Detailed Description

template<class CAMERA>
class gtsam::RegularImplicitSchurFactor< CAMERA >

Inheritance diagram for gtsam::RegularImplicitSchurFactor< CAMERA >:

Public Member Functions
	RegularImplicitSchurFactor ()
	Constructor.

	RegularImplicitSchurFactor (const KeyVector &keys, const std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > > &FBlocks, const Matrix &E, const Matrix &P, const Vector &b)
	Construct from blocks of F, E, inv(E'*E), and RHS vector b.

virtual	~RegularImplicitSchurFactor ()
	Destructor.

std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > > &	FBlocks () const

const Matrix &	E () const

const Vector &	b () const

const Matrix &	getPointCovariance () const

void	print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	print

bool	equals (const GaussianFactor &lf, double tol) const
	equals

virtual DenseIndex	getDim (const_iterator variable) const
	Degrees of freedom of camera.

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

virtual Matrix	augmentedJacobian () const
	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
	Return the dense Jacobian \( A \) and right-hand-side \( b \), with the noise models baked into A and b. More...

virtual Matrix	augmentedInformation () const
	Compute full augmented information matrix

virtual Matrix	information () const
	Compute full information matrix

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

virtual void	hessianDiagonal (double *d) const
	add the contribution of this factor to the diagonal of the hessian d(output) = d(input) + deltaHessianFactor

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

virtual GaussianFactor::shared_ptr	clone () const
	Clone a factor (make a deep copy)

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

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

void	projectError2 (const Error2s &e1, Error2s &e2) const
	Calculate corrected error Q(e-ZDimb) = (I - EPE')(e-ZDimb)

virtual double	error (const VectorValues &x) const
	Print for testable.

double	errorJF (const VectorValues &x) const

void	projectError (const Error2s &e1, Error2s &e2) const
	Calculate corrected error Qe = (I - EPE')e.

void	multiplyHessianAdd (double alpha, const double x, double y) const
	double* Hessian-vector multiply, i.e. More...

void	multiplyHessianAdd (double alpha, const double x, double y, std::vector< size_t > keys) const

void	multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const
	Hessian-vector multiply, i.e. More...

void	multiplyHessianDummy (double alpha, const VectorValues &x, VectorValues &y) const
	Dummy version to measure overhead of key access.

VectorValues	gradientAtZero () const
	Calculate gradient, which is -F'Q*b, see paper.

virtual void	gradientAtZero (double *d) const
	Calculate gradient, which is -F'Q*b, see paper - RAW MEMORY ACCESS.

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

Public Member Functions inherited from gtsam::GaussianFactor
	GaussianFactor ()
	Default constructor creates empty factor.

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

virtual	~GaussianFactor ()
	Destructor.

Public Member Functions inherited from gtsam::Factor
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

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

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

KeyVector &	keys ()

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

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

Static Public Member Functions
static void	multiplyHessianAdd (const Matrix &F, const Matrix &E, const Matrix &PointCovariance, double alpha, const Vector &x, Vector &y)

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

Public Attributes
Error2s	e1
	Scratch space for multiplyHessianAdd.

Error2s	e2

Public Types
typedef RegularImplicitSchurFactor	This
	Typedef to this class.

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

typedef std::vector< Vector2, Eigen::aligned_allocator< Vector2 > >	Error2s

Public Types inherited from gtsam::GaussianFactor
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.

Protected Types
typedef CameraSet< CAMERA >	Set

typedef CAMERA::Measurement	Z

typedef Eigen::Matrix< double, ZDim, D >	MatrixZD
	type of an F block

typedef Eigen::Matrix< double, D, D >	MatrixDD
	camera hessian

Protected Attributes
const std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > >	FBlocks_
	All ZDim*D F blocks (one for each camera)

const Matrix	PointCovariance_
	the 33 matrix P = inv(E'E) (22 if degenerate)

const Matrix	E_
	The 2m*3 E Jacobian with respect to the point.

const Vector	b_
	2m-dimensional RHS vector

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

Static Protected Attributes
static const int	D = traits<CAMERA>::dimension
	Camera dimension.

static const int	ZDim = traits<Z>::dimension
	Measurement dimension.

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...

Member Function Documentation

◆ augmentedJacobian()

template<class CAMERA >

virtual Matrix gtsam::RegularImplicitSchurFactor< CAMERA >::augmentedJacobian ( ) const

inlinevirtual

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.

Implements gtsam::GaussianFactor.

◆ jacobian()

template<class CAMERA >

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

inlinevirtual

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.

Implements gtsam::GaussianFactor.

◆ multiplyHessianAdd() [1/2]

template<class CAMERA >

void gtsam::RegularImplicitSchurFactor< CAMERA >::multiplyHessianAdd	(	double	alpha,
		const double *	x,
		double *	y
	)		const

inline

double* Hessian-vector multiply, i.e.

y += F'alpha(I - E*P*E')*F*x RAW memory access! Assumes keys start at 0 and go to M-1, and x and and y are laid out that way

◆ multiplyHessianAdd() [2/2]

template<class CAMERA >

void gtsam::RegularImplicitSchurFactor< CAMERA >::multiplyHessianAdd	(	double	alpha,
		const VectorValues &	x,
		VectorValues &	y
	)		const

inlinevirtual

Hessian-vector multiply, i.e.

y += F'alpha(I - E*P*E')*F*x

Implements gtsam::GaussianFactor.

◆ negate()

template<class CAMERA >

virtual GaussianFactor::shared_ptr gtsam::RegularImplicitSchurFactor< CAMERA >::negate ( ) const

inlinevirtual

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

Returns: a HessianFactor with negated Hessian matrices

Implements gtsam::GaussianFactor.

◆ updateHessian()

template<class CAMERA >

virtual void gtsam::RegularImplicitSchurFactor< CAMERA >::updateHessian	(	const KeyVector &	keys,
		SymmetricBlockMatrix *	info
	)		const

inlinevirtual

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

Implements gtsam::GaussianFactor.

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

/Users/dellaert/git/gtsam/gtsam/slam/RegularImplicitSchurFactor.h

Detailed Description

template<class CAMERA> class gtsam::RegularImplicitSchurFactor< CAMERA >

Public Member Functions

Static Public Member Functions

Public Attributes

Public Types

Protected Types

Protected Attributes

Static Protected Attributes

Additional Inherited Members

Member Function Documentation

◆ augmentedJacobian()

◆ jacobian()

◆ multiplyHessianAdd() [1/2]

◆ multiplyHessianAdd() [2/2]

◆ negate()

◆ updateHessian()

template<class CAMERA>
class gtsam::RegularImplicitSchurFactor< CAMERA >