This virtual class defines the interface that any particles based PDF class must implement in order to be executed by a mrpt::bayes::CParticleFilter.
See the Particle Filter tutorial explaining how to use the particle filter-related classes.
- See Also
- CParticleFilter, CParticleFilterData
Definition at line 46 of file CParticleFilterCapable.h.
#include <mrpt/bayes/CParticleFilterCapable.h>
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| | CParticleFilterCapable () |
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| virtual | ~CParticleFilterCapable () |
| | Virtual destructor.
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| void | prepareFastDrawSample (const bayes::CParticleFilter::TParticleFilterOptions &PF_options, TParticleProbabilityEvaluator partEvaluator=defaultEvaluator, const void *action=NULL, const void *observation=NULL) const |
| | Prepares data structures for calling fastDrawSample method next.
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| size_t | fastDrawSample (const bayes::CParticleFilter::TParticleFilterOptions &PF_options) const |
| | Draws a random sample from the particle filter, in such a way that each particle has a probability proportional to its weight (in the standard PF algorithm).
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| virtual double | getW (size_t i) const =0 |
| | Access to i'th particle (logarithm) weight, where first one is index 0.
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| virtual void | setW (size_t i, double w)=0 |
| | Modifies i'th particle (logarithm) weight, where first one is index 0.
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| virtual size_t | particlesCount () const =0 |
| | Get the m_particles count.
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| void | prediction_and_update (const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs the prediction stage of the Particle Filter.
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| virtual void | performSubstitution (const std::vector< size_t > &indx)=0 |
| | Performs the substitution for internal use of resample in particle filter algorithm, don't call it directly.
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| virtual double | normalizeWeights (double *out_max_log_w=NULL)=0 |
| | Normalize the (logarithmic) weights, such as the maximum weight is zero.
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| virtual double | ESS ()=0 |
| | Returns the normalized ESS (Estimated Sample Size), in the range [0,1].
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| void | performResampling (const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs a resample of the m_particles, using the method selected in the constructor.
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| static double | defaultEvaluator (const bayes::CParticleFilter::TParticleFilterOptions &PF_options, const CParticleFilterCapable *obj, size_t index, const void *action, const void *observation) |
| | The default evaluator function, which simply returns the particle weight.
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| static void | computeResampling (CParticleFilter::TParticleResamplingAlgorithm method, const vector_double &in_logWeights, std::vector< size_t > &out_indexes) |
| | A static method to perform the computation of the samples resulting from resampling a given set of particles, given their logarithmic weights, and a resampling method.
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| static void | log2linearWeights (const vector_double &in_logWeights, vector_double &out_linWeights) |
| | A static method to compute the linear, normalized (the sum the unity) weights from log-weights.
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| virtual void | prediction_and_update_pfStandardProposal (const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs the particle filter prediction/update stages for the algorithm "pfStandardProposal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).
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| virtual void | prediction_and_update_pfAuxiliaryPFStandard (const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs the particle filter prediction/update stages for the algorithm "pfAuxiliaryPFStandard" (if not implemented in heritated class, it will raise a 'non-implemented' exception).
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| virtual void | prediction_and_update_pfOptimalProposal (const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs the particle filter prediction/update stages for the algorithm "pfOptimalProposal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).
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| virtual void | prediction_and_update_pfAuxiliaryPFOptimal (const mrpt::slam::CActionCollection *action, const mrpt::slam::CSensoryFrame *observation, const bayes::CParticleFilter::TParticleFilterOptions &PF_options) |
| | Performs the particle filter prediction/update stages for the algorithm "pfAuxiliaryPFOptimal" (if not implemented in heritated class, it will raise a 'non-implemented' exception).
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A callback function type for evaluating the probability of m_particles of being selected, used in "fastDrawSample".
The default evaluator function "defaultEvaluator" simply returns the particle weight.
- Parameters
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| index | This is the index of the particle its probability is being computed. |
| action | The value of this is the parameter passed to "prepareFastDrawSample" |
| observation | The value of this is the parameter passed to "prepareFastDrawSample" The action and the observation are declared as "void*" for a greater flexibility. |
- See Also
- prepareFastDrawSample
Definition at line 73 of file CParticleFilterCapable.h.
| mrpt::bayes::CParticleFilterCapable::CParticleFilterCapable |
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| virtual mrpt::bayes::CParticleFilterCapable::~CParticleFilterCapable |
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inlinevirtual |
A static method to perform the computation of the samples resulting from resampling a given set of particles, given their logarithmic weights, and a resampling method.
It returns the sequence of indexes from the resampling. The number of output samples is the same than the input population. This generic method just computes these indexes, to actually perform a resampling in a particle filter object, call performResampling
- See Also
- performResampling
| virtual double mrpt::bayes::CParticleFilterCapable::ESS |
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Returns the normalized ESS (Estimated Sample Size), in the range [0,1].
Note that you do NOT need to normalize the weights before calling this.
Draws a random sample from the particle filter, in such a way that each particle has a probability proportional to its weight (in the standard PF algorithm).
This method can be used to generate a variable number of m_particles when resampling: to vary the number of m_particles in the filter. See prepareFastDrawSample for more information, or the Particle Filter tutorial.
NOTES:
- You MUST call "prepareFastDrawSample" ONCE before calling this method. That method must be called after modifying the particle filter (executing one step, resampling, etc...)
- This method returns ONE index for the selected ("drawn") particle, in the range [0,M-1]
- You do not need to call "normalizeWeights" before calling this.
- See Also
- prepareFastDrawSample
| virtual double mrpt::bayes::CParticleFilterCapable::getW |
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size_t |
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const |
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pure virtual |
Access to i'th particle (logarithm) weight, where first one is index 0.
Referenced by defaultEvaluator().
| static void mrpt::bayes::CParticleFilterCapable::log2linearWeights |
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const vector_double & |
in_logWeights, |
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vector_double & |
out_linWeights |
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A static method to compute the linear, normalized (the sum the unity) weights from log-weights.
- See Also
- performResampling
| virtual double mrpt::bayes::CParticleFilterCapable::normalizeWeights |
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double * |
out_max_log_w = NULL | ) |
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Normalize the (logarithmic) weights, such as the maximum weight is zero.
- Parameters
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| out_max_log_w | If provided, will return with the maximum log_w before normalizing, such as new_weights = old_weights - max_log_w. |
- Returns
- The max/min ratio of weights ("dynamic range")
| virtual size_t mrpt::bayes::CParticleFilterCapable::particlesCount |
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Get the m_particles count.
Performs a resample of the m_particles, using the method selected in the constructor.
After computing the surviving samples, this method internally calls "performSubstitution" to actually perform the particle replacement. This method is called automatically by CParticleFilter::execute, andshould not be invoked manually normally. To just obtaining the sequence of resampled indexes from a sequence of weights, use "resample"
- See Also
- resample
| virtual void mrpt::bayes::CParticleFilterCapable::performSubstitution |
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const std::vector< size_t > & |
indx | ) |
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pure virtual |
Performs the substitution for internal use of resample in particle filter algorithm, don't call it directly.
- Parameters
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| indx | The indices of current m_particles to be saved as the new m_particles set. |
Prepares data structures for calling fastDrawSample method next.
This method must be called once before using "fastDrawSample" (calling this more than once has no effect, but it takes time for nothing!) The behavior depends on the configuration of the PF (see CParticleFilter::TParticleFilterOptions):
- DYNAMIC SAMPLE SIZE=NO: In this case this method fills out an internal array (m_fastDrawAuxiliary.alreadyDrawnIndexes) with the random indexes generated according to the selected resample scheme in TParticleFilterOptions. Those indexes are read sequentially by subsequent calls to fastDrawSample.
- DYNAMIC SAMPLE SIZE=YES: Then:
- If TParticleFilterOptions.resamplingMethod = prMultinomial, the internal buffers will be filled out (m_fastDrawAuxiliary.CDF, CDF_indexes & PDF) and then fastDrawSample can be called an arbitrary number of times to generate random indexes.
- For the rest of resampling algorithms, an exception will be raised since they are not appropriate for a dynamic (unknown in advance) number of particles.
The function pointed by "partEvaluator" should take into account the particle filter algorithm selected in "m_PFAlgorithm". If called without arguments (defaultEvaluator), the default behavior is to draw samples with a probability proportional to their current weights. The action and the observation are declared as "void*" for a greater flexibility. For a more detailed information see the Particle Filter tutorial. Custom supplied "partEvaluator" functions must take into account the previous particle weight, i.e. multiplying the current observation likelihood by the weights.
- See Also
- fastDrawSample
| virtual void mrpt::bayes::CParticleFilterCapable::setW |
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size_t |
i, |
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double |
w |
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pure virtual |
Modifies i'th particle (logarithm) weight, where first one is index 0.
| const unsigned mrpt::bayes::CParticleFilterCapable::PARTICLE_FILTER_CAPABLE_FAST_DRAW_BINS |
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staticprivate |
