Class PDF: Virtual Base class representing Probability Density Functions. More...

#include <mixtureParticleFilter.h>

Inheritance diagram for BFL::BFL::Pdf< T >:

[legend]

Public Member Functions
virtual Pdf< T > *	Clone () const =0
	Pure virtual clone function. More...

virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const
	Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf. More...

unsigned int	DimensionGet () const
	Get the dimension of the argument. More...

virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument. More...

virtual T	ExpectedValueGet () const
	Get the expected value E[x] of the pdf. More...

	Pdf (unsigned int dimension=0)
	Constructor. More...

virtual Probability	ProbabilityGet (const T &input) const
	Get the probability of a certain argument. More...

virtual bool	SampleFrom (vector< Sample< T > > &list_samples, const unsigned int num_samples, int method=DEFAULT, void *args=NULL) const
	Draw multiple samples from the Pdf (overloaded) More...

virtual bool	SampleFrom (Sample< T > &one_sample, int method=DEFAULT, void *args=NULL) const
	Draw 1 sample from the Pdf: More...

virtual	~Pdf ()
	Destructor. More...

Private Attributes
unsigned int	_dimension
	Dimension of the argument x of P(x \| ...). More...

Detailed Description

template<typename T>
class BFL::BFL::Pdf< T >

Class PDF: Virtual Base class representing Probability Density Functions.

Definition at line 53 of file mixtureParticleFilter.h.

Constructor & Destructor Documentation

◆ Pdf()

template<typename T >

BFL::Pdf< T >::Pdf ( unsigned int dimension = 0 )

Constructor.

Parameters

dimension int representing the number of rows of the state

Definition at line 150 of file mixtureParticleFilter.h.

◆ ~Pdf()

template<typename T >

BFL::Pdf< T >::~Pdf ( )

virtual

Destructor.

Definition at line 161 of file mixtureParticleFilter.h.

Member Function Documentation

◆ Clone()

template<typename T>

virtual Pdf<T>* BFL::BFL::Pdf< T >::Clone ( ) const

pure virtual

Pure virtual clone function.

◆ CovarianceGet()

template<typename T >

MatrixWrapper::SymmetricMatrix BFL::Pdf< T >::CovarianceGet ( ) const

virtual

Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.

Get first order statistic (Covariance) of this AnalyticPdf

Returns: The Covariance of the Pdf (a SymmetricMatrix of dim DIMENSION)

Todo:: extend this more general to n-th order statistic

Bug:: Discrete pdfs should not be able to use this!

Reimplemented in BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::NonLinearAnalyticConditionalGaussian_Ginac, BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::Gaussian, BFL::ConditionalGaussianAdditiveNoise, BFL::AnalyticConditionalGaussianAdditiveNoise, BFL::FilterProposalDensity, and BFL::OptimalImportanceDensity.

Definition at line 225 of file mixtureParticleFilter.h.

◆ DimensionGet()

template<typename T >

unsigned int BFL::Pdf< T >::DimensionGet ( ) const

inline

Get the dimension of the argument.

Returns: the dimension of the argument

Definition at line 169 of file mixtureParticleFilter.h.

◆ DimensionSet()

template<typename T >

void BFL::Pdf< T >::DimensionSet ( unsigned int dim )

virtual

Set the dimension of the argument.

Parameters

dim	the dimension

Definition at line 175 of file mixtureParticleFilter.h.

◆ ExpectedValueGet()

template<typename T >

T BFL::Pdf< T >::ExpectedValueGet ( ) const

virtual

Get the expected value E[x] of the pdf.

Get low order statistic (Expected Value) of this AnalyticPdf

Returns: The Expected Value of the Pdf (a ColumnVector with DIMENSION rows)

Note: No set functions here! This can be useful for analytic functions, but not for sample based representations!; For certain discrete Pdfs, this function has no meaning, what is the average between yes and no?

Reimplemented in BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::NonLinearAnalyticConditionalGaussian_Ginac, BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::MCPdf< T >, BFL::MCPdf< T >, BFL::Gaussian, BFL::LinearAnalyticConditionalGaussian, BFL::FilterProposalDensity, BFL::NonLinearAnalyticConditionalGaussianMobile, BFL::NonLinearAnalyticConditionalGaussianMobile, BFL::OptimalImportanceDensity, BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::Mixture< T >, and BFL::Mixture< T >.

Definition at line 215 of file mixtureParticleFilter.h.

◆ ProbabilityGet()

template<typename T>

Probability BFL::Pdf< T >::ProbabilityGet ( const T & input ) const

virtual

Get the probability of a certain argument.

Parameters

input T argument of the Pdf

Returns: the probability value of the argument

Reimplemented in BFL::DiscreteConditionalPdf, BFL::BFL::Mixture< T >, BFL::Mixture< T >, BFL::BFL::DiscretePdf, BFL::DiscretePdf, BFL::Gaussian, BFL::Uniform, BFL::ConditionalGaussian, BFL::ConditionalUniformMeasPdf1d, and BFL::NonlinearMeasurementPdf.

Definition at line 207 of file mixtureParticleFilter.h.

◆ SampleFrom() [1/2]

template<typename T>

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

virtual

Draw multiple samples from the Pdf (overloaded)

Parameters

list_samples	list of samples that will contain result of sampling
num_samples	Number of Samples to be drawn (iid)
method	Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
args	Pointer to a struct representing extra sample arguments. "Sample Arguments" can be anything (the number of steps a gibbs-iterator should take, the interval width in MCMC, ... (or nothing), so it is hard to give a meaning to what exactly Sample Arguments should represent...

Todo:: replace the C-call "void * args" by a more object-oriented structure: Perhaps something like virtual Sample * Sample (const int num_samples,class Sampler)

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

Reimplemented in BFL::BFL::Mixture< T >, BFL::BFL::MCPdf< T >, and BFL::BFL::DiscretePdf.

Definition at line 182 of file mixtureParticleFilter.h.

◆ SampleFrom() [2/2]

template<typename T>

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

virtual

Draw 1 sample from the Pdf:

There's no need to create a list for only 1 sample!

Parameters

one_sample	sample that will contain result of sampling
method	Sampling method to be used. Each sampling method is currently represented by a #define statement, eg. #define BOXMULLER 1
args	Pointer to a struct representing extra sample arguments

See also: SampleFrom()

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

Reimplemented in BFL::BFL::Mixture< T >, BFL::DiscreteConditionalPdf, BFL::BFL::MCPdf< T >, BFL::BFL::DiscretePdf, and BFL::DiscretePdf.

Definition at line 197 of file mixtureParticleFilter.h.

Member Data Documentation

◆ _dimension

template<typename T>

unsigned int BFL::BFL::Pdf< T >::_dimension

private

Dimension of the argument x of P(x | ...).

Definition at line 145 of file mixtureParticleFilter.h.

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

Public Member Functions

Private Attributes

Detailed Description

template<typename T> class BFL::BFL::Pdf< T >

Constructor & Destructor Documentation

◆ Pdf()

◆ ~Pdf()

Member Function Documentation

◆ Clone()

◆ CovarianceGet()

◆ DimensionGet()

◆ DimensionSet()

◆ ExpectedValueGet()

◆ ProbabilityGet()

◆ SampleFrom() [1/2]

◆ SampleFrom() [2/2]

Member Data Documentation

◆ _dimension

template<typename T>
class BFL::BFL::Pdf< T >