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NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac Class Reference

Class for nonlinear analytic measurementmodels with additive gaussian noise. More...

#include <nonlinearanalyticmeasurementmodel_gaussianuncertainty_ginac.h>

Inheritance diagram for NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac:
AnalyticMeasurementModelGaussianUncertainty MeasurementModel< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector >

Public Member Functions

 NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac (NonLinearAnalyticConditionalGaussian_Ginac *const pdf)
 Constructor. More...
 
virtual ~NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac ()
 copy constructor More...
 
virtual MatrixWrapper::Matrix df_dxGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x)
 output stream for measurement model
 
virtual MatrixWrapper::ColumnVector PredictionGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x)
 Returns estimation of measurement.
 
virtual MatrixWrapper::SymmetricMatrix CovarianceGet (const MatrixWrapper::ColumnVector &u, const MatrixWrapper::ColumnVector &x)
 Returns covariance on the measurement.
 
GiNaC::matrix FunctionGet ()
 Get function.
 
vector< GiNaC::symbol > StateGet ()
 Get State symbols.
 
vector< GiNaC::symbol > InputGet ()
 Get input symbols.
 
vector< GiNaC::symbol > ConditionalGet ()
 Get conditional arguments.
 
int MeasurementSizeGet () const
 Get Measurement Size.
 
bool SystemWithoutSensorParams () const
 Number of Conditional Arguments.
 
ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * MeasurementPdfGet ()
 Get the MeasurementPDF.
 
void MeasurementPdfSet (ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > *pdf)
 Set the MeasurementPDF. More...
 
MatrixWrapper::ColumnVector Simulate (const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s, const SampleMthd sampling_method=SampleMthd::DEFAULT, void *sampling_args=NULL)
 Simulate the Measurement, given a certain state, and an input. More...
 
MatrixWrapper::ColumnVector Simulate (const MatrixWrapper::ColumnVector &x, const SampleMthd sampling_method=SampleMthd::DEFAULT, void *sampling_args=NULL)
 Simulate the system (no input system) More...
 
Probability ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x, const MatrixWrapper::ColumnVector &s)
 Get the probability of a certain measurement. More...
 
Probability ProbabilityGet (const MatrixWrapper::ColumnVector &z, const MatrixWrapper::ColumnVector &x)
 Get the probability of a certain measurement. More...
 

Protected Attributes

ConditionalPdf< MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector > * _MeasurementPdf
 ConditionalPdf representing $ P(Z_k | X_{k}, U_{k}) $.
 
bool _systemWithoutSensorParams
 System with no sensor params??
 

Detailed Description

Class for nonlinear analytic measurementmodels with additive gaussian noise.

This class represents all measurementmodels of the form

\[ h(x)=z \ or \ h(x,z)=0 \]

Definition at line 39 of file nonlinearanalyticmeasurementmodel_gaussianuncertainty_ginac.h.

Constructor & Destructor Documentation

◆ NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac()

Constructor.

Parameters
pdfconditional pdf, gaussian uncertainty

◆ ~NonLinearAnalyticMeasurementModelGaussianUncertainty_Ginac()

copy constructor

Destructor

Member Function Documentation

◆ MeasurementPdfSet()

void MeasurementPdfSet ( ConditionalPdf< MeasVar, StateVar > *  pdf)
inherited

Set the MeasurementPDF.

Parameters
pdfa pointer to the measurement pdf

◆ ProbabilityGet() [1/2]

Probability ProbabilityGet ( const MeasVar &  z,
const StateVar &  x 
)
inherited

Get the probability of a certain measurement.

(measurement independent of input) gived a certain state and input

Parameters
zthe measurement value
xx current state of the system
Returns
the "probability" of the measurement

◆ ProbabilityGet() [2/2]

Probability ProbabilityGet ( const MeasVar &  z,
const StateVar &  x,
const StateVar &  s 
)
inherited

Get the probability of a certain measurement.

given a certain state and input

Parameters
zthe measurement value
xcurrent state of the system
sthe sensor param value
Returns
the "probability" of the measurement

◆ Simulate() [1/2]

MatrixWrapper::ColumnVector Simulate ( const StateVar &  x,
const StateVar &  s,
const SampleMthd  sampling_method = SampleMthd::DEFAULT,
void *  sampling_args = NULL 
)
inherited

Simulate the Measurement, given a certain state, and an input.

Parameters
xcurrent state of the system
ssensor parameter
Returns
Measurement generated by simulating the measurement model
Parameters
sampling_methodthe sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
sampling_argsSometimes a sampling method can have some extra parameters (eg mcmc sampling)
Note
Maybe the return value would better be a Sample<StateVar> instead of a StateVar

◆ Simulate() [2/2]

MatrixWrapper::ColumnVector Simulate ( const StateVar &  x,
const SampleMthd  sampling_method = SampleMthd::DEFAULT,
void *  sampling_args = NULL 
)
inherited

Simulate the system (no input system)

Parameters
xcurrent state of the system
Returns
State where we arrive by simulating the measurement model
Note
Maybe the return value would better be a Sample<StateVar> instead of a StateVar
Parameters
sampling_methodthe sampling method to be used while sampling from the Conditional Pdf describing the system (if not specified = DEFAULT)
sampling_argsSometimes a sampling method can have some extra parameters (eg mcmc sampling)

The documentation for this class was generated from the following file: