Public Member Functions | Protected Attributes | List of all members
BFL::AnalyticConditionalGaussianAdditiveNoise Class Reference

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 ConditionalGaussianClone () 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
gausGaussian representing the additive uncertainty
num_conditional_argumentsThe number of conditional arguments.
BFL::AnalyticConditionalGaussianAdditiveNoise::AnalyticConditionalGaussianAdditiveNoise ( int  dim = 0,
int  num_conditional_arguments = 0 
)

Constructor 2, Gaussian not yet known.

Parameters
dimDimension of state
num_conditional_argumentsThe 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
muthe 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
sigmathe 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:


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 Jun 10 2019 12:48:01