Class PDF: Virtual Base class representing Probability Density Functions.
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#include <pdf.h>
template<typename T>
class BFL::Pdf< T >
Class PDF: Virtual Base class representing Probability Density Functions.
Definition at line 53 of file pdf.h.
Constructor.
- Parameters
-
dimension | int representing the number of rows of the state |
Pure virtual clone function.
template<typename T>
virtual MatrixWrapper::SymmetricMatrix BFL::Pdf< T >::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!
template<typename T>
unsigned int BFL::Pdf< T >::DimensionGet |
( |
| ) |
const |
Get the dimension of the argument.
- Returns
- the dimension of the argument
template<typename T>
virtual void BFL::Pdf< T >::DimensionSet |
( |
unsigned int |
dim | ) |
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|
virtual |
Set the dimension of the argument.
- Parameters
-
template<typename T>
virtual T BFL::Pdf< T >::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?
Get the probability of a certain argument.
- Parameters
-
input | T argument of the Pdf |
- Returns
- the probability value of the argument
template<typename T>
virtual bool BFL::Pdf< T >::SampleFrom |
( |
vector< Sample< T > > & |
list_samples, |
|
|
const unsigned int |
num_samples, |
|
|
int |
method = DEFAULT , |
|
|
void * |
args = NULL |
|
) |
| const |
|
virtual |
Draw multiple samples from the Pdf (overloaded)
- Parameters
-
list_samples | list of samples that will contain result of sampling |
num_samples | Number of Samples to be drawn (iid) |
method | Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1 |
args | Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent... |
- Todo:
- replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)
- Bug:
- Sometimes the compiler doesn't know which method to choose!
template<typename T>
virtual bool BFL::Pdf< T >::SampleFrom |
( |
Sample< T > & |
one_sample, |
|
|
int |
method = DEFAULT , |
|
|
void * |
args = NULL |
|
) |
| const |
|
virtual |
Draw 1 sample from the Pdf:
There's no need to create a list for only 1 sample!
- Parameters
-
one_sample | sample that will contain result of sampling |
method | Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1 |
args | Pointer to a struct representing extra sample arguments |
- See also
- SampleFrom()
- Bug:
- Sometimes the compiler doesn't know which method to choose!
Dimension of the argument x of P(x | ...).
Definition at line 145 of file pdf.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