Public Member Functions | Private Attributes
BFL::LinearAnalyticConditionalGaussian Class Reference

Linear Conditional Gaussian. More...

#include <linearanalyticconditionalgaussian.h>

Inheritance diagram for BFL::LinearAnalyticConditionalGaussian:
Inheritance graph
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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 $ \mu $.
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

Detailed Description

Linear Conditional Gaussian.

Definition at line 35 of file linearanalyticconditionalgaussian.h.


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 $\mu$
additiveNoisePdf 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:
aMatrix for calculation of $\mu$: $ \mu = a . ConditionalArguments[0] + Noise.\mu $
additiveNoisePdf representing the additive Gaussian uncertainty

Destructor.

Definition at line 60 of file linearanalyticconditionalgaussian.cpp.


Member Function Documentation

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:
iNumber 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.

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:
iindex 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 $ \mu $.

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

Precondition:
i < Numconditionalarg
Parameters:
iindex determining which conditional Arg. will be multiplied with the given matrix
mMatrix for calculation of $ \mu $: $ \mu = ... m . ConditionalArguments[i] + ... $

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.


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.


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


bfl
Author(s): Klaas Gadeyne, Wim Meeussen, Tinne Delaet and many others. See web page for a full contributor list. ROS package maintained by Wim Meeussen.
autogenerated on Mon Feb 11 2019 03:45:12