Abstract Class representing all Conditional gaussians. More...

#include <conditionalgaussian.h>

Inheritance diagram for BFL::ConditionalGaussian:

[legend]

Public Member Functions
virtual ConditionalGaussian *	Clone () const
	Clone function. More...

	ConditionalGaussian (int dim=0, int num_conditional_arguments=0)
	Constructor. More...

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

virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &sample, int method=DEFAULT, void *args=NULL) const

virtual bool	SampleFrom (std::vector< Sample< MatrixWrapper::ColumnVector > > &samples, const int num_samples, int method=DEFAULT, void *args=NULL) const

virtual	~ConditionalGaussian ()
	Destructor. More...

Public Member Functions inherited from BFL::ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >
const MatrixWrapper::ColumnVector &	ConditionalArgumentGet (unsigned int n_argument) const
	Get the n-th argument of the list. More...

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

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

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

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

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

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

virtual	~ConditionalPdf ()
	Destructor. More...

Public Member Functions inherited from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >
virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const
	Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. 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 MatrixWrapper::ColumnVector	ExpectedValueGet () const
	Get the expected value E[x] of the pdf. More...

	Pdf (unsigned int dimension=0)
	Constructor. More...

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

virtual	~Pdf ()
	Destructor. More...

Protected Attributes
ColumnVector	_diff

Matrix	_Low_triangle

ColumnVector	_Mu

ColumnVector	_samples

ColumnVector	_SampleValue

Detailed Description

Abstract Class representing all Conditional gaussians.

This class inherits only from ConditionalPdf<ColumnVector, ColumnVector>.

So this class represents all Pdf's of the type

$P ( A | B, C, D, ... )$

where

$\mu_A = f(B,C,D, ...)$

and

$\Sigma_A = g(B,C,D, ...)$

and

$A = N(\mu_A, \Sigma_A)$

f and g are not necessarily analytical functions

Definition at line 40 of file conditionalgaussian.h.

Constructor & Destructor Documentation

BFL::ConditionalGaussian::ConditionalGaussian	(	int	dim = `0`,
		int	num_conditional_arguments = `0`
	)

Constructor.

Parameters

dim	Dimension of state
num_conditional_arguments	The number of conditional arguments.

Definition at line 28 of file conditionalgaussian.cpp.

BFL::ConditionalGaussian::~ConditionalGaussian ( )

virtual

Destructor.

Definition at line 39 of file conditionalgaussian.cpp.

Member Function Documentation

ConditionalGaussian * BFL::ConditionalGaussian::Clone ( ) const

virtual

Clone function.

Reimplemented from BFL::ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >.

Reimplemented in BFL::LinearAnalyticConditionalGaussian.

Definition at line 42 of file conditionalgaussian.cpp.

Probability BFL::ConditionalGaussian::ProbabilityGet ( const MatrixWrapper::ColumnVector & input ) const

virtual

Get the probability of a certain argument.

Parameters

input T argument of the Pdf

Returns: the probability value of the argument

Reimplemented from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 48 of file conditionalgaussian.cpp.

virtual bool BFL::ConditionalGaussian::SampleFrom	(	Sample< MatrixWrapper::ColumnVector > &	sample,
		int	method = `DEFAULT`,
		void *	args = `NULL`
	)		const

virtual

virtual bool BFL::ConditionalGaussian::SampleFrom	(	std::vector< Sample< MatrixWrapper::ColumnVector > > &	samples,
		const int	num_samples,
		int	method = `DEFAULT`,
		void *	args = `NULL`
	)		const

virtual

Member Data Documentation

ColumnVector BFL::ConditionalGaussian::_diff

mutableprotected

Definition at line 67 of file conditionalgaussian.h.

Matrix BFL::ConditionalGaussian::_Low_triangle

mutableprotected

Definition at line 69 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_Mu

mutableprotected

Definition at line 68 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_samples

mutableprotected

Definition at line 70 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_SampleValue

mutableprotected

Definition at line 71 of file conditionalgaussian.h.

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

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation