#include <GaussianFactor.h>

Inheritance diagram for gtsam::GaussianFactor:

[legend]

Public Types
typedef Factor	Base
	Our base class. More...

typedef boost::shared_ptr< This >	shared_ptr
	shared_ptr to this class More...

typedef GaussianFactor	This
	This class. More...

Public Types inherited from gtsam::Factor
typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys. More...

typedef KeyVector::iterator	iterator
	Iterator over keys. More...

Public Member Functions
virtual Matrix	augmentedInformation () const =0

virtual Matrix	augmentedJacobian () const =0

virtual GaussianFactor::shared_ptr	clone () const =0

virtual bool	empty () const =0

virtual bool	equals (const GaussianFactor &lf, double tol=1e-9) const =0

virtual double	error (const VectorValues &c) const =0

	GaussianFactor ()

template<typename CONTAINER >
	GaussianFactor (const CONTAINER &keys)

virtual DenseIndex	getDim (const_iterator variable) const =0

virtual Vector	gradient (Key key, const VectorValues &x) const =0
	Gradient wrt a key at any values. More...

virtual VectorValues	gradientAtZero () const =0
	A'*b for Jacobian, eta for Hessian. More...

virtual void	gradientAtZero (double *d) const =0
	Raw memory access version of gradientAtZero. More...

virtual std::map< Key, Matrix >	hessianBlockDiagonal () const =0
	Return the block diagonal of the Hessian for this factor. More...

VectorValues	hessianDiagonal () const
	Return the diagonal of the Hessian for this factor. More...

virtual void	hessianDiagonal (double *d) const =0
	Raw memory access version of hessianDiagonal. More...

virtual void	hessianDiagonalAdd (VectorValues &d) const =0
	Add the current diagonal to a VectorValues instance. More...

virtual Matrix	information () const =0

virtual std::pair< Matrix, Vector >	jacobian () const =0

virtual void	multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const =0
	y += alpha * A'Ax More...

virtual GaussianFactor::shared_ptr	negate () const =0

void	print (const std::string &s="", const KeyFormatter &formatter=DefaultKeyFormatter) const override=0
	print More...

virtual void	updateHessian (const KeyVector &keys, SymmetricBlockMatrix *info) const =0

virtual	~GaussianFactor ()

Public Member Functions inherited from gtsam::Factor
virtual	~Factor ()=default
	Default destructor. More...

Key	front () const
	First key. More...

Key	back () const
	Last key. More...

const_iterator	find (Key key) const
	find More...

const KeyVector &	keys () const
	Access the factor's involved variable keys. More...

const_iterator	begin () const

const_iterator	end () const

size_t	size () const

virtual void	printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const
	print only keys More...

KeyVector &	keys ()

iterator	begin ()

iterator	end ()

Static Public Member Functions
template<typename CONTAINER >
static DenseIndex	Slot (const CONTAINER &keys, Key key)

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

Friends
class	boost::serialization::access

Additional Inherited Members
Protected Member Functions inherited from gtsam::Factor
	Factor ()

template<typename CONTAINER >
	Factor (const CONTAINER &keys)

template<typename ITERATOR >
	Factor (ITERATOR first, ITERATOR last)

bool	equals (const This &other, double tol=1e-9) const
	check equality More...

Static Protected Member Functions inherited from gtsam::Factor
template<typename CONTAINER >
static Factor	FromKeys (const CONTAINER &keys)

template<typename ITERATOR >
static Factor	FromIterators (ITERATOR first, ITERATOR last)

Protected Attributes inherited from gtsam::Factor
KeyVector	keys_
	The keys involved in this factor. More...

Detailed Description

An abstract virtual base class for JacobianFactor and HessianFactor. A GaussianFactor has a quadratic error function. GaussianFactor is non-mutable (all methods const!). The factor value is exp(-0.5*||Ax-b||^2)

Definition at line 38 of file GaussianFactor.h.

Member Typedef Documentation

typedef Factor gtsam::GaussianFactor::Base

Our base class.

