Bug List

Member BFL::AnalyticSystemModelGaussianUncertainty::df_dxGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x)

Should actually be defined for any continuous system model! There should be a class between this one and system model tout court, not assuming gaussian uncertainty!

Member BFL::BFL::Pdf< T >::CovarianceGet () const

Discrete pdfs should not be able to use this!

Member BFL::BFL::Pdf< T >::SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const

Sometimes the compiler doesn't know which method to choose!

Member BFL::BFL::Pdf< T >::SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const

Sometimes the compiler doesn't know which method to choose!

Class BFL::ConditionalPdf< Var, CondArg >

All conditional arguments should be of the same type T for now!

Member BFL::ConditionalPdf< Var, CondArg >::NumConditionalArgumentsSet (unsigned int numconditionalarguments)

will probably give rise to memory allocation problems if you herit from this class and do not redefine this method.

Member BFL::EKParticleFilter::EKParticleFilter (MCPdf< ColumnVector > *prior, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS)

prior should be of type pdf and not mcpdf. See also notes with implementation

Class BFL::Filter< StateVar, MeasVar >

For now, due to a "bug" (= non-existence of a feature :-) in the ConditionalPdf class, STATES AND INPUTS MUST BE OF THE SAME TYPE (both discrete, or both continuous! This means that you can use this class for the following model types:

• States, inputs and measurements continuous (most frequently used?)
• States and inputs continous, Measurements discrete
• States and inputs discrete, Measurements continous
• States, inputs and measurements discrete

Member BFL::Filter< StateVar, MeasVar >::Filter (const Filter< StateVar, MeasVar > &filt)

we should make a copy of the prior

we should make a copy of the pdf's too

Member BFL::FilterProposalDensity::FilterProposalDensity (const FilterProposalDensity &fpd)

Not implemented yet

Member BFL::LinearAnalyticConditionalGaussian::NumConditionalArgumentsSet (unsigned int numconditionalarguments)

This method is not implemented, we can ReSize the std::vector<BFL::Matrix>, but we don't know the dimensions of the matrices self. So this will most certainly result in a segfault. Anyway, why would you need this?

Class BFL::MixtureParticleFilter< StateVar, MeasVar >

Resampling is not implemented generically enough yet. There's only the possibility to choose between static period resampling and dynamic resampling as proposed by Jun Liu. The correct way of implementing this would be to create a virtual function that has to be implemented by the user, but this creates more hassle for the user (a different particle filter for each scheme).

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::DynamicResampleStepOne (int component)

let the user implement her/his own resamplescheme

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::MaintainMixtureStep ()

let the user implement her/his own mixture maintaince scheme

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::MixtureParticleFilter (Mixture< StateVar > *prior, Mixture< StateVar > *post, ConditionalPdf< StateVar, StateVar > *proposal, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS, int maintainMixturePeriod=1)

prior should be of type pdf and not mcpdf. See also notes with implementation

let the user implement her/his own resamplescheme

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::MixtureParticleFilter (const MixtureParticleFilter< StateVar, MeasVar > &filt)

implementation probably contains a bug

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::MixtureParticleFilter (Mixture< StateVar > *prior, ConditionalPdf< StateVar, StateVar > *proposal, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS, int maintainMixturePeriod=1)

prior should be of type pdf and not mcpdf. See also notes with implementation

let the user implement her/his own resamplescheme

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::ProposalStepInternal (SystemModel< StateVar > *const sysmodel, const StateVar &u, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s)

Make sampling method variable. See implementation.

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::ProposalStepInternalOne (int component, SystemModel< StateVar > *const sysmodel, const StateVar &u, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s)

Make sampling method variable. See implementation.

Member BFL::MixtureParticleFilter< StateVar, MeasVar >::StaticResampleStep ()

let the user implement her/his own resamplescheme

Class BFL::NonLinearAnalyticConditionalGaussian_Ginac

: This class is higly biased towards filtering applications.

Member BFL::NonLinearAnalyticConditionalGaussian_Ginac::dfGet (unsigned int i) const

only implemented for i = 0 for now (so in a filter context, only the derivative with respect to x is implemented

Class BFL::ParticleFilter< StateVar, MeasVar >

Resampling is not implemented generically enough yet. There's only the possibility to choose between static period resampling and dynamic resampling as proposed by Jun Liu. The correct way of implementing this would be to create a virtual function that has to be implemented by the user, but this creates more hassle for the user (a different particle filter for each scheme).

Member BFL::ParticleFilter< StateVar, MeasVar >::DynamicResampleStep ()

let the user implement her/his own resamplescheme

Member BFL::ParticleFilter< StateVar, MeasVar >::ParticleFilter (MCPdf< StateVar > *prior, MCPdf< StateVar > *post, ConditionalPdf< StateVar, StateVar > *proposal, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS)

prior should be of type pdf and not mcpdf. See also notes with implementation

let the user implement her/his own resamplescheme

Member BFL::ParticleFilter< StateVar, MeasVar >::ParticleFilter (MCPdf< StateVar > *prior, ConditionalPdf< StateVar, StateVar > *proposal, int resampleperiod=0, double resamplethreshold=0, int resamplescheme=DEFAULT_RS)

prior should be of type pdf and not mcpdf. See also notes with implementation

let the user implement her/his own resamplescheme

Member BFL::ParticleFilter< StateVar, MeasVar >::ParticleFilter (const ParticleFilter< StateVar, MeasVar > &filt)

implementation probably contains a bug

Member BFL::ParticleFilter< StateVar, MeasVar >::ProposalStepInternal (SystemModel< StateVar > *const sysmodel, const StateVar &u, MeasurementModel< MeasVar, StateVar > *const measmodel, const MeasVar &z, const StateVar &s)

Make sampling method variable. See implementation.

Member BFL::ParticleFilter< StateVar, MeasVar >::StaticResampleStep ()

let the user implement her/his own resamplescheme

Member BFL::Pdf< T >::CovarianceGet () const

Discrete pdfs should not be able to use this!

Member BFL::Pdf< T >::SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const

Sometimes the compiler doesn't know which method to choose!

Member BFL::Pdf< T >::SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const

Sometimes the compiler doesn't know which method to choose!

Class BFL::SystemModel< T >

Currently supports only systemmodels of the form P(x | x, u), where both u and x are continu or discrete. So it lacks support for mixed systems () and systems with extra parameters. You are welcome to provide an API and implementation for this :-)