#include <NoiseModel.h>

Inheritance diagram for gtsam::noiseModel::Diagonal:

[legend]

Public Types
typedef std::shared_ptr< Diagonal >	shared_ptr

Public Types inherited from gtsam::noiseModel::Gaussian
typedef std::shared_ptr< Gaussian >	shared_ptr

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

Public Member Functions
	Diagonal ()

double	invsigma (size_t i) const

const Vector &	invsigmas () const

double	precision (size_t i) const

const Vector &	precisions () const

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

Matrix	R () const override

double	sigma (size_t i) const

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

void	WhitenInPlace (Matrix &H) const override

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

	~Diagonal () override

Public Member Functions inherited from gtsam::noiseModel::Gaussian
virtual Matrix	covariance () const
	Compute covariance matrix. More...

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

	Gaussian (size_t dim=1, const std::optional< Matrix > &sqrt_information={})

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

virtual std::shared_ptr< Diagonal >	QR (Matrix &Ab) 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	Precisions (const Vector &precisions, bool smart=true)

static shared_ptr	Sigmas (const Vector &sigmas, bool smart=true)

static shared_ptr	Variances (const Vector &variances, bool smart=true)

Static Public Member Functions inherited from gtsam::noiseModel::Gaussian
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
	Diagonal (const Vector &sigmas)

Protected Attributes
Vector	invsigmas_

Vector	precisions_

Vector	sigmas_

Protected Attributes inherited from gtsam::noiseModel::Gaussian
std::optional< Matrix >	sqrt_information_

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

Detailed Description

A diagonal noise model implements a diagonal covariance matrix, with the elements of the diagonal specified in a Vector. This class has no public constructors, instead, use the static constructor functions Sigmas etc...

Definition at line 288 of file NoiseModel.h.

Member Typedef Documentation

◆ shared_ptr

typedef std::shared_ptr<Diagonal> gtsam::noiseModel::Diagonal::shared_ptr

Definition at line 307 of file NoiseModel.h.

Constructor & Destructor Documentation

◆ Diagonal() [1/2]

gtsam::noiseModel::Diagonal::Diagonal ( const Vector & sigmas )

protected

constructor to allow for disabling initialization of invsigmas

Definition at line 250 of file NoiseModel.cpp.

◆ Diagonal() [2/2]

gtsam::noiseModel::Diagonal::Diagonal ( )

constructor - no initializations, for serialization

Definition at line 244 of file NoiseModel.cpp.

◆ ~Diagonal()

gtsam::noiseModel::Diagonal::~Diagonal ( )

inlineoverride

Definition at line 309 of file NoiseModel.h.

Member Function Documentation

◆ invsigma()

double gtsam::noiseModel::Diagonal::invsigma ( size_t i ) const

inline

Definition at line 348 of file NoiseModel.h.

◆ invsigmas()

const Vector& gtsam::noiseModel::Diagonal::invsigmas ( ) const

inline

Return sqrt precisions

Definition at line 347 of file NoiseModel.h.

◆ precision()

double gtsam::noiseModel::Diagonal::precision ( size_t i ) const

inline

Definition at line 354 of file NoiseModel.h.

◆ Precisions()

Diagonal::shared_ptr gtsam::noiseModel::Diagonal::Precisions	(	const Vector &	precisions,
		bool	smart = `true`
	)

static

A diagonal noise model created by specifying a Vector of precisions, i.e. i.e. the diagonal of the information matrix, i.e., weights

Definition at line 287 of file NoiseModel.cpp.

◆ precisions()

const Vector& gtsam::noiseModel::Diagonal::precisions ( ) const

inline

Return precisions

Definition at line 353 of file NoiseModel.h.

◆ print()

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

overridevirtual

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 292 of file NoiseModel.cpp.

◆ R()

Matrix gtsam::noiseModel::Diagonal::R ( ) const

inlineoverridevirtual

Return R itself, but note that Whiten(H) is cheaper than R*H

Reimplemented from gtsam::noiseModel::Gaussian.

Definition at line 359 of file NoiseModel.h.

◆ sigma()

double gtsam::noiseModel::Diagonal::sigma ( size_t i ) const

inline

Return standard deviations (sqrt of diagonal)

Definition at line 342 of file NoiseModel.h.

◆ Sigmas()

Diagonal::shared_ptr gtsam::noiseModel::Diagonal::Sigmas	(	const Vector &	sigmas,
		bool	smart = `true`
	)

static

A diagonal noise model created by specifying a Vector of sigmas, i.e. standard deviations, the diagonal of the square root covariance matrix.

Definition at line 270 of file NoiseModel.cpp.

◆ sigmas()

Vector gtsam::noiseModel::Diagonal::sigmas ( ) const

inlineoverridevirtual

Calculate standard deviations.

Reimplemented from gtsam::noiseModel::Gaussian.

Definition at line 332 of file NoiseModel.h.

◆ unwhiten()

Vector gtsam::noiseModel::Diagonal::unwhiten ( const Vector & v ) const

overridevirtual

Unwhiten an error vector.

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 301 of file NoiseModel.cpp.

◆ Variances()

Diagonal::shared_ptr gtsam::noiseModel::Diagonal::Variances	(	const Vector &	variances,
		bool	smart = `true`
	)

static

A diagonal noise model created by specifying a Vector of variances, i.e. i.e. the diagonal of the covariance matrix.

Parameters

variances	A vector containing the variances of this noise model
smart	check if can be simplified to derived class

Definition at line 258 of file NoiseModel.cpp.

◆ whiten()

Vector gtsam::noiseModel::Diagonal::whiten ( const Vector & v ) const

overridevirtual

Whiten an error vector.

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 297 of file NoiseModel.cpp.

◆ Whiten()

Matrix gtsam::noiseModel::Diagonal::Whiten ( const Matrix & H ) const

overridevirtual

Multiply a derivative with R (derivative of whiten) Equivalent to whitening each column of the input matrix.

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 305 of file NoiseModel.cpp.

◆ WhitenInPlace() [1/2]

void gtsam::noiseModel::Diagonal::WhitenInPlace ( Matrix & H ) const

overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 309 of file NoiseModel.cpp.

◆ WhitenInPlace() [2/2]

void gtsam::noiseModel::Diagonal::WhitenInPlace ( Eigen::Block< Matrix > H ) const

overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Gaussian.

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

Definition at line 313 of file NoiseModel.cpp.

Member Data Documentation

◆ invsigmas_

Vector gtsam::noiseModel::Diagonal::invsigmas_

protected

Definition at line 296 of file NoiseModel.h.

◆ precisions_

Vector gtsam::noiseModel::Diagonal::precisions_

protected

Definition at line 296 of file NoiseModel.h.

◆ sigmas_

Vector gtsam::noiseModel::Diagonal::sigmas_

protected

Standard deviations (sigmas), their inverse and inverse square (weights/precisions) These are all computed at construction: the idea is to use one shared model where computation is done only once, the common use case in many problems.

Definition at line 296 of file NoiseModel.h.

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

Public Types

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ shared_ptr

Constructor & Destructor Documentation

◆ Diagonal() [1/2]

◆ Diagonal() [2/2]

◆ ~Diagonal()

Member Function Documentation

◆ invsigma()

◆ invsigmas()

◆ precision()

◆ Precisions()

◆ precisions()

◆ print()

◆ R()

◆ sigma()

◆ Sigmas()

◆ sigmas()

◆ unwhiten()

◆ Variances()

◆ whiten()

◆ Whiten()

◆ WhitenInPlace() [1/2]

◆ WhitenInPlace() [2/2]

Member Data Documentation

◆ invsigmas_

◆ precisions_

◆ sigmas_