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

#include <gaussian.h>

Inheritance diagram for BFL::Gaussian:

Public Member Functions
virtual Gaussian *	Clone () const
	Clone function.
virtual MatrixWrapper::SymmetricMatrix	CovarianceGet () const
	Get the Covariance Matrix E[(x - E[x])^2] of the Analytic pdf.
void	CovarianceSet (const MatrixWrapper::SymmetricMatrix &cov)
	Set the Covariance Matrix.
virtual void	DimensionSet (unsigned int dim)
	Set the dimension of the argument.
virtual MatrixWrapper::ColumnVector	ExpectedValueGet () const
	Get the expected value E[x] of the pdf.
void	ExpectedValueSet (const MatrixWrapper::ColumnVector &mu)
	Set the Expected Value.
	Gaussian (const MatrixWrapper::ColumnVector &Mu, const MatrixWrapper::SymmetricMatrix &Sigma)
	Constructor.
	Gaussian (int dimension=0)
	constructor with only dimensions or nothing
virtual Probability	ProbabilityGet (const MatrixWrapper::ColumnVector &input) const
	Get the probability of a certain argument.
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.
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

Detailed Description

Class representing Gaussian (or normal density)

Definition at line 27 of file gaussian.h.

Constructor & Destructor Documentation

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

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

constructor with only dimensions or nothing

Definition at line 46 of file gaussian.cpp.

BFL::Gaussian::~Gaussian ( ) [virtual]

Default Copy Constructor will do.

Destructor

Definition at line 60 of file gaussian.cpp.

Member Function Documentation

Gaussian * BFL::Gaussian::Clone ( ) const [virtual]

Clone function.

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

Definition at line 70 of file gaussian.cpp.

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.

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.

void BFL::Gaussian::DimensionSet ( unsigned int dim ) [virtual]

Set the dimension of the argument.

Parameters:

dim	the dimension

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

Definition at line 216 of file gaussian.cpp.

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.

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.

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.

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

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

Friends And Related Function Documentation

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

ColumnVector BFL::Gaussian::_diff [mutable, private]

Definition at line 37 of file gaussian.h.

Matrix BFL::Gaussian::_Low_triangle [mutable, private]

Definition at line 42 of file gaussian.h.

MatrixWrapper::ColumnVector BFL::Gaussian::_Mu [private]

Definition at line 30 of file gaussian.h.

ColumnVector BFL::Gaussian::_samples [mutable, private]

Definition at line 40 of file gaussian.h.

ColumnVector BFL::Gaussian::_sampleValue [mutable, private]

Definition at line 41 of file gaussian.h.

MatrixWrapper::SymmetricMatrix BFL::Gaussian::_Sigma [private]

Definition at line 31 of file gaussian.h.

bool BFL::Gaussian::_Sigma_changed [mutable, private]

Definition at line 34 of file gaussian.h.

MatrixWrapper::SymmetricMatrix BFL::Gaussian::_Sigma_inverse [mutable, private]

Definition at line 35 of file gaussian.h.

double BFL::Gaussian::_sqrt_pow [mutable, private]

Definition at line 36 of file gaussian.h.

ColumnVector BFL::Gaussian::_tempColumn [mutable, private]

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

Member Function Documentation

Friends And Related Function Documentation

Member Data Documentation