Namespaces | |
| BFL | |
| MatrixWrapper | |
Classes | |
| class | AnalyticConditionalGaussian |
| Abstract Class representing all FULL Analytical Conditional gaussians. More... | |
| class | AnalyticConditionalGaussianAdditiveNoise |
| Abstract Class representing all full Analytical Conditional gaussians with Additive Gaussian Noise. More... | |
| class | AnalyticMeasurementModelGaussianUncertainty |
| class | AnalyticSystemModelGaussianUncertainty |
| Class for analytic system models with additive Gauss. uncertainty. More... | |
| class | ASIRFilter |
| ASIR: Auxiliary Particle Filter. More... | |
| class | BackwardFilter |
| Virtual Baseclass representing all bayesian backward filters. More... | |
| class | bflToolkitPlugin |
| class | BootstrapFilter |
| Particular particle filter : Proposal PDF = SystemPDF. More... | |
| class | ConditionalGaussian |
| Abstract Class representing all Conditional gaussians. More... | |
| class | ConditionalGaussianAdditiveNoise |
| Abstract Class representing all Conditional Gaussians with additive gaussian noise. More... | |
| class | ConditionalPdf |
| Abstract Class representing conditional Pdfs P(x | ...) More... | |
| class | ConditionalUniformMeasPdf1d |
| class | DiscreteConditionalPdf |
| Abstract Class representing all FULLY Discrete Conditional PDF's. More... | |
| class | DiscretePdf |
| Class representing a PDF on a discrete variable. More... | |
| class | DiscreteSystemModel |
| Class for discrete System Models. More... | |
| class | EKFProposalDensity |
| Proposal Density for non-linear systems with additive Gaussian Noise (using a EKF Filter) More... | |
| class | EKFTest |
| class | EKParticleFilter |
| Particle filter using EKF for proposal step. More... | |
| class | ExtendedKalmanFilter |
| class | Filter |
| Abstract class representing an interface for Bayesian Filters. More... | |
| class | FilterProposalDensity |
| Proposal Density for non-linear systems with additive Gaussian Noise (using a (analytic) Filter) More... | |
| class | Gaussian |
| Class representing Gaussian (or normal density) More... | |
| struct | get_size |
| class | HistogramFilter |
| Class representing the histogram filter. More... | |
| class | InnovationCheck |
| Class implementing an innovationCheck used in IEKF. More... | |
| class | IteratedExtendedKalmanFilter |
| class | KalmanFilter |
| Class representing the family of all Kalman Filters (EKF, IEKF, ...) More... | |
| class | LinearAnalyticConditionalGaussian |
| Linear Conditional Gaussian. More... | |
| class | LinearAnalyticMeasurementModelGaussianUncertainty |
| Class for linear analytic measurementmodels with additive gaussian noise. More... | |
| class | LinearAnalyticMeasurementModelGaussianUncertainty_Implicit |
| Class for linear analytic measurementmodels with additive gaussian noise. More... | |
| class | LinearAnalyticSystemModelGaussianUncertainty |
| Class for linear analytic systemmodels with additive gaussian noise. More... | |
| struct | matrix_i_j_constructor |
| struct | matrix_index |
| struct | MatrixAssignChecker |
| struct | MatrixIndexChecker |
| struct | MatrixTypeInfo |
| class | MCPdf |
| Monte Carlo Pdf: Sample based implementation of Pdf. More... | |
| class | MeasurementModel |
| class | Mixture |
| Class representing a mixture of PDFs, the mixture can contain different. More... | |
| class | MixtureBootstrapFilter |
| Particular mixture particle filter : Proposal PDF = SystemPDF. More... | |
| class | MixtureParticleFilter |
| Virtual Class representing all Mixture particle filters. More... | |
| class | MobileRobot |
| This is a class simulating a mobile robot. More... | |
| class | NonLinearAnalyticConditionalGaussian_Ginac |
| Conditional Gaussian for an analytic nonlinear system using Ginac: More... | |
| class | NonLinearAnalyticConditionalGaussianMobile |
| Non Linear Conditional Gaussian. More... | |
| class | NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac |
| Class for nonlinear analytic measurementmodels with additive gaussian noise. More... | |
| class | NonLinearAnalyticSystemModelGaussianUncertainty_Ginac |
| Class for nonlinear analytic systemmodels with additive gaussian noise. More... | |
| class | NonlinearMeasurementPdf |
| Non Linear Conditional Gaussian. More... | |
| class | NonlinearSystemPdf |
| Non Linear Conditional Gaussian. More... | |
| class | NonminimalKalmanFilter |
| class | OptimalImportanceDensity |
| Optimal importance density for Nonlinear Gaussian SS Models. More... | |
| class | Optimalimportancefilter |
| Particular particle filter: Proposal PDF = Optimal Importance function. More... | |
| class | ParticleFilter |
| Virtual Class representing all particle filters. More... | |
| class | ParticleSmoother |
| Class representing a particle backward filter. More... | |
