Abstract Class representing all Conditional gaussians. More...
#include <conditionalgaussian.h>
Public Member Functions | |
| virtual ConditionalGaussian * | Clone () const |
| Clone function. | |
| ConditionalGaussian (int dim=0, int num_conditional_arguments=0) | |
| Constructor. | |
| 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 () |
| Destructor. | |
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
![\[ P ( A | B, C, D, ... ) \]](form_43.png)
where
![\[ \mu_A = f(B,C,D, ...) \]](form_44.png)
and
![\[ \Sigma_A = g(B,C,D, ...) \]](form_45.png)
and
![\[ A = N(\mu_A, \Sigma_A) \]](form_46.png)
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 |
||
| ) |
Constructor.
- Parameters:
-
dim Dimension of state num_conditional_arguments The number of conditional arguments.
Definition at line 28 of file conditionalgaussian.cpp.
| BFL::ConditionalGaussian::~ConditionalGaussian | ( | ) | [virtual] |
Destructor.
Definition at line 39 of file conditionalgaussian.cpp.
Member Function Documentation
| ConditionalGaussian * BFL::ConditionalGaussian::Clone | ( | ) | const [virtual] |
Clone function.
Reimplemented from BFL::ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >.
Reimplemented in BFL::LinearAnalyticConditionalGaussian.
Definition at line 42 of file conditionalgaussian.cpp.
| Probability BFL::ConditionalGaussian::ProbabilityGet | ( | const MatrixWrapper::ColumnVector & | input | ) | const [virtual] |
Get the probability of a certain argument.
- Parameters:
-
input T argument of the Pdf
- Returns:
- 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: