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gtsam 4.2.0
gtsam
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A specialization of a GaussianFactor to structure-less SFM, which is very fast in a conjugate gradient (CG) solver. Specifically, as measured in timeSchurFactors.cpp, it stays very fast for an increasing number of cameras. The magic is in multiplyHessianAdd, which does the Hessian-vector multiply at the core of CG, and implements y += F'alpha(I - E*P*E')*F*x where
Inheritance diagram for gtsam::RegularImplicitSchurFactor< CAMERA >:Public Member Functions | |
| RegularImplicitSchurFactor () | |
| Constructor. | |
| RegularImplicitSchurFactor (const KeyVector &keys, const FBlocks &Fs, const Matrix &E, const Matrix &P, const Vector &b) | |
| Construct from blocks of F, E, inv(E'*E), and RHS vector b. | |
| ~RegularImplicitSchurFactor () override | |
| Destructor. | |
| const FBlocks & | Fs () 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). | |
| 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. | |
| 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. | |
| 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) | |
| GaussianFactor::shared_ptr | negate () const override |
| Construct the corresponding anti-factor to negate information stored stored in this factor. | |
| 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 |
| 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. | |
| 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. | |
| 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. | |
| virtual | ~GaussianFactor () |
| Destructor. | |
| double | error (const HybridValues &c) const override |
| All factor types need to implement an error function. | |
| VectorValues | hessianDiagonal () const |
| Return the diagonal of the Hessian for this factor. | |
Public Member Functions inherited from gtsam::Factor | |
| virtual | ~Factor ()=default |
| Default destructor. | |
| bool | empty () const |
| Whether the factor is empty (involves zero variables). | |
| 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 |
| virtual void | printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const |
| print only keys | |
| bool | equals (const This &other, double tol=1e-9) const |
| check equality | |
| 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 | |
| typedef std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > > | FBlocks |
Protected Attributes | |
| FBlocks | 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. | |
| template<typename ITERATOR > | |
| Factor (ITERATOR first, ITERATOR last) | |
| Construct factor from iterator keys. | |
Static Protected Member Functions inherited from gtsam::Factor | |
| template<typename CONTAINER > | |
| static Factor | FromKeys (const CONTAINER &keