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)

Inheritance diagram for gtsam::GaussianFactor:

Public Member Functions
	GaussianFactor ()
	Default constructor creates empty factor.

template<typename CONTAINER >
	GaussianFactor (const CONTAINER &keys)
	Construct from container of keys. More...

virtual	~GaussianFactor ()
	Destructor.

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

virtual bool	equals (const GaussianFactor &lf, double tol=1e-9) const =0
	Equals for testable. More...

virtual double	error (const VectorValues &c) const =0
	Print for testable. More...

virtual DenseIndex	getDim (const_iterator variable) const =0
	0.5(Ax-b)'D(A*x-b) More...

virtual Matrix	augmentedJacobian () const =0
	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. More...

virtual std::pair< Matrix, Vector >	jacobian () const =0
	Return the dense Jacobian \( A \) and right-hand-side \( b \), with the noise models baked into A and b. More...

virtual Matrix	augmentedInformation () const =0
	Return the augmented information matrix represented by this GaussianFactor. More...

virtual Matrix	information () const =0
	Return the non-augmented information matrix represented by this GaussianFactor. More...

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

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

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

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

virtual GaussianFactor::shared_ptr	clone () const =0
	Clone a factor (make a deep copy) More...

virtual bool	empty () const =0
	Test whether the factor is empty. More...

virtual GaussianFactor::shared_ptr	negate () const =0
	Construct the corresponding anti-factor to negate information stored stored in this factor. More...

virtual void	updateHessian (const KeyVector &keys, SymmetricBlockMatrix *info) const =0
	Update an information matrix by adding the information corresponding to this factor (used internally during elimination). More...

virtual void	multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const =0
	y += alpha * A'Ax 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 Vector	gradient (Key key, const VectorValues &x) const =0
	Gradient wrt a key at any values. More...

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

KeyVector &	keys ()

iterator	begin ()
	Iterator at beginning of involved variable keys.

iterator	end ()
	Iterator at end of involved variable keys.

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

Key	front () const
	First key.

Key	back () const
	Last key.

const_iterator	find (Key key) const
	find

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

const_iterator	begin () const
	Iterator at beginning of involved variable keys.

const_iterator	end () const
	Iterator at end of involved variable keys.

size_t	size () const

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

Public Types
typedef GaussianFactor	This
	This class.

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

typedef Factor	Base
	Our base class.

Public Types inherited from gtsam::Factor
typedef KeyVector::iterator	iterator
	Iterator over keys.

typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys.

Friends
class	boost::serialization::access
	Serialization function.

Additional Inherited Members
Protected Member Functions inherited from gtsam::Factor
	Factor ()
	Default constructor for I/O.

template<typename CONTAINER >
	Factor (const CONTAINER &keys)
	Construct factor from container of keys. More...

template<typename ITERATOR >
	Factor (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys. More...

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

Static Protected Member Functions inherited from gtsam::Factor
template<typename CONTAINER >
static Factor	FromKeys (const CONTAINER &keys)
	Construct factor from container of keys. More...

template<typename ITERATOR >
static Factor	FromIterators (ITERATOR first, ITERATOR last)
	Construct factor from iterator keys. More...

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

Constructor & Destructor Documentation

◆ GaussianFactor()

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.

Member Function Documentation

◆ augmentedInformation()

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 >.

◆ augmentedJacobian()

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 >.

◆ clone()

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

pure virtual

Clone a factor (make a deep copy)

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

◆ empty()

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

pure virtual

Test whether the factor is empty.

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

◆ equals()

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

pure virtual

Equals for testable.

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

◆ error()

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

pure virtual

Print for testable.

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

◆ getDim()

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

◆ gradient()

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

pure virtual

Gradient wrt a key at any values.

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

◆ gradientAtZero() [1/2]

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

pure virtual

A'*b for Jacobian, eta for Hessian.

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

◆ gradientAtZero() [2/2]

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

pure virtual

Raw memory access version of gradientAtZero.

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

◆ hessianBlockDiagonal()

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 >.

◆ hessianDiagonal()

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::RegularJacobianFactor< D >, gtsam::RegularImplicitSchurFactor< CAMERA >, gtsam::RegularJacobianFactor< D >, and gtsam::RegularImplicitSchurFactor< CAMERA >.

◆ hessianDiagonalAdd()

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 >.

◆ information()

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 >.

◆ jacobian()

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 >.

◆ multiplyHessianAdd()

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

pure virtual

y += alpha * A'*A*x

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

◆ negate()

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

◆ print()

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

overridepure virtual

print

Reimplemented from gtsam::Factor.

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

◆ updateHessian()

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

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

/Users/dellaert/git/github/gtsam/linear/GaussianFactor.h
/Users/dellaert/git/github/gtsam/linear/GaussianFactor.cpp

Detailed Description

Public Member Functions

Static Public Member Functions

Public Types

Friends

Additional Inherited Members

Constructor & Destructor Documentation

◆ GaussianFactor()

Member Function Documentation

◆ augmentedInformation()

◆ augmentedJacobian()

◆ clone()

◆ empty()

◆ equals()

◆ error()

◆ getDim()

◆ gradient()

◆ gradientAtZero() [1/2]

◆ gradientAtZero() [2/2]

◆ hessianBlockDiagonal()

◆ hessianDiagonal()

◆ hessianDiagonalAdd()

◆ information()

◆ jacobian()

◆ multiplyHessianAdd()

◆ negate()

◆ print()

◆ updateHessian()