gtsam  4.1.0
gtsam
gtsam::RegularJacobianFactor< D > Class Template Reference

Detailed Description

template<size_t D>
class gtsam::RegularJacobianFactor< D >

JacobianFactor with constant sized blocks Provides raw memory access versions of linear operator.

Is base class for JacobianQFactor, JacobianFactorQR, and JacobianFactorSVD

+ Inheritance diagram for gtsam::RegularJacobianFactor< D >:

Public Member Functions

 RegularJacobianFactor ()
 Default constructor.
 
template<typename TERMS >
 RegularJacobianFactor (const TERMS &terms, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
 Construct an n-ary factor. More...
 
template<typename KEYS >
 RegularJacobianFactor (const KEYS &keys, const VerticalBlockMatrix &augmentedMatrix, const SharedDiagonal &sigmas=SharedDiagonal())
 Constructor with arbitrary number keys, and where the augmented matrix is given all together instead of in block terms. More...
 
void multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const override
 y += alpha * A'*A*x
 
void multiplyHessianAdd (double alpha, const double *x, double *y) const
 double* Hessian-vector multiply, i.e. More...
 
void hessianDiagonal (double *d) const override
 Raw memory access version of hessianDiagonal.
 
VectorValues gradientAtZero () const override
 Expose base class gradientAtZero.
 
void gradientAtZero (double *d) const override
 Raw memory access version of gradientAtZero.
 
void transposeMultiplyAdd (double alpha, const Vector &e, double *x) const
 double* Transpose Matrix-vector multiply, i.e. More...
 
Vector operator* (const double *x) const
 double* Matrix-vector multiply, i.e. More...
 
void multiplyHessianAdd (double alpha, const VectorValues &x, VectorValues &y) const override
 y += alpha * A'*A*x
 
void multiplyHessianAdd (double alpha, const double *x, double *y, const std::vector< size_t > &accumulatedDims) const
 Raw memory access version of multiplyHessianAdd y += alpha * A'*A*x Requires the vector accumulatedDims to tell the dimension of each variable: e.g. More...
 
VectorValues hessianDiagonal () const
 Using the base method.
 
virtual void hessianDiagonal (double *d) const=0
 Using the base method.
 
- Public Member Functions inherited from gtsam::JacobianFactor
 JacobianFactor (const GaussianFactor &gf)
 Convert from other GaussianFactor.
 
 JacobianFactor (const JacobianFactor &jf)
 Copy constructor.
 
 JacobianFactor (const HessianFactor &hf)
 Conversion from HessianFactor (does Cholesky to obtain Jacobian matrix)
 
 JacobianFactor ()
 default constructor for I/O
 
 JacobianFactor (const Vector &b_in)
 Construct Null factor.
 
 JacobianFactor (Key i1, const Matrix &A1, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
 Construct unary factor.
 
 JacobianFactor (Key i1, const Matrix &A1, Key i2, const Matrix &A2, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
 Construct binary factor.
 
 JacobianFactor (Key i1, const Matrix &A1, Key i2, const Matrix &A2, Key i3, const Matrix &A3, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
 Construct ternary factor.
 
template<typename TERMS >
 JacobianFactor (const TERMS &terms, const Vector &b, const SharedDiagonal &model=SharedDiagonal())
 Construct an n-ary factor. More...
 
template<typename KEYS >
 JacobianFactor (const KEYS &keys, const VerticalBlockMatrix &augmentedMatrix, const SharedDiagonal &sigmas=SharedDiagonal())
 Constructor with arbitrary number keys, and where the augmented matrix is given all together instead of in block terms. More...
 
 JacobianFactor (const GaussianFactorGraph &graph)
 Build a dense joint factor from all the factors in a factor graph. More...
 
 JacobianFactor (const GaussianFactorGraph &graph, const VariableSlots &p_variableSlots)
 Build a dense joint factor from all the factors in a factor graph. More...
 
 JacobianFactor (const GaussianFactorGraph &graph, const Ordering &ordering)
 Build a dense joint factor from all the factors in a factor graph. More...
 
 JacobianFactor (const GaussianFactorGraph &graph, const Ordering &ordering, const VariableSlots &p_variableSlots)
 Build a dense joint factor from all the factors in a factor graph. More...
 
virtual ~JacobianFactor ()
 Virtual destructor.
 