| class | |
| Class PDF: Virtual Base class representing Probability Density Functions. More... | |
| class | Probability |
| Class representing a probability (a double between 0 and 1) More... | |
| struct | Probability_ctor |
| struct | ProbabilityTypeInfo |
| class | RauchTungStriebel |
| Class representing all Rauch-Tung-Striebel backward filters. More... | |
| struct | rget_size |
| struct | rvector_index |
| struct | rvector_index_constructor |
| struct | RVectorTypeInfo |
| class | Sample |
| struct | Sample_ctor |
| struct | SampleTypeInfo |
| class | SRIteratedExtendedKalmanFilter |
| struct | symmetricMatrix_index_constructor |
| struct | SymmetricMatrixTypeInfo |
| class | SystemModel |
| class | Uniform |
| Class representing uniform density. More... | |
| struct | vector_index |
| struct | vector_index_constructor |
| struct | VectorAssignChecker |
| struct | VectorTypeInfo |
| class | WeightedSample |
| struct | WeightedSample_ctor |
| struct | WeightedSampleTypeInfo |
Functions | |
| template<class T > | |
| bool | composeProperty (const PropertyBag &bag, Sample< T > &sample) |
| template<class T > | |
| bool | composeProperty (const PropertyBag &bag, WeightedSample< T > &weightedSample) |
| template<class T > | |
| void | decomposeProperty (const Sample< T > &sample, PropertyBag &targetbag) |
| template<class T > | |
| void | decomposeProperty (const WeightedSample< T > &weightedSample, PropertyBag &targetbag) |
| std::ostream & | operator<< (std::ostream &os, const Uniform &u) |
| ostream & | operator<< (ostream &stream, Probability &prob) |
| std::ostream & | operator<< (std::ostream &os, const Gaussian &g) |
| std::ostream & | operator<< (std::ostream &os, NonLinearAnalyticConditionalGaussian_Ginac &p) |
| template<typename S > | |
| ostream & | operator<< (ostream &stream, WeightedSample< S > &mws) |
| template<typename S > | |
| ostream & | operator<< (ostream &stream, Sample< S > &my_sample) |
| istream & | operator>> (istream &stream, Probability &prob) |
| template<typename S > | |
| istream & | operator>> (istream &stream, Sample< S > &my_sample) |
| double | rnorm (const double &mu, const double &sigma) |
| double | runif () |
| double | runif (const double &min, const double &max) |
Variables | |
| bflToolkitPlugin | bflToolkit |
| bool BFL::composeProperty | ( | const PropertyBag & | bag, |
| Sample< T > & | sample | ||
| ) |
A composeProperty method for composing a property of a vector<T> The dimension of the vector must be less than 100.
Definition at line 95 of file SampleComposition.hpp.
| bool BFL::composeProperty | ( | const PropertyBag & | bag, |
| WeightedSample< T > & | weightedSample | ||
| ) |
A composeProperty method for composing a property of a vector<T> The dimension of the vector must be less than 100.
Definition at line 224 of file SampleComposition.hpp.
| void BFL::decomposeProperty | ( | const Sample< T > & | sample, |
| PropertyBag & | targetbag | ||
| ) |
A decomposePropertyBag method for decomposing a sample<T> into a PropertyBag with Property<T>'s.
Definition at line 62 of file SampleComposition.hpp.
| void BFL::decomposeProperty | ( | const WeightedSample< T > & | weightedSample, |
| PropertyBag & | targetbag | ||
| ) |
A decomposePropertyBag method for decomposing a sample<T> into a PropertyBag with Property<T>'s.
Definition at line 188 of file SampleComposition.hpp.
| std::ostream& BFL::operator<< | ( | std::ostream & | os, |
| const Uniform & | u | ||
| ) |
Definition at line 54 of file uniform.cpp.
| ostream& BFL::operator<< | ( | ostream & | stream, |
| Probability & | prob | ||
| ) |
Definition at line 62 of file bfl_toolkit.cpp.
| std::ostream& BFL::operator<< | ( | std::ostream & | os, |
| const Gaussian & | g | ||
| ) |
Definition at line 62 of file gaussian.cpp.
| std::ostream& BFL::operator<< | ( | std::ostream & | os, |
| NonLinearAnalyticConditionalGaussian_Ginac & | p | ||
| ) |
Definition at line 116 of file nonlinearanalyticconditionalgaussian_ginac.cpp.
| ostream& BFL::operator<< | ( | ostream & | stream, |
| WeightedSample< S > & | mws | ||
| ) |
| stream | the stream to be returned |
| mws | the weighted sample to be printed |
Definition at line 116 of file weightedsample.h.
| ostream& BFL::operator<< | ( | ostream & | stream, |
| Sample< S > & | my_sample | ||
| ) |
| istream& BFL::operator>> | ( | istream & | stream, |
| Probability & | prob | ||
| ) |
Definition at line 68 of file bfl_toolkit.cpp.
| istream& BFL::operator>> | ( | istream & | stream, |
| Sample< S > & | my_sample | ||
| ) |
| double BFL::rnorm | ( | const double & | mu, |
| const double & | sigma | ||
| ) |
| double BFL::runif | ( | ) |
| double BFL::runif | ( | const double & | min, |
| const double & | max | ||
| ) |
| bflToolkitPlugin BFL::bflToolkit |
Definition at line 85 of file bfl_toolkit.cpp.