Definition at line 43 of file GaussianFactor.h.

typedef boost::shared_ptr<This> gtsam::GaussianFactor::shared_ptr

shared_ptr to this class

Definition at line 42 of file GaussianFactor.h.

typedef GaussianFactor gtsam::GaussianFactor::This

This class.

Definition at line 41 of file GaussianFactor.h.

Constructor & Destructor Documentation

gtsam::GaussianFactor::GaussianFactor ( )

inline

Default constructor creates empty factor

Definition at line 46 of file GaussianFactor.h.

template<typename CONTAINER >

gtsam::GaussianFactor::GaussianFactor ( const CONTAINER & keys )

inline

Construct from container of keys. This constructor is used internally from derived factor constructors, either from a container of keys or from a boost::assign::list_of.

Definition at line 51 of file GaussianFactor.h.

virtual gtsam::GaussianFactor::~GaussianFactor ( )

inlinevirtual

Destructor

Definition at line 54 of file GaussianFactor.h.

Member Function Documentation

virtual Matrix gtsam::GaussianFactor::augmentedInformation ( ) const

pure virtual

Return the augmented information matrix represented by this GaussianFactor. The augmented information matrix contains the information matrix with an additional column holding the information vector, and an additional row holding the transpose of the information vector. The lower-right entry contains the constant error term (when $\delta x = 0$ ). The augmented information matrix is described in more detail in HessianFactor, which in fact stores an augmented information matrix.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual Matrix gtsam::GaussianFactor::augmentedJacobian ( ) const

pure virtual

Return a dense $[ \;A\;b\; ] \in \mathbb{R}^{m \times n+1}$ Jacobian matrix, augmented with b with the noise models baked into A and b. The negative log-likelihood is $\frac{1}{2} \Vert Ax-b \Vert^2$ . See also GaussianFactorGraph::jacobian and GaussianFactorGraph::sparseJacobian.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual GaussianFactor::shared_ptr gtsam::GaussianFactor::clone ( ) const

pure virtual

Clone a factor (make a deep copy)

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::LinearInequality, gtsam::LinearEquality, gtsam::LinearCost, and gtsam::DummyFactor< CAMERA >.

virtual bool gtsam::GaussianFactor::empty ( ) const

pure virtual

Test whether the factor is empty

Implemented in gtsam::JacobianFactor, gtsam::RegularImplicitSchurFactor< CAMERA >, and gtsam::HessianFactor.

virtual bool gtsam::GaussianFactor::equals	(	const GaussianFactor &	lf,
		double	tol = `1e-9`
	)		const

pure virtual

Equals for testable

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::LinearInequality, gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::GaussianConditional, gtsam::LinearEquality, and gtsam::LinearCost.

virtual double gtsam::GaussianFactor::error ( const VectorValues & c ) const

pure virtual

Print for testable

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::LinearInequality, gtsam::LinearEquality, and gtsam::LinearCost.

virtual DenseIndex gtsam::GaussianFactor::getDim ( const_iterator variable ) const

pure virtual

0.5*(A*x-b)'D(A*x-b) Return the dimension of the variable pointed to by the given key iterator

Implemented in gtsam::JacobianFactor, gtsam::HessianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual Vector gtsam::GaussianFactor::gradient	(	Key	key,
		const VectorValues &	x
	)		const

pure virtual

Gradient wrt a key at any values.

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::JacobianFactor, and gtsam::HessianFactor.

virtual VectorValues gtsam::GaussianFactor::gradientAtZero ( ) const

pure virtual

A'*b for Jacobian, eta for Hessian.

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::JacobianFactor, gtsam::HessianFactor, and gtsam::RegularJacobianFactor< D >.

virtual void gtsam::GaussianFactor::gradientAtZero ( double * d ) const

pure virtual

Raw memory access version of gradientAtZero.

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::JacobianFactor, gtsam::HessianFactor, gtsam::RegularHessianFactor< D >, and gtsam::RegularJacobianFactor< D >.

virtual std::map<Key,Matrix> gtsam::GaussianFactor::hessianBlockDiagonal ( ) const

pure virtual

Return the block diagonal of the Hessian for this factor.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

VectorValues gtsam::GaussianFactor::hessianDiagonal ( ) const

Return the diagonal of the Hessian for this factor.

Definition at line 27 of file GaussianFactor.cpp.

virtual void gtsam::GaussianFactor::hessianDiagonal ( double * d ) const

pure virtual

Raw memory access version of hessianDiagonal.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::RegularHessianFactor< D >, gtsam::RegularImplicitSchurFactor< CAMERA >, and gtsam::RegularJacobianFactor< D >.

virtual void gtsam::GaussianFactor::hessianDiagonalAdd ( VectorValues & d ) const

pure virtual

Add the current diagonal to a VectorValues instance.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual Matrix gtsam::GaussianFactor::information ( ) const

pure virtual

Return the non-augmented information matrix represented by this GaussianFactor.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual std::pair<Matrix,Vector> gtsam::GaussianFactor::jacobian ( ) const

pure virtual

Return the dense Jacobian $ A $ and right-hand-side $ b $ , with the noise models baked into A and b. The negative log-likelihood is $\frac{1}{2} \Vert Ax-b \Vert^2$ . See also GaussianFactorGraph::augmentedJacobian and GaussianFactorGraph::sparseJacobian.

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, and gtsam::RegularImplicitSchurFactor< CAMERA >.

virtual void gtsam::GaussianFactor::multiplyHessianAdd	(	double	alpha,
		const VectorValues &	x,
		VectorValues &	y
	)		const

pure virtual

y += alpha * A'*A*x

Implemented in gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::RegularHessianFactor< D >, and gtsam::RegularJacobianFactor< D >.

virtual GaussianFactor::shared_ptr gtsam::GaussianFactor::negate ( ) const

pure virtual

Construct the corresponding anti-factor to negate information stored stored in this factor.

Returns: a HessianFactor with negated Hessian matrices

Implemented in gtsam::JacobianFactor, gtsam::RegularImplicitSchurFactor< CAMERA >, and gtsam::HessianFactor.

void gtsam::GaussianFactor::print	(	const std::string &	s = `""`,
		const KeyFormatter &	formatter = `DefaultKeyFormatter`
	)		const

overridepure virtual

print

Reimplemented from gtsam::Factor.

Implemented in gtsam::JacobianFactor, gtsam::HessianFactor, gtsam::LinearInequality, gtsam::LinearEquality, gtsam::LinearCost, gtsam::GaussianConditional, gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::GaussianDensity, and gtsam::DummyFactor< CAMERA >.

template<class ARCHIVE >

void gtsam::GaussianFactor::serialize	(	ARCHIVE &	ar,
		const unsigned	int
	)

inlineprivate

Definition at line 160 of file GaussianFactor.h.

template<typename CONTAINER >

static DenseIndex gtsam::GaussianFactor::Slot	(	const CONTAINER &	keys,
		Key	key
	)

inlinestatic

Definition at line 152 of file GaussianFactor.h.

virtual void gtsam::GaussianFactor::updateHessian	(	const KeyVector &	keys,
		SymmetricBlockMatrix *	info
	)		const

pure virtual

Update an information matrix by adding the information corresponding to this factor (used internally during elimination).

Parameters

scatter	A mapping from variable index to slot index in this HessianFactor
info	The information matrix to be updated

Implemented in gtsam::HessianFactor, gtsam::JacobianFactor, gtsam::RegularImplicitSchurFactor< CAMERA >, and gtsam::BinaryJacobianFactor< M, N1, N2 >.

Friends And Related Function Documentation

friend class boost::serialization::access

friend

Serialization function

Definition at line 158 of file GaussianFactor.h.

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

Public Types

Public Member Functions

Static Public Member Functions

Private Member Functions

Friends

Additional Inherited Members

Detailed Description

Member Typedef Documentation

Constructor & Destructor Documentation

Member Function Documentation

Friends And Related Function Documentation