BFL::Pdf< T > Class Template Reference

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

#include <pdf.h>

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::Pdf< T >

Class PDF: Virtual Base class representing Probability Density Functions.

Definition at line 53 of file pdf.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

~Pdf()

template<typename T>

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

virtual

Destructor.

Member Function Documentation

Clone()

template<typename T>

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

pure virtual

Pure virtual clone function.

CovarianceGet()

template<typename T>

virtual 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!

DimensionGet()

template<typename T>

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

(

)

const

Get the dimension of the argument.

Returns

the dimension of the argument

DimensionSet()

template<typename T>

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

virtual

Set the dimension of the argument.

Parameters

dim	the dimension

ExpectedValueGet()

template<typename T>

virtual 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?

ProbabilityGet()

template<typename T>

virtual 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

SampleFrom() [1/2]

template<typename T>

virtual 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!

SampleFrom() [2/2]

template<typename T>

virtual 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!

Member Data Documentation

_dimension

template<typename T>

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

private

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

Definition at line 145 of file pdf.h.

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

• pdf.h