1
args Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent...
Todo:
replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)
Bug:
Sometimes the compiler doesn't know which method to choose!

virtual bool SampleFrom ( Sample< Var > &  one_sample,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual, inherited]

Draw 1 sample from the Pdf:.

There's no need to create a list for only 1 sample!

Parameters:
one_sample sample that will contain result of sampling
method Sampling method to be used. Each sampling method is currently represented by a define statement, eg. define BOXMULLER 1
args Pointer to a struct representing extra sample arguments
See also:
SampleFrom()
Bug:
Sometimes the compiler doesn't know which method to choose!

virtual Probability ProbabilityGet ( const Var &  input  )  const [virtual, inherited]

Get the probability of a certain argument.

Parameters:
input T argument of the Pdf
Returns:
the probability value of the argument

unsigned int DimensionGet (  )  const [inherited]

Get the dimension of the argument.

Returns:
the dimension of the argument

virtual void DimensionSet ( unsigned int  dim  )  [virtual, inherited]

Set the dimension of the argument.

Parameters:
dim the dimension

virtual Var ExpectedValueGet (  )  const [virtual, inherited]

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns:
The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)
Note:
No set functions here! This can be useful for analytic functions, but not for sample based representations!

For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

virtual MatrixWrapper::SymmetricMatrix CovarianceGet (  )  const [virtual, inherited]

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns:
The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)
Todo:
extend this more general to n-th order statistic
Bug:
Discrete pdfs should not be able to use this!


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

Generated on Mon Mar 30 05:43:59 2009 for Bayesian Filtering Library by  doxygen 1.5.5