gtsam  4.1.0
gtsam
gtsam::RegularImplicitSchurFactor< CAMERA > Class Template Reference

Detailed Description

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

RegularImplicitSchurFactor.

+ 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 override
 print
 
bool equals (const GaussianFactor &lf, double tol) const override
 equals
 
DenseIndex getDim (const_iterator variable) const override
 Degrees of freedom of camera.
 
void updateHessian (const KeyVector &keys, SymmetricBlockMatrix *info) const override
 Update an information matrix by adding the information corresponding to this factor (used internally during elimination). More...
 
Matrix augmentedJacobian () const override
 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...
 
std::pair< Matrix, Vector > jacobian () const override
 Return the dense Jacobian \( A \) and right-hand-side \( b \), with the noise models baked into A and b. More...
 
Matrix augmentedInformation () const override
 Compute full augmented information matrix
 
Matrix information () const override
 Compute full information matrix
 
void hessianDiagonalAdd (VectorValues &d) const override
 Add the diagonal of the Hessian for this factor to existing VectorValues.
 
void hessianDiagonal (double *d) const override
 add the contribution of this factor to the diagonal of the hessian d(output) = d(input) + deltaHessianFactor
 
std::map< Key, Matrix > hessianBlockDiagonal () const override
 Return the block diagonal of the Hessian for this factor.
 
GaussianFactor::shared_ptr clone () const override
 Clone a factor (make a deep copy)
 
bool empty () const override
 Test whether the factor is empty.
 
GaussianFactor::shared_ptr negate () const override
 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-ZDim*b) = (I - E*P*E')*(e-ZDim*b)
 
double error (const VectorValues &x) const override
 Print for testable.
 
double errorJF (const VectorValues &x) const
 
void projectError (const Error2s &e1, Error2s &e2) const
 Calculate corrected error Q*e = (I - E*P*E')*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 override
 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 override
 Calculate gradient, which is -F'Q*b, see paper.
 
void gradientAtZero (double *d) const override
 Calculate gradient, which is -F'Q*b, see paper - RAW MEMORY ACCESS.
 
Vector gradient (Key key, const VectorValues &x) const override
 Gradient wrt a key at any values.
 
VectorValues hessianDiagonal () const
 Using the base method.
 
virtual void hessianDiagonal (double *d) const=0
 Using the base method.
 
- 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.
 
VectorValues hessianDiagonal () const
 Return the diagonal of the Hessian for this factor.
 
- 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

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< Thisshared_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< 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.
 

Protected Types

typedef CameraSet< CAMERA > Set
 
typedef CAMERA::Measurement Z
 
typedef Eigen::Matrix< double, ZDim, DMatrixZD
 type of an F block
 
typedef Eigen::Matrix< double, D, DMatrixDD
 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 3*3 matrix P = inv(E'E) (2*2 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 >
Matrix gtsam::RegularImplicitSchurFactor< CAMERA >::augmentedJacobian ( ) const
inlineoverridevirtual

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

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
inlineoverridevirtual

Hessian-vector multiply, i.e.

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

Implements gtsam::GaussianFactor.

◆ negate()

template<class CAMERA >
GaussianFactor::shared_ptr gtsam::RegularImplicitSchurFactor< CAMERA >::negate ( ) const
inlineoverridevirtual

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

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

Parameters
scatterA mapping from variable index to slot index in this HessianFactor
infoThe information matrix to be updated

Implements gtsam::GaussianFactor.


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