#include <NoiseModel.h>

Inheritance diagram for gtsam::noiseModel::Gaussian:

[legend]

Public Types
typedef boost::shared_ptr< Gaussian >	shared_ptr

Public Types inherited from gtsam::noiseModel::Base
typedef boost::shared_ptr< Base >	shared_ptr

Public Member Functions
virtual Matrix	covariance () const
	Compute covariance matrix. More...

bool	equals (const Base &expected, double tol=1e-9) const override

virtual Matrix	information () const
	Compute information matrix. More...

void	print (const std::string &name) const override

virtual boost::shared_ptr< Diagonal >	QR (Matrix &Ab) const

virtual Matrix	R () const
	Return R itself, but note that Whiten(H) is cheaper than R*H. More...

Vector	sigmas () const override
	Calculate standard deviations. More...

Vector	unwhiten (const Vector &v) const override
	Unwhiten an error vector. More...

Vector	whiten (const Vector &v) const override
	Whiten an error vector. More...

Matrix	Whiten (const Matrix &H) const override

virtual void	WhitenInPlace (Matrix &H) const

virtual void	WhitenInPlace (Eigen::Block< Matrix > H) const

void	WhitenSystem (std::vector< Matrix > &A, Vector &b) const override

void	WhitenSystem (Matrix &A, Vector &b) const override

void	WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const override

void	WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const override

	~Gaussian () override

Public Member Functions inherited from gtsam::noiseModel::Base
	Base (size_t dim=1)
	primary constructor More...

size_t	dim () const
	Dimensionality. More...

virtual bool	isConstrained () const
	true if a constrained noise model, saves slow/clumsy dynamic casting More...

virtual bool	isUnit () const
	true if a unit noise model, saves slow/clumsy dynamic casting More...

virtual double	loss (const double squared_distance) const
	loss function, input is Mahalanobis distance More...

virtual double	mahalanobisDistance (const Vector &v) const
	Mahalanobis distance. More...

virtual double	squaredMahalanobisDistance (const Vector &v) const
	Squared Mahalanobis distance v'R'Rv = <Rv,R*v> More...

virtual Vector	unweightedWhiten (const Vector &v) const

virtual void	unwhitenInPlace (Vector &v) const

virtual void	unwhitenInPlace (Eigen::Block< Vector > &v) const

virtual double	weight (const Vector &v) const

virtual void	whitenInPlace (Vector &v) const

virtual void	whitenInPlace (Eigen::Block< Vector > &v) const

virtual	~Base ()

Static Public Member Functions
static shared_ptr	Covariance (const Matrix &covariance, bool smart=true)

static shared_ptr	Information (const Matrix &M, bool smart=true)

static shared_ptr	SqrtInformation (const Matrix &R, bool smart=true)

Protected Member Functions
	Gaussian (size_t dim=1, const boost::optional< Matrix > &sqrt_information=boost::none)

Protected Attributes
boost::optional< Matrix >	sqrt_information_

Protected Attributes inherited from gtsam::noiseModel::Base
size_t	dim_

Private Member Functions
template<class ARCHIVE >
void	serialize (ARCHIVE &ar, const unsigned int)

const Matrix &	thisR () const

Friends
class	boost::serialization::access

Detailed Description

Gaussian implements the mathematical model |R*x|^2 = |y|^2 with R'*R=inv(Sigma) where y = whiten(x) = R*x x = unwhiten(x) = inv(R)*y as indeed |y|^2 = y'*y = x'*R'*R*x Various derived classes are available that are more efficient. The named constructors return a shared_ptr because, when the smart flag is true, the underlying object might be a derived class such as Diagonal.

Definition at line 162 of file NoiseModel.h.

Member Typedef Documentation

typedef boost::shared_ptr<Gaussian> gtsam::noiseModel::Gaussian::shared_ptr

Definition at line 189 of file NoiseModel.h.

Constructor & Destructor Documentation

gtsam::noiseModel::Gaussian::Gaussian	(	size_t	dim = `1`,
		const boost::optional< Matrix > &	sqrt_information = `boost::none`
	)

inlineprotected

protected constructor takes square root information matrix

Definition at line 183 of file NoiseModel.h.

gtsam::noiseModel::Gaussian::~Gaussian ( )

inlineoverride

Definition at line 191 of file NoiseModel.h.

Member Function Documentation

Gaussian::shared_ptr gtsam::noiseModel::Gaussian::Covariance	(	const Matrix &	covariance,
		bool	smart = `true`
	)

static

A Gaussian noise model created by specifying a covariance matrix.

Parameters

covariance	The square covariance Matrix
smart	check if can be simplified to derived class

Definition at line 116 of file NoiseModel.cpp.

Matrix gtsam::noiseModel::Gaussian::covariance ( ) const

virtual

Compute covariance matrix.

Definition at line 149 of file NoiseModel.cpp.

bool gtsam::noiseModel::Gaussian::equals	(	const Base &	expected,
		double	tol = `1e-9`
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 141 of file NoiseModel.cpp.

Gaussian::shared_ptr gtsam::noiseModel::Gaussian::Information	(	const Matrix &	M,
		bool	smart = `true`
	)

static

A Gaussian noise model created by specifying an information matrix.

Parameters

M	The information matrix
smart	check if can be simplified to derived class

Definition at line 99 of file NoiseModel.cpp.

virtual Matrix gtsam::noiseModel::Gaussian::information ( ) const

inlinevirtual

Compute information matrix.

Definition at line 259 of file NoiseModel.h.

void gtsam::noiseModel::Gaussian::print ( const std::string & name ) const

overridevirtual

Implements gtsam::noiseModel::Base.

Reimplemented in gtsam::noiseModel::Unit, gtsam::noiseModel::Isotropic, gtsam::noiseModel::Constrained, and gtsam::noiseModel::Diagonal.

Definition at line 136 of file NoiseModel.cpp.

SharedDiagonal gtsam::noiseModel::Gaussian::QR ( Matrix & Ab ) const

virtual

Apply appropriately weighted QR factorization to the system [A b] Q' * [A b] = [R d] Dimensions: (r*m) * m*(n+1) = r*(n+1), where r = min(m,n). This routine performs an in-place factorization on Ab. Below-diagonal elements are set to zero by this routine.

Parameters