GaussianFactor::shared_ptr clone () const override
 Clone this JacobianFactor.
 
void print (const std::string &s="", const KeyFormatter &formatter=DefaultKeyFormatter) const override
 
bool equals (const GaussianFactor &lf, double tol=1e-9) const override
 Equals for testable.
 
Vector unweighted_error (const VectorValues &c) const
 
Vector error_vector (const VectorValues &c) const
 (A*x-b)
 
double error (const VectorValues &c) const override
 (A*x-b)/sigma
 
Matrix augmentedInformation () const override
 0.5*(A*x-b)'D(A*x-b) More...
 
Matrix information () const override
 Return the non-augmented information matrix represented by this GaussianFactor.
 
void hessianDiagonalAdd (VectorValues &d) const override
 Add the current diagonal to a VectorValues instance.
 
std::map< Key, Matrix > hessianBlockDiagonal () const override
 Return the block diagonal of the Hessian for this factor.
 
std::pair< Matrix, Vector > jacobian () const override
 Returns (dense) A,b pair associated with factor, bakes in the weights.
 
std::pair< Matrix, Vector > jacobianUnweighted () const
 Returns (dense) A,b pair associated with factor, does not bake in weights.
 
Matrix augmentedJacobian () const override
 Return (dense) matrix associated with factor. More...
 
Matrix augmentedJacobianUnweighted () const
 Return (dense) matrix associated with factor. More...
 
const VerticalBlockMatrixmatrixObject () const
 Return the full augmented Jacobian matrix of this factor as a VerticalBlockMatrix object.
 
VerticalBlockMatrixmatrixObject ()
 Mutable access to the full augmented Jacobian matrix of this factor as a VerticalBlockMatrix object.
 
GaussianFactor::shared_ptr negate () const override
 Construct the corresponding anti-factor to negate information stored stored in this factor. More...
 
bool empty () const override
 Check if the factor is empty. More...
 
bool isConstrained () const
 is noise model constrained ?
 
DenseIndex getDim (const_iterator variable) const override
 Return the dimension of the variable pointed to by the given key iterator todo: Remove this in favor of keeping track of dimensions with variables?
 
size_t rows () const
 return the number of rows in the corresponding linear system
 
size_t cols () const
 return the number of columns in the corresponding linear system
 
const SharedDiagonal & get_model () const
 get a copy of model
 
SharedDiagonal & get_model ()
 get a copy of model (non-const version)
 
const constBVector getb () const
 Get a view of the r.h.s. More...
 
constABlock getA (const_iterator variable) const
 Get a view of the A matrix for the variable pointed to by the given key iterator.
 
constABlock getA () const
 Get a view of the A matrix, not weighted by noise.
 
BVector getb ()
 Get a view of the r.h.s. More...
 
ABlock getA (iterator variable)
 Get a view of the A matrix for the variable pointed to by the given key iterator (non-const version)
 
ABlock getA ()
 Get a view of the A matrix.
 
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...
 
Vector operator* (const VectorValues &x) const
 Return A*x.
 
void transposeMultiplyAdd (double alpha, const Vector &e, VectorValues &x) const
 x += alpha * A'*e. More...
 
void multiplyHessianAdd (double alpha, const double *x, double *y, const std::vector< size_t > &accumulatedDims) const
 Raw memory access version of multiplyHessianAdd y += alpha * A'*A*x Requires the vector accumulatedDims to tell the dimension of each variable: e.g. More...
 
Vector gradient (Key key, const VectorValues &x) const override
 Compute the gradient wrt a key at any values.
 
JacobianFactor whiten () const
 Return a whitened version of the factor, i.e. More...
 
std::pair< boost::shared_ptr< GaussianConditional >, shared_ptreliminate (const Ordering &keys)
 Eliminate the requested variables.
 
void setModel (bool anyConstrained, const Vector &sigmas)
 set noiseModel correctly
 
boost::shared_ptr< GaussianConditionalsplitConditional (size_t nrFrontals)
 splits a pre-factorized factor into a conditional, and changes the current factor to be the remaining component. More...
 
- 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.
 

Additional Inherited Members

- Static Public Member Functions inherited from gtsam::GaussianFactor
template<typename CONTAINER >
static DenseIndex Slot (const CONTAINER &keys, Key key)
 
- Public Types inherited from gtsam::JacobianFactor
typedef JacobianFactor This
 Typedef to this class.
 
typedef GaussianFactor Base
 Typedef to base class.
 
typedef boost::shared_ptr< Thisshared_ptr
 shared_ptr to this class
 
typedef VerticalBlockMatrix::Block ABlock
 
typedef VerticalBlockMatrix::constBlock constABlock
 
typedef ABlock::ColXpr BVector
 
typedef constABlock::ConstColXpr constBVector
 
- 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 Member Functions inherited from gtsam::JacobianFactor
template<typename TERMS >
void fillTerms (const TERMS &terms, const Vector &b, const SharedDiagonal &noiseModel)
 Internal function to fill blocks and set dimensions.
 
- 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::JacobianFactor
VerticalBlockMatrix Ab_
 
noiseModel::Diagonal::shared_ptr model_
 
- Protected Attributes inherited from gtsam::Factor
KeyVector keys_
 The keys involved in this factor.
 

Constructor & Destructor Documentation

◆ RegularJacobianFactor() [1/2]

template<size_t D>
template<typename TERMS >
gtsam::RegularJacobianFactor< D >::RegularJacobianFactor ( const TERMS &  terms,
const Vector &  b,
const SharedDiagonal &  model = SharedDiagonal() 
)
inline

Construct an n-ary factor.

Template Parameters
TERMSA container whose value type is std::pair<Key, Matrix>, specifying the collection of keys and matrices making up the factor. TODO Verify terms are regular

◆ RegularJacobianFactor() [2/2]

template<size_t D>
template<typename KEYS >
gtsam::RegularJacobianFactor< D >::RegularJacobianFactor ( const KEYS &  keys,
const VerticalBlockMatrix augmentedMatrix,
const SharedDiagonal &  sigmas = SharedDiagonal() 
)
inline

Constructor with arbitrary number keys, and where the augmented matrix is given all together instead of in block terms.

Note that only the active view of the provided augmented matrix is used, and that the matrix data is copied into a newly-allocated matrix in the constructed factor. TODO Verify complies to regular

Member Function Documentation

◆ multiplyHessianAdd() [1/2]

template<size_t D>
void gtsam::RegularJacobianFactor< D >::multiplyHessianAdd ( double  alpha,
const double *  x,
double *  y 
) const
inline

double* Hessian-vector multiply, i.e.

y += A'*(A*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<size_t D>
void gtsam::JacobianFactor::multiplyHessianAdd

Raw memory access version of multiplyHessianAdd y += alpha * A'*A*x Requires the vector accumulatedDims to tell the dimension of each variable: e.g.

Raw memory access version of multiplyHessianAdd y += alpha * A'*A*x Note: this is not assuming a fixed dimension for the variables, but requires the vector accumulatedDims to tell the dimension of each variable: e.g.

: x0 has dim 3, x2 has dim 6, x3 has dim 2, then accumulatedDims is [0 3 9 11 13] NOTE: size of accumulatedDims is size of keys + 1!! TODO(frank): we should probably kill this if no longer needed

: x0 has dim 3, x2 has dim 6, x3 has dim 2, then accumulatedDims is [0 3 9 11 13] NOTE: size of accumulatedDims is size of keys + 1!! TODO Frank asks: why is this here if not regular ????

Use Eigen magic to access raw memory

Just iterate over all A matrices and multiply in correct config part (looping over keys) E.g.: Jacobian A = [A0 A1 A2] multiplies x = [x0 x1 x2]' Hence: Ax = A0 x0 + A1 x1 + A2 x2 (hence we loop over the keys and accumulate)

Deal with noise properly, need to Double* whiten as we are dividing by variance

multiply with alpha

Again iterate over all A matrices and insert Ai^T into y

◆ operator*()

template<size_t D>
Vector gtsam::RegularJacobianFactor< D >::operator* ( const double *  x) const
inline

double* Matrix-vector multiply, i.e.

y = A*x RAW memory access! Assumes keys start at 0 and go to M-1, and x is laid out that way

◆ transposeMultiplyAdd()

template<size_t D>
void gtsam::RegularJacobianFactor< D >::transposeMultiplyAdd ( double  alpha,
const Vector &  e,
double *  x 
) const
inline

double* Transpose Matrix-vector multiply, i.e.

x += A'*e RAW memory access! Assumes keys start at 0 and go to M-1, and y is laid out that way


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