gtsam  4.0.0 gtsam
gtsam::GaussianFactor Class Referenceabstract

## 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.

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

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

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

virtual DenseIndex getDim (const_iterator variable) const =0
0.5*(A*x-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.

virtual VectorValues hessianDiagonal () const =0
Return the diagonal of the Hessian for this factor.

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

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

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

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

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'*A*x

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

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

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

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 KeyVectorkeys () 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

KeyVectorkeys ()

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

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

## 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< Thisshared_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.

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.

## ◆ 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.

## ◆ 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 >.

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

## ◆ jacobian()

 virtual std::pair 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 >.

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

## ◆ 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

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