Class representing Gaussian (or normal density) More...

#include <gaussian.h>

Inheritance diagram for BFL::Gaussian:

Public Member Functions
virtual Gaussian *	Clone () const
	Clone function. More...

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

void	CovarianceSet (const MatrixWrapper::SymmetricMatrix &cov)
	Set the Covariance Matrix. More...

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

void	ExpectedValueSet (const MatrixWrapper::ColumnVector &mu)
	Set the Expected Value. More...

	Gaussian (const MatrixWrapper::ColumnVector &Mu, const MatrixWrapper::SymmetricMatrix &Sigma)
	Constructor. More...

	Gaussian (int dimension=0)
	constructor with only dimensions or nothing More...

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

bool	SampleFrom (vector< Sample< MatrixWrapper::ColumnVector > > &list_samples, const int num_samples, int method=DEFAULT, void *args=NULL) const

virtual bool	SampleFrom (Sample< MatrixWrapper::ColumnVector > &one_sample, int method=DEFAULT, void *args=NULL) const

virtual	~Gaussian ()
	Default Copy Constructor will do. More...

Public Member Functions inherited from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >
unsigned int	DimensionGet () const
	Get the dimension of the argument. More...

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

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

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

virtual	~Pdf ()
	Destructor. More...

Private Attributes
ColumnVector	_diff

Matrix	_Low_triangle

MatrixWrapper::ColumnVector	_Mu

ColumnVector	_samples

ColumnVector	_sampleValue

MatrixWrapper::SymmetricMatrix	_Sigma

bool	_Sigma_changed

MatrixWrapper::SymmetricMatrix	_Sigma_inverse

double	_sqrt_pow

ColumnVector	_tempColumn

Friends
std::ostream &	operator<< (std::ostream &os, const Gaussian &g)
	output stream for Gaussian More...

Detailed Description

Class representing Gaussian (or normal density)

Definition at line 27 of file gaussian.h.

Constructor & Destructor Documentation

◆ Gaussian() [1/2]

BFL::Gaussian::Gaussian	(	const MatrixWrapper::ColumnVector &	Mu,
		const MatrixWrapper::SymmetricMatrix &	Sigma
	)

Constructor.

Parameters

Mu	Mean Vector of the Gaussian
Sigma	Covariance Matrix of the Gaussian

◆ Gaussian() [2/2]

BFL::Gaussian::Gaussian ( int dimension = 0 )

constructor with only dimensions or nothing

Definition at line 46 of file gaussian.cpp.

◆ ~Gaussian()

BFL::Gaussian::~Gaussian ( )

virtual

Default Copy Constructor will do.

Destructor

Definition at line 60 of file gaussian.cpp.

Member Function Documentation

◆ Clone()

Gaussian * BFL::Gaussian::Clone ( ) const

virtual

Clone function.

Implements BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 70 of file gaussian.cpp.

◆ CovarianceGet()

SymmetricMatrix BFL::Gaussian::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 from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 187 of file gaussian.cpp.

◆ CovarianceSet()

void BFL::Gaussian::CovarianceSet ( const MatrixWrapper::SymmetricMatrix & cov )

Set the Covariance Matrix.

Set the Covariance Matrix

Parameters

cov	The new Covariance matrix

Definition at line 204 of file gaussian.cpp.

◆ ExpectedValueGet()

ColumnVector BFL::Gaussian::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 from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 181 of file gaussian.cpp.

◆ ExpectedValueSet()

void BFL::Gaussian::ExpectedValueSet ( const MatrixWrapper::ColumnVector & mu )

Set the Expected Value.

Set the Expected Value

Parameters

mu	The new Expected Value

Definition at line 193 of file gaussian.cpp.

◆ ProbabilityGet()

Probability BFL::Gaussian::ProbabilityGet ( const MatrixWrapper::ColumnVector & 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 from BFL::BFL::Pdf< MatrixWrapper::ColumnVector >.

Definition at line 75 of file gaussian.cpp.

◆ SampleFrom() [1/2]

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

◆ SampleFrom() [2/2]

virtual bool BFL::Gaussian::SampleFrom	(	Sample< MatrixWrapper::ColumnVector > &	one_sample,
		int	method = `DEFAULT`,
		void *	args = `NULL`
	)		const

virtual

Friends And Related Function Documentation

◆ operator<<

std::ostream& operator<<	(	std::ostream &	os,
		const Gaussian &	g
	)

friend

output stream for Gaussian

Definition at line 62 of file gaussian.cpp.

Member Data Documentation

◆ _diff

ColumnVector BFL::Gaussian::_diff

mutableprivate

Definition at line 37 of file gaussian.h.

◆ _Low_triangle

Matrix BFL::Gaussian::_Low_triangle

mutableprivate

Definition at line 42 of file gaussian.h.

◆ _Mu

MatrixWrapper::ColumnVector BFL::Gaussian::_Mu

private

Definition at line 30 of file gaussian.h.

◆ _samples

ColumnVector BFL::Gaussian::_samples

mutableprivate

Definition at line 40 of file gaussian.h.

◆ _sampleValue

ColumnVector BFL::Gaussian::_sampleValue

mutableprivate

Definition at line 41 of file gaussian.h.

◆ _Sigma

MatrixWrapper::SymmetricMatrix BFL::Gaussian::_Sigma

private

Definition at line 31 of file gaussian.h.

◆ _Sigma_changed

bool BFL::Gaussian::_Sigma_changed

mutableprivate

Definition at line 34 of file gaussian.h.

◆ _Sigma_inverse

MatrixWrapper::SymmetricMatrix BFL::Gaussian::_Sigma_inverse

mutableprivate

Definition at line 35 of file gaussian.h.

◆ _sqrt_pow

double BFL::Gaussian::_sqrt_pow

mutableprivate

Definition at line 36 of file gaussian.h.

◆ _tempColumn

ColumnVector BFL::Gaussian::_tempColumn

mutableprivate

Definition at line 38 of file gaussian.h.

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

Public Member Functions

Private Attributes

Friends

Detailed Description

Constructor & Destructor Documentation

◆ Gaussian() [1/2]

◆ Gaussian() [2/2]

◆ ~Gaussian()

Member Function Documentation

◆ Clone()

◆ CovarianceGet()

◆ CovarianceSet()

◆ ExpectedValueGet()

◆ ExpectedValueSet()

◆ ProbabilityGet()

◆ SampleFrom() [1/2]

◆ SampleFrom() [2/2]

Friends And Related Function Documentation

◆ operator<<

Member Data Documentation

◆ _diff

◆ _Low_triangle

◆ _Mu

◆ _samples

◆ _sampleValue

◆ _Sigma

◆ _Sigma_changed

◆ _Sigma_inverse

◆ _sqrt_pow

◆ _tempColumn