BFL::LinearAnalyticConditionalGaussian Class Reference

Linear Conditional Gaussian. More...

#include <linearanalyticconditionalgaussian.h>

Inheritance diagram for BFL::LinearAnalyticConditionalGaussian:

List of all members.

Public Member Functions
virtual LinearAnalyticConditionalGaussian *	Clone () const
	Clone function.
virtual MatrixWrapper::Matrix	dfGet (unsigned int i) const
	returns derivative from function to n-th conditional variable
virtual MatrixWrapper::ColumnVector	ExpectedValueGet () const
	Get the expected value E[x] of the pdf.
	LinearAnalyticConditionalGaussian (const vector< MatrixWrapper::Matrix > &ratio, const Gaussian &additiveNoise)
	Constructor.
	LinearAnalyticConditionalGaussian (const MatrixWrapper::Matrix &a, const Gaussian &additiveNoise)
	Constructor (overloaded)
const MatrixWrapper::Matrix &	MatrixGet (unsigned int i) const
	Get the i-th matrix of the system.
void	MatrixSet (unsigned int i, const MatrixWrapper::Matrix &m)
	Set the i-th Matrix for calculation of .
virtual void	NumConditionalArgumentsSet (unsigned int numconditionalarguments)
	Be careful: you don't want to use this one: Redefined.
virtual	~LinearAnalyticConditionalGaussian ()
	Destructor.
Private Attributes
MatrixWrapper::ColumnVector	_arg
MatrixWrapper::ColumnVector	_mean_temp
vector< MatrixWrapper::Matrix >	_ratio

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Detailed Description

Linear Conditional Gaussian.

• 
• Covariance is independent of the ConditionalArguments, and is the covariance of the Noise pdf

Definition at line 35 of file linearanalyticconditionalgaussian.h.

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Constructor & Destructor Documentation

BFL::LinearAnalyticConditionalGaussian::LinearAnalyticConditionalGaussian	(	const vector< MatrixWrapper::Matrix > &	ratio,
		const Gaussian &	additiveNoise
	)

Constructor.

Precondition:

: Every Matrix should have the same amount of rows! This is currently not checked. The same goes for the number of columns, which should be equal to the number of rows of the corresponding conditional argument!

Parameters:

ratio,:	vector containing the different matrices of the linear relationship between the conditional arguments and
additiveNoise	Pdf representing the additive Gaussian uncertainty

BFL::LinearAnalyticConditionalGaussian::LinearAnalyticConditionalGaussian	(	const MatrixWrapper::Matrix &	a,
		const Gaussian &	additiveNoise
	)

Constructor (overloaded)

Precondition:

There is only 1 conditional argument.

Parameters:

a	Matrix for calculation of :
additiveNoise	Pdf representing the additive Gaussian uncertainty

BFL::LinearAnalyticConditionalGaussian::~LinearAnalyticConditionalGaussian

(

)

[virtual]

Destructor.

Definition at line 60 of file linearanalyticconditionalgaussian.cpp.

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Member Function Documentation

LinearAnalyticConditionalGaussian * BFL::LinearAnalyticConditionalGaussian::Clone

(

)

const [virtual]

Clone function.

Reimplemented from BFL::ConditionalGaussian.

Definition at line 63 of file linearanalyticconditionalgaussian.cpp.

Matrix BFL::LinearAnalyticConditionalGaussian::dfGet

(

unsigned int

i

)

const [virtual]

returns derivative from function to n-th conditional variable

Parameters:

i	Number of the conditional variable to use for partial derivation

Returns:

Partial derivative with respect to conditional variable i

Reimplemented from BFL::AnalyticConditionalGaussian.

Definition at line 82 of file linearanalyticconditionalgaussian.cpp.

ColumnVector BFL::LinearAnalyticConditionalGaussian::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 69 of file linearanalyticconditionalgaussian.cpp.

const Matrix & BFL::LinearAnalyticConditionalGaussian::MatrixGet

(

unsigned int

i

)

const

Get the i-th matrix of the system.

Parameters:

i	index determining which conditional Arg. multiplier matrix will returned

Returns:

the n-th Matrix of the system-equation

Definition at line 103 of file linearanalyticconditionalgaussian.cpp.

void BFL::LinearAnalyticConditionalGaussian::MatrixSet	(	unsigned int	i,
		const MatrixWrapper::Matrix &	m
	)

Set the i-th Matrix for calculation of .

Set the i-th Matrix of the calculation in the conditonal gaussian class

Precondition:

i < Numconditionalarg

Parameters:

i	index determining which conditional Arg. will be multiplied with the given matrix
m	Matrix for calculation of :

Definition at line 96 of file linearanalyticconditionalgaussian.cpp.

void BFL::LinearAnalyticConditionalGaussian::NumConditionalArgumentsSet

(

unsigned int

numconditionalarguments

)

[virtual]

Be careful: you don't want to use this one: Redefined.

Bug:

This method is not implemented, we can ReSize the std::vector<BFL::Matrix>, but we don't know the dimensions of the matrices self. So this will most certainly result in a segfault. Anyway, why would you need this?

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

Definition at line 89 of file linearanalyticconditionalgaussian.cpp.

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Member Data Documentation

MatrixWrapper::ColumnVector BFL::LinearAnalyticConditionalGaussian::_arg [mutable, private]

Definition at line 104 of file linearanalyticconditionalgaussian.h.

MatrixWrapper::ColumnVector BFL::LinearAnalyticConditionalGaussian::_mean_temp [mutable, private]

Definition at line 103 of file linearanalyticconditionalgaussian.h.

vector<MatrixWrapper::Matrix> BFL::LinearAnalyticConditionalGaussian::_ratio [private]

Definition at line 101 of file linearanalyticconditionalgaussian.h.

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

• linearanalyticconditionalgaussian.h
• linearanalyticconditionalgaussian.cpp