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

#include <conditionalpdf.h>

Inheritance diagram for ConditionalPdf< Var, CondArg >:

Public Member Functions
	ConditionalPdf (int dimension=0, unsigned int num_conditional_arguments=0)
	Constructor. More...

virtual	~ConditionalPdf ()
	Destructor.

virtual ConditionalPdf< Var, CondArg > *	Clone () const
	Clone function.

unsigned int	NumConditionalArgumentsGet () const
	Get the Number of conditional arguments. More...

virtual void	NumConditionalArgumentsSet (unsigned int numconditionalarguments)
	Set the Number of conditional arguments. More...

const std::vector< CondArg > &	ConditionalArgumentsGet () const
	Get the whole list of conditional arguments. More...

virtual void	ConditionalArgumentsSet (std::vector< CondArg > ConditionalArguments)
	Set the whole list of conditional arguments. More...

const CondArg &	ConditionalArgumentGet (unsigned int n_argument) const
	Get the n-th argument of the list. More...

virtual void	ConditionalArgumentSet (unsigned int n_argument, const CondArg &argument)
	Set the n-th argument of the list. More...

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) More...

virtual bool	SampleFrom (Sample< Var > &one_sample, int method=DEFAULT, void *args=NULL) const
	Draw 1 sample from the Pdf: More...

virtual Probability	ProbabilityGet (const Var &input) const
	Get the probability of a certain argument. More...

unsigned int	DimensionGet () const
	Get the dimension of the argument. More...

virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument. More...

virtual Var	ExpectedValueGet () const
	Get the expected value E[x] of the pdf. More...

virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const
	Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. More...

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`
	)

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.

Member Function Documentation

const CondArg & ConditionalArgumentGet ( unsigned int n_argument ) const

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
	)

virtual

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.

const std::vector< CondArg > & ConditionalArgumentsGet ( ) const

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 )

virtual

Set the whole list of conditional arguments.

Parameters

ConditionalArguments

an STL-vector of type

containing the condtional arguments

Definition at line 158 of file conditionalpdf.h.

virtual MatrixWrapper::SymmetricMatrix CovarianceGet ( ) const

virtualinherited

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!

unsigned int DimensionGet ( ) const

inherited

Get the dimension of the argument.

Returns: the dimension of the argument

virtual void DimensionSet ( unsigned int dim )

virtualinherited

Set the dimension of the argument.

Parameters

dim	the dimension

virtual Var ExpectedValueGet ( ) const

virtualinherited

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?

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 )

inlinevirtual

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.

virtual Probability ProbabilityGet ( const Var & input ) const

virtualinherited

Get the probability of a certain argument.

Parameters

input T argument of the Pdf

Returns: the probability value of the argument

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

virtualinherited

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

virtualinherited

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!

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

conditionalpdf.h

Public Member Functions

Detailed Description

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

Constructor & Destructor Documentation

Member Function Documentation

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