MipBaselib::Gaussian Class Reference
[Probability Density Functions (PDF) and Hypotesis Densities (PHD)]

Provides a class to represent the generic 2D Gaussian pdf. More...

#include <Gaussian.h>

Inheritance diagram for MipBaselib::Gaussian:

List of all members.

Public Member Functions
	Gaussian ()
	Default Constructor.
	Gaussian (DCol m, DMat &c)
	Complete Constructor.
	Gaussian (const Gaussian &g)
	Copy Constructor.
int	dim ()
	Gets the dimension.
void	operator= (const Gaussian &g)
	Operator =.
DCol	expectedValue ()
	Returns the expected value.
DCol	expectedValue (const int n)
	Returns the first n elements of the expected value.
Decimal	covariance (int row, int col)
	Returns the (row-th, col-th) element of the covariance matrix.
DMat &	covariance ()
	Returns the covariance matrix as a vector of vector with the appropriate size.
DMat	covariance (const int n) const
	Returns the covariance matrix of the first n elements of the random vector.
Decimal	evaluate (DCol p)
	Returns the the value of the pdf in the given position.
Gaussian	marginalize (int n)
	Returns a Gaussian marginalized to the first n random variables.
void	printCovInv ()
	Print the invese of the covariance.
virtual string	print ()
	Returns the the value of the pdf in the given position.
Protected Member Functions
void	_computeCovInv ()
Protected Attributes
DCol	_mean
DMat	_cov
DMat	_covInv
bool	_covInvComputed

---

Detailed Description

Provides a class to represent the generic 2D Gaussian pdf.

Author:

Paolo Stegagno

---

Constructor & Destructor Documentation

MipBaselib::Gaussian::Gaussian

(

)

Default Constructor.

MipBaselib::Gaussian::Gaussian	(	DCol	m,
		DMat &	c
	)

Complete Constructor.

Parameters:

[in]	m	Mean, default (0 0)'.
[in]	&c	Pointer to a covariance matrix, default (1 0; 0 1) when c==NULL.

MipBaselib::Gaussian::Gaussian

(

const Gaussian &

g

)

Copy Constructor.

Parameters:

[in]

&g

Copied Gaussian.

---

Member Function Documentation

void MipBaselib::Gaussian::_computeCovInv

(

)

[protected]

int MipBaselib::Gaussian::dim

(

)

Gets the dimension.

void MipBaselib::Gaussian::operator=

(

const Gaussian &

g

)

Operator =.

Parameters:

[in]

&g

Copied Gaussian.

DCol MipBaselib::Gaussian::expectedValue

(

)

[virtual]

Returns the expected value.

Implements MipBaselib::PDF.

DCol MipBaselib::Gaussian::expectedValue

(

const int

n

)

Returns the first n elements of the expected value.

Parameters:

[in]

n

Number of requested elements.

Decimal MipBaselib::Gaussian::covariance	(	int	row,
		int	col
	)			[virtual]

Returns the (row-th, col-th) element of the covariance matrix.

Parameters:

[in]	row	Requested row.
[in]	col	Requested column.

Implements MipBaselib::PDF.

DMat & MipBaselib::Gaussian::covariance

(

)

Returns the covariance matrix as a vector of vector with the appropriate size.

DMat MipBaselib::Gaussian::covariance

(

const int

n

)

const

Returns the covariance matrix of the first n elements of the random vector.

Decimal MipBaselib::Gaussian::evaluate

(

DCol

p

)

[virtual]

Returns the the value of the pdf in the given position.

Parameters:

[in]

col

Requested position.

Implements MipBaselib::PDF.

Gaussian MipBaselib::Gaussian::marginalize

(

int

n

)

Returns a Gaussian marginalized to the first n random variables.

Parameters:

[in]

n

Requested number of components.

void MipBaselib::Gaussian::printCovInv

(

)

Print the invese of the covariance.

Parameters:

[in]

col

Requested position.

string MipBaselib::Gaussian::print

(

)

[virtual]

Returns the the value of the pdf in the given position.

Parameters:

[in]

col

Requested position.

Reimplemented in MipBaselib::GaussianComponent.

---

Member Data Documentation

DCol MipBaselib::Gaussian::_mean [protected]

DMat MipBaselib::Gaussian::_cov [protected]

DMat MipBaselib::Gaussian::_covInv [protected]

bool MipBaselib::Gaussian::_covInvComputed [protected]

---

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

• baselib/PDFs/Gaussian.h
• baselib/PDFs/Gaussian.cpp