Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise. More...

#include <analyticconditionalgaussian_additivenoise.h>

Inheritance diagram for BFL::AnalyticConditionalGaussianAdditiveNoise:

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Public Member Functions
const MatrixWrapper::ColumnVector &	AdditiveNoiseMuGet () const
	Get the mean Value of the Additive Gaussian uncertainty. More...

void	AdditiveNoiseMuSet (const MatrixWrapper::ColumnVector &mu)
	Set the mean Value of the Additive Gaussian uncertainty. More...

const MatrixWrapper::SymmetricMatrix &	AdditiveNoiseSigmaGet () const
	Get the covariance matrix of the Additive Gaussian uncertainty. More...

void	AdditiveNoiseSigmaSet (const MatrixWrapper::SymmetricMatrix &sigma)
	Set the covariance of the Additive Gaussian uncertainty. More...

	AnalyticConditionalGaussianAdditiveNoise (const Gaussian &gaus, int num_conditional_arguments=1)
	Constructor. More...

	AnalyticConditionalGaussianAdditiveNoise (int dim=0, int num_conditional_arguments=0)
	Constructor 2, Gaussian not yet known. More...

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

virtual	~AnalyticConditionalGaussianAdditiveNoise ()
	Destructor. More...

Public Member Functions inherited from BFL::AnalyticConditionalGaussian
	AnalyticConditionalGaussian (int dim=0, int num_conditional_arguments=0)
	Constructor. More...

virtual MatrixWrapper::Matrix	dfGet (unsigned int i) const
	returns derivative from function to n-th conditional variable More...

virtual	~AnalyticConditionalGaussian ()
	Destructor. More...

Public Member Functions inherited from BFL::ConditionalGaussian
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 >
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
MatrixWrapper::ColumnVector	_additiveNoise_Mu
	additive noise expected value More...

MatrixWrapper::SymmetricMatrix	_additiveNoise_Sigma
	additive noise covariance More...

Protected Attributes inherited from BFL::ConditionalGaussian
ColumnVector	_diff

Matrix	_Low_triangle

ColumnVector	_Mu

ColumnVector	_samples

ColumnVector	_SampleValue

Detailed Description

Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise.

This class represents all Pdf's of the type

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

where

$\mu_A = f(B,C,D, ...) + mu_{additiveNoise}$

and

$\Sigma_A = \Sigma_{additiveNoise}$

and

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

Definition at line 37 of file analyticconditionalgaussian_additivenoise.h.

Constructor & Destructor Documentation

BFL::AnalyticConditionalGaussianAdditiveNoise::AnalyticConditionalGaussianAdditiveNoise	(	const Gaussian &	gaus,
		int	num_conditional_arguments = `1`
	)

Constructor.

Parameters

gaus	Gaussian representing the additive uncertainty
num_conditional_arguments	The number of conditional arguments.

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

Constructor 2, Gaussian not yet known.

Parameters

dim	Dimension of state
num_conditional_arguments	The number of conditional arguments.

virtual BFL::AnalyticConditionalGaussianAdditiveNoise::~AnalyticConditionalGaussianAdditiveNoise ( )

virtual

Destructor.

Member Function Documentation

const MatrixWrapper::ColumnVector& BFL::AnalyticConditionalGaussianAdditiveNoise::AdditiveNoiseMuGet ( ) const

Get the mean Value of the Additive Gaussian uncertainty.

Returns: the mean Value of the Additive Gaussian uncertainty

void BFL::AnalyticConditionalGaussianAdditiveNoise::AdditiveNoiseMuSet ( const MatrixWrapper::ColumnVector & mu )

Set the mean Value of the Additive Gaussian uncertainty.

Parameters

mu	the mean Value of the Additive Gaussian uncertainty

const MatrixWrapper::SymmetricMatrix& BFL::AnalyticConditionalGaussianAdditiveNoise::AdditiveNoiseSigmaGet ( ) const

Get the covariance matrix of the Additive Gaussian uncertainty.

Returns: the mean Value of the Additive Gaussian uncertainty

void BFL::AnalyticConditionalGaussianAdditiveNoise::AdditiveNoiseSigmaSet ( const MatrixWrapper::SymmetricMatrix & sigma )

Set the covariance of the Additive Gaussian uncertainty.

Parameters

sigma the covariance matrix of the Additive Gaussian uncertainty

virtual MatrixWrapper::SymmetricMatrix BFL::AnalyticConditionalGaussianAdditiveNoise::CovarianceGet ( ) const

virtual

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!

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

Reimplemented in BFL::NonLinearAnalyticConditionalGaussian_Ginac.

Member Data Documentation

MatrixWrapper::ColumnVector BFL::AnalyticConditionalGaussianAdditiveNoise::_additiveNoise_Mu

protected

additive noise expected value

Definition at line 92 of file analyticconditionalgaussian_additivenoise.h.

MatrixWrapper::SymmetricMatrix BFL::AnalyticConditionalGaussianAdditiveNoise::_additiveNoise_Sigma

protected

additive noise covariance

Definition at line 95 of file analyticconditionalgaussian_additivenoise.h.

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

analyticconditionalgaussian_additivenoise.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation