Conditional Gaussian for an analytic nonlinear system using Ginac: More...

#include <nonlinearanalyticconditionalgaussian_ginac.h>

Inheritance diagram for BFL::NonLinearAnalyticConditionalGaussian_Ginac:

[legend]

Public Member Functions
vector< GiNaC::symbol >	ConditionalGet ()
	Get conditional arguments. More...

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

virtual MatrixWrapper::Matrix	dfGet (unsigned int i) const

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

GiNaC::matrix	FunctionGet ()
	return function More...

vector< GiNaC::symbol >	InputGet ()
	return substitution symbols More...

	NonLinearAnalyticConditionalGaussian_Ginac (const GiNaC::matrix &func, const vector< GiNaC::symbol > &u, const vector< GiNaC::symbol > &x, const Gaussian &additiveNoise, const vector< GiNaC::symbol > &cond)
	constructor More...

	NonLinearAnalyticConditionalGaussian_Ginac (const GiNaC::matrix &func, const vector< GiNaC::symbol > &u, const vector< GiNaC::symbol > &x, const Gaussian &additiveNoise)
	constructor More...

	NonLinearAnalyticConditionalGaussian_Ginac (const NonLinearAnalyticConditionalGaussian_Ginac &g)
	copy constructor More...

vector< GiNaC::symbol >	StateGet ()
	return state symbols More...

virtual	~NonLinearAnalyticConditionalGaussian_Ginac ()
	Destructor. More...

Public Member Functions inherited from BFL::AnalyticConditionalGaussianAdditiveNoise
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	~AnalyticConditionalGaussianAdditiveNoise ()
	Destructor. More...

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

	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...

Private Attributes
unsigned int	cond_size

vector< GiNaC::symbol >	cond_sym

vector< GiNaC::ex >	dfunc_dcond

vector< GiNaC::ex >	dfunc_dx

unsigned int	func_size

GiNaC::matrix	func_sym

unsigned int	u_size

vector< GiNaC::symbol >	u_sym

unsigned int	x_size

vector< GiNaC::symbol >	x_sym

Friends
std::ostream &	operator<< (std::ostream &os, NonLinearAnalyticConditionalGaussian_Ginac &p)
	output stream for measurement model More...

Additional Inherited Members
Protected Attributes inherited from BFL::AnalyticConditionalGaussianAdditiveNoise
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

Conditional Gaussian for an analytic nonlinear system using Ginac:

Describes classes of the type

$P(z | subs)$

with

$z=f(subs) + N(\mu,\Sigma)$

or

$z=f(subs,c+N(\mu, \Sigma))$

Constructor for the first type:

$NonLinearAnalyticConditionalGaussian_Ginac(f(subs), subs, N(\mu, \Sigma) )$

Constructor for the second type:

$NonLinearAnalyticConditionalGaussian_Ginac(f(subs,z), subs, N(\mu, \Sigma) ,c)$

When the second type is used, the additive noise on c will be converted to additive noise on f, by locally linearising the function.

Bug:: : This class is higly biased towards filtering applications.

Definition at line 48 of file nonlinearanalyticconditionalgaussian_ginac.h.

Constructor & Destructor Documentation

◆ NonLinearAnalyticConditionalGaussian_Ginac() [1/3]

BFL::NonLinearAnalyticConditionalGaussian_Ginac::NonLinearAnalyticConditionalGaussian_Ginac	(	const GiNaC::matrix &	func,
		const vector< GiNaC::symbol > &	u,
		const vector< GiNaC::symbol > &	x,
		const Gaussian &	additiveNoise,
		const vector< GiNaC::symbol > &	cond
	)

constructor

Parameters

func	function to be evaluated for expected value
u	symbols to be substituted (by numeric values) for evaluation. These can be system inputs or sensor parameters
x	symbols representing state
additiveNoise	Gaussian representing additive noise
cond	parameters where additive noise applies to

Definition at line 30 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ NonLinearAnalyticConditionalGaussian_Ginac() [2/3]

BFL::NonLinearAnalyticConditionalGaussian_Ginac::NonLinearAnalyticConditionalGaussian_Ginac	(	const GiNaC::matrix &	func,
		const vector< GiNaC::symbol > &	u,
		const vector< GiNaC::symbol > &	x,
		const Gaussian &	additiveNoise
	)

constructor

Parameters

func	function to be evaluated for expected value
u	symbols to be substituted (by numeric values) for evaluation. These can be system inputs or sensor parameters
x	symbols representing state
additiveNoise	Gaussian representing additive noise on function output

Definition at line 62 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ NonLinearAnalyticConditionalGaussian_Ginac() [3/3]

BFL::NonLinearAnalyticConditionalGaussian_Ginac::NonLinearAnalyticConditionalGaussian_Ginac ( const NonLinearAnalyticConditionalGaussian_Ginac & g )

copy constructor

Definition at line 85 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ ~NonLinearAnalyticConditionalGaussian_Ginac()

BFL::NonLinearAnalyticConditionalGaussian_Ginac::~NonLinearAnalyticConditionalGaussian_Ginac ( )

virtual

Destructor.

Definition at line 112 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

Member Function Documentation

◆ ConditionalGet()

vector< GiNaC::symbol > BFL::NonLinearAnalyticConditionalGaussian_Ginac::ConditionalGet ( )

Get conditional arguments.

Definition at line 285 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ CovarianceGet()

MatrixWrapper::SymmetricMatrix BFL::NonLinearAnalyticConditionalGaussian_Ginac::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::AnalyticConditionalGaussianAdditiveNoise.

Definition at line 173 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ dfGet()

MatrixWrapper::Matrix BFL::NonLinearAnalyticConditionalGaussian_Ginac::dfGet ( unsigned int i ) const

virtual

Bug:: only implemented for i = 0 for now (so in a filter context, only the derivative with respect to x is implemented

Reimplemented from BFL::AnalyticConditionalGaussian.

Definition at line 224 of file nonlinearanalyticconditionalgaussian_ginac.cpp.

◆ ExpectedValueGet()

MatrixWrapper::ColumnVector BFL::NonLinearAnalyticConditionalGaussian_Ginac::ExpectedValueGet ( ) const

virtual

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?

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

Definition at line 127 of file nonlinearanalyticconditionalgaussian_ginac.cpp.