#include <NoiseModel.h>

Inheritance diagram for gtsam::noiseModel::Constrained:

[legend]

Public Types
typedef std::shared_ptr< Constrained >	shared_ptr

Public Types inherited from gtsam::noiseModel::Diagonal
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
	Constrained (const Vector &sigmas=Z_1x1)

bool	constrained (size_t i) const
	Return true if a particular dimension is free or constrained. More...

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

const Vector &	mu () const
	Access mu as a vector. More...

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

Diagonal::shared_ptr	QR (Matrix &Ab) const override

double	squaredMahalanobisDistance (const Vector &v) const override

shared_ptr	unit () const

Matrix	Whiten (const Matrix &H) const override

Vector	whiten (const Vector &v) const override
	Calculates error vector with weights applied. More...

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

void	WhitenInPlace (Matrix &H) const override

	~Constrained () override

Public Member Functions inherited from gtsam::noiseModel::Diagonal
	Diagonal ()

double	invsigma (size_t i) const

const Vector &	invsigmas () const

double	precision (size_t i) const

const Vector &	precisions () const

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...

	~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...

double	logDeterminant () const
	Compute the log of \|Σ\|. More...

double	negLogConstant () const
	Compute the negative log of the normalization constant for a Gaussian noise model k = 1/\sqrt(\|2πΣ\|). More...

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

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

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

void	WhitenSystem (std::vector< Matrix > &A, 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	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 Vector	unweightedWhiten (const Vector &v) const

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

virtual void	unwhitenInPlace (Vector &v) const

virtual double	weight (const Vector &v) const

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

virtual void	whitenInPlace (Vector &v) const

virtual	~Base ()

Static Public Member Functions
static shared_ptr	All (size_t dim)

static shared_ptr	All (size_t dim, const Vector &mu)

static shared_ptr	All (size_t dim, double mu)

static shared_ptr	MixedPrecisions (const Vector &mu, const Vector &precisions)

static shared_ptr	MixedPrecisions (const Vector &precisions)

static shared_ptr	MixedSigmas (const Vector &mu, const Vector &sigmas)

static shared_ptr	MixedSigmas (const Vector &sigmas)

static shared_ptr	MixedSigmas (double m, const Vector &sigmas)

static shared_ptr	MixedVariances (const Vector &mu, const Vector &variances)

static shared_ptr	MixedVariances (const Vector &variances)

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

Protected Member Functions inherited from gtsam::noiseModel::Diagonal
	Diagonal (const Vector &sigmas)

virtual double	logDetR () const override
	Compute the log of \|R\|. Used for computing log(\|Σ\|) More...

Protected Attributes
Vector	mu_
	Penalty function weight - needs to be large enough to dominate soft constraints. More...

Protected Attributes inherited from gtsam::noiseModel::Diagonal
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 Constrained constrained model is a specialization of Diagonal which allows some or all of the sigmas to be zero, forcing the error to be zero there. All other Gaussian models are guaranteed to have a non-singular square-root information matrix, but this class is specifically equipped to deal with singular noise models, specifically: whiten will return zero on those components that have zero sigma and zero error, unchanged otherwise.

While a hard constraint may seem to be a case in which there is infinite error, we do not ever produce an error value of infinity to allow for constraints to actually be optimized rather than self-destructing if not initialized correctly.

Definition at line 404 of file NoiseModel.h.

Member Typedef Documentation

◆ shared_ptr

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

Definition at line 419 of file NoiseModel.h.

Constructor & Destructor Documentation

◆ Constrained() [1/2]

gtsam::noiseModel::Constrained::Constrained	(	const Vector &	mu,
		const Vector &	sigmas
	)

protected

Constructor that prevents any inf values from appearing in invsigmas or precisions. Allows for specifying mu.

Definition at line 370 of file NoiseModel.cpp.

◆ Constrained() [2/2]

gtsam::noiseModel::Constrained::Constrained ( const Vector & sigmas = Z_1x1 )

protected constructor takes sigmas. prevents any inf values from appearing in invsigmas or precisions. mu set to large default value (1000.0)

Definition at line 364 of file NoiseModel.cpp.

◆ ~Constrained()

gtsam::noiseModel::Constrained::~Constrained ( )

inlineoverride

Definition at line 429 of file NoiseModel.h.

Member Function Documentation

◆ All() [1/3]

static shared_ptr gtsam::noiseModel::Constrained::All ( size_t dim )

inlinestatic

Fully constrained variations

Definition at line 480 of file NoiseModel.h.

◆ All() [2/3]

static shared_ptr gtsam::noiseModel::Constrained::All	(	size_t	dim,
		const Vector &	mu
	)

inlinestatic

Fully constrained variations

Definition at line 485 of file NoiseModel.h.

◆ All() [3/3]

static shared_ptr gtsam::noiseModel::Constrained::All	(	size_t	dim,
		double	mu
	)

inlinestatic

Fully constrained variations with a mu parameter

Definition at line 490 of file NoiseModel.h.

◆ constrained()

bool gtsam::noiseModel::Constrained::constrained ( size_t i ) const

Return true if a particular dimension is free or constrained.

Definition at line 382 of file NoiseModel.cpp.

◆ isConstrained()

bool gtsam::noiseModel::Constrained::isConstrained ( ) const

inlineoverridevirtual

true if a constrained noise mode, saves slow/clumsy dynamic casting

Reimplemented from gtsam::noiseModel::Base.

Definition at line 432 of file NoiseModel.h.

◆ MixedPrecisions() [1/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedPrecisions	(	const Vector &	mu,
		const Vector &	precisions
	)

static

A diagonal noise model created by specifying a Vector of precisions, some of which might be inf

Definition at line 428 of file NoiseModel.cpp.

◆ MixedPrecisions() [2/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedPrecisions ( const Vector & precisions )

static

Definition at line 432 of file NoiseModel.cpp.

◆ MixedSigmas() [1/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas	(	const Vector &	mu,
		const Vector &	sigmas
	)

static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 376 of file NoiseModel.cpp.

◆ MixedSigmas() [2/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas ( const Vector & sigmas )

static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 411 of file NoiseModel.cpp.

◆ MixedSigmas() [3/3]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedSigmas	(	double	m,
		const Vector &	sigmas
	)

static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 415 of file NoiseModel.cpp.

◆ MixedVariances() [1/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedVariances	(	const Vector &	mu,
		const Vector &	variances
	)

static

A diagonal noise model created by specifying a Vector of standard devations, some of which might be zero

Definition at line 420 of file NoiseModel.cpp.

◆ MixedVariances() [2/2]

Constrained::shared_ptr gtsam::noiseModel::Constrained::MixedVariances ( const Vector & variances )

static

Definition at line 424 of file NoiseModel.cpp.

◆ mu()

const Vector& gtsam::noiseModel::Constrained::mu ( ) const

inline

Access mu as a vector.

Definition at line 438 of file NoiseModel.h.

◆ print()

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

overridevirtual

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 388 of file NoiseModel.cpp.

◆ QR()

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

overridevirtual

Apply QR factorization to the system [A b], taking into account constraints 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

Ab	is the m*(n+1) augmented system matrix [A b]

Returns: diagonal noise model can be all zeros, mixed, or not-constrained

Reimplemented from gtsam::noiseModel::Gaussian.

Definition at line 502 of file NoiseModel.cpp.

◆ squaredMahalanobisDistance()

double gtsam::noiseModel::Constrained::squaredMahalanobisDistance ( const Vector & v ) const

overridevirtual

The squaredMahalanobisDistance function for a constrained noisemodel, for non-constrained versions, uses sigmas, otherwise uses the penalty function with mu

Reimplemented from gtsam::noiseModel::Base.

Definition at line 437 of file NoiseModel.cpp.

◆ unit()

Constrained::shared_ptr gtsam::noiseModel::Constrained::unit ( ) const

Returns a Unit version of a constrained noisemodel in which constrained sigmas remain constrained and the rest are unit scaled

Definition at line 469 of file NoiseModel.cpp.

◆ Whiten()

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

overridevirtual

Whitening functions will perform partial whitening on rows with a non-zero sigma. Other rows remain untouched.

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 446 of file NoiseModel.cpp.

◆ whiten()

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

overridevirtual

Calculates error vector with weights applied.

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 394 of file NoiseModel.cpp.

◆ WhitenInPlace() [1/2]

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

overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 462 of file NoiseModel.cpp.

◆ WhitenInPlace() [2/2]

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

overridevirtual

In-place version

Reimplemented from gtsam::noiseModel::Diagonal.

Definition at line 455 of file NoiseModel.cpp.

Member Data Documentation

◆ mu_

Vector gtsam::noiseModel::Constrained::mu_

protected

Penalty function weight - needs to be large enough to dominate soft constraints.

Definition at line 408 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

◆ Constrained() [1/2]

◆ Constrained() [2/2]

◆ ~Constrained()

Member Function Documentation

◆ All() [1/3]

◆ All() [2/3]

◆ All() [3/3]

◆ constrained()

◆ isConstrained()

◆ MixedPrecisions() [1/2]

◆ MixedPrecisions() [2/2]

◆ MixedSigmas() [1/3]

◆ MixedSigmas() [2/3]

◆ MixedSigmas() [3/3]

◆ MixedVariances() [1/2]

◆ MixedVariances() [2/2]

◆ mu()

◆ print()

◆ QR()

◆ squaredMahalanobisDistance()

◆ unit()

◆ Whiten()

◆ whiten()

◆ WhitenInPlace() [1/2]

◆ WhitenInPlace() [2/2]

Member Data Documentation

◆ mu_