Public Member Functions | Protected Attributes
BFL::ConditionalGaussian Class Reference

Abstract Class representing all Conditional gaussians. More...

#include <conditionalgaussian.h>

Inheritance diagram for BFL::ConditionalGaussian:
Inheritance graph

List of all members.

Public Member Functions

virtual ConditionalGaussianClone () const
 Clone function.
 ConditionalGaussian (int dim=0, int num_conditional_arguments=0)
virtual Probability ProbabilityGet (const MatrixWrapper::ColumnVector &input) const
 Get the probability of a certain argument.
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 ()

Protected Attributes

ColumnVector _diff
Matrix _Low_triangle
ColumnVector _Mu
ColumnVector _samples
ColumnVector _SampleValue

Detailed Description

Abstract Class representing all Conditional gaussians.

This class inherits only from ConditionalPdf<ColumnVector, ColumnVector>.

So this class represents all Pdf's of the type

\[ P ( A | B, C, D, ... ) \]


\[ \mu_A = f(B,C,D, ...) \]


\[ \Sigma_A = g(B,C,D, ...) \]


\[ A = N(\mu_A, \Sigma_A) \]

f and g are not necessarily analytical functions

Definition at line 40 of file conditionalgaussian.h.

Constructor & Destructor Documentation

BFL::ConditionalGaussian::ConditionalGaussian ( int  dim = 0,
int  num_conditional_arguments = 0 


dimDimension of state
num_conditional_argumentsThe number of conditional arguments.

Definition at line 28 of file conditionalgaussian.cpp.


Definition at line 39 of file conditionalgaussian.cpp.

Member Function Documentation

Probability BFL::ConditionalGaussian::ProbabilityGet ( const MatrixWrapper::ColumnVector &  input) const [virtual]

Get the probability of a certain argument.

inputT argument of the Pdf
the probability value of the argument

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

Definition at line 48 of file conditionalgaussian.cpp.

virtual bool BFL::ConditionalGaussian::SampleFrom ( Sample< MatrixWrapper::ColumnVector > &  sample,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]
virtual bool BFL::ConditionalGaussian::SampleFrom ( std::vector< Sample< MatrixWrapper::ColumnVector > > &  samples,
const int  num_samples,
int  method = DEFAULT,
void *  args = NULL 
) const [virtual]

Member Data Documentation

ColumnVector BFL::ConditionalGaussian::_diff [mutable, protected]

Definition at line 67 of file conditionalgaussian.h.

Matrix BFL::ConditionalGaussian::_Low_triangle [mutable, protected]

Definition at line 69 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_Mu [mutable, protected]

Definition at line 68 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_samples [mutable, protected]

Definition at line 70 of file conditionalgaussian.h.

ColumnVector BFL::ConditionalGaussian::_SampleValue [mutable, protected]

Definition at line 71 of file conditionalgaussian.h.

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

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