MRPT  1.9.9
mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE > Class Template Referenceabstract

Detailed Description

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
class mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >

A base class for implementing rejection sampling in a generic state space.

See the main method CRejectionSamplingCapable::rejectionSampling To use this class, create your own class as a child of this one and implement the desired virtual methods, and add any required internal data.

Definition at line 30 of file CRejectionSamplingCapable.h.

#include <mrpt/bayes/CRejectionSamplingCapable.h>

Inheritance diagram for mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >:
Inheritance graph

Public Types

using TParticle = CProbabilityParticle< TStateSpace, STORAGE >
 

Public Member Functions

virtual ~CRejectionSamplingCapable ()
 Virtual destructor. More...
 
void rejectionSampling (size_t desiredSamples, std::vector< TParticle > &outSamples, size_t timeoutTrials=1000)
 Generates a set of N independent samples via rejection sampling. More...
 

Protected Member Functions

virtual void RS_drawFromProposal (TStateSpace &outSample)=0
 Generates one sample, drawing from some proposal distribution. More...
 
virtual double RS_observationLikelihood (const TStateSpace &x)=0
 Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the state space (values in the range [0,1]). More...
 

Member Typedef Documentation

◆ TParticle

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
using mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >::TParticle = CProbabilityParticle<TStateSpace,STORAGE>

Definition at line 33 of file CRejectionSamplingCapable.h.

Constructor & Destructor Documentation

◆ ~CRejectionSamplingCapable()

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
virtual mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >::~CRejectionSamplingCapable ( )
inlinevirtual

Virtual destructor.

Definition at line 37 of file CRejectionSamplingCapable.h.

Member Function Documentation

◆ rejectionSampling()

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
void mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >::rejectionSampling ( size_t  desiredSamples,
std::vector< TParticle > &  outSamples,
size_t  timeoutTrials = 1000 
)
inline

Generates a set of N independent samples via rejection sampling.

Parameters
desiredSamplesThe number of desired samples to generate
outSamplesThe output samples.
timeoutTrialsThe maximum number of rejection trials for each generated sample (i.e. the maximum number of iterations). This can be used to set a limit to the time complexity of the algorithm for difficult probability densities. All will have equal importance weights (a property of rejection sampling), although those samples generated at timeout will have a different importance weights.

Definition at line 49 of file CRejectionSamplingCapable.h.

◆ RS_drawFromProposal()

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
virtual void mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >::RS_drawFromProposal ( TStateSpace &  outSample)
protectedpure virtual

Generates one sample, drawing from some proposal distribution.

Implemented in mrpt::slam::CRejectionSamplingRangeOnlyLocalization.

Referenced by mrpt::bayes::CRejectionSamplingCapable< CPose2D >::rejectionSampling().

◆ RS_observationLikelihood()

template<class TStateSpace, mrpt::bayes::particle_storage_mode STORAGE = mrpt::bayes::particle_storage_mode::POINTER>
virtual double mrpt::bayes::CRejectionSamplingCapable< TStateSpace, STORAGE >::RS_observationLikelihood ( const TStateSpace &  x)
protectedpure virtual

Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the state space (values in the range [0,1]).

Implemented in mrpt::slam::CRejectionSamplingRangeOnlyLocalization.

Referenced by mrpt::bayes::CRejectionSamplingCapable< CPose2D >::rejectionSampling().




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