Class representing a PDF on a discrete variable. More...
#include <mixtureParticleFilter.h>
Public Member Functions  
virtual DiscretePdf *  Clone () const 
Clone function. More...  
DiscretePdf (unsigned int num_states=0)  
Constructor (dimension = number of classes) An equal probability is set for all classes. More...  
DiscretePdf (const DiscretePdf &)  
Copy Constructor. More...  
int  MostProbableStateGet () 
Get the index of the most probable state. More...  
unsigned int  NumStatesGet () const 
Get the number of discrete States. More...  
vector< Probability >  ProbabilitiesGet () const 
Get all probabilities. More...  
bool  ProbabilitiesSet (vector< Probability > &values) 
Set all probabilities. More...  
Probability  ProbabilityGet (const int &state) const 
Implementation of virtual base class method. More...  
bool  ProbabilitySet (int state, Probability a) 
Function to change/set the probability of a single state. More...  
bool  SampleFrom (vector< Sample< int > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const 
Draw multiple samples from the Pdf (overloaded) More...  
bool  SampleFrom (Sample< int > &one_sample, int method=DEFAULT, void *args=NULL) const 
Draw 1 sample from the Pdf: More...  
virtual  ~DiscretePdf () 
Destructor. More...  
Public Member Functions inherited from BFL::BFL::Pdf< int >  
virtual MatrixWrapper::SymmetricMatrix  CovarianceGet () const 
Get the Covariance Matrix E[(x  E[x])^2] of the Analytic pdf. More...  
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 int  ExpectedValueGet () const 
Get the expected value E[x] of the pdf. More...  
Pdf (unsigned int dimension=0)  
Constructor. More...  
virtual  ~Pdf () 
Destructor. More...  
Protected Member Functions  
bool  CumPDFUpdate () 
Updates the cumPDF. More...  
bool  NormalizeProbs () 
Normalize all the probabilities (eg. after setting a probability) More...  
Protected Attributes  
vector< double >  _CumPDF 
STLvector containing the Cumulative PDF (for efficient sampling) More...  
unsigned int  _num_states 
The number of discrete state. More...  
vector< Probability > *  _Values_p 
Pointer to the discrete PDFvalues, the sum of the elements = 1. More...  
Class representing a PDF on a discrete variable.
This class is an instantation from the template class Pdf, with added methods to get a set the probability of a certain discrete value (methods only relevant for discrete pdfs)
Definition at line 34 of file mixtureParticleFilter.h.
BFL::DiscretePdf::DiscretePdf  (  unsigned int  num_states = 0  ) 
Constructor (dimension = number of classes) An equal probability is set for all classes.
num_states  number of different classes or states 
Definition at line 31 of file discretepdf.cpp.
BFL::DiscretePdf::DiscretePdf  (  const DiscretePdf &  my_dpdf  ) 
Copy Constructor.
Definition at line 47 of file discretepdf.cpp.

virtual 
Destructor.
Definition at line 59 of file discretepdf.cpp.

virtual 

protected 
Updates the cumPDF.
Definition at line 225 of file discretepdf.cpp.
int BFL::DiscretePdf::MostProbableStateGet  (  ) 
Get the index of the most probable state.
Definition at line 250 of file discretepdf.cpp.

protected 
Normalize all the probabilities (eg. after setting a probability)
Definition at line 207 of file discretepdf.cpp.
unsigned int BFL::DiscretePdf::NumStatesGet  (  )  const 
Get the number of discrete States.
Definition at line 74 of file discretepdf.cpp.
vector< Probability > BFL::DiscretePdf::ProbabilitiesGet  (  )  const 
Get all probabilities.
Definition at line 112 of file discretepdf.cpp.
bool BFL::DiscretePdf::ProbabilitiesSet  (  vector< Probability > &  values  ) 
Set all probabilities.
values  vector<Probability> containing the new probability values. The sum of the probabilities of this list is not required to be one since the normalization is automatically carried out. 
Definition at line 117 of file discretepdf.cpp.

virtual 
Implementation of virtual base class method.
Reimplemented from BFL::BFL::Pdf< int >.
Definition at line 80 of file discretepdf.cpp.
bool BFL::DiscretePdf::ProbabilitySet  (  int  state, 
Probability  a  
) 
Function to change/set the probability of a single state.
Changes the probabilities such that AFTER normalization the probability of the state "state" is equal to the probability a
state  number of state of which the probability will be set 
a  probability value to which the probability of state "state" will be set (must be <= 1) 
Definition at line 86 of file discretepdf.cpp.

virtual 
Draw multiple samples from the Pdf (overloaded)
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 gibbsiterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent... 
Reimplemented from BFL::BFL::Pdf< int >.
Definition at line 128 of file discretepdf.cpp.

virtual 
Draw 1 sample from the Pdf:
There's no need to create a list for only 1 sample!
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 
Reimplemented from BFL::BFL::Pdf< int >.
Definition at line 181 of file discretepdf.cpp.

protected 
STLvector containing the Cumulative PDF (for efficient sampling)
Definition at line 47 of file mixtureParticleFilter.h.

protected 
The number of discrete state.
Definition at line 38 of file mixtureParticleFilter.h.

protected 
Pointer to the discrete PDFvalues, the sum of the elements = 1.
Definition at line 41 of file mixtureParticleFilter.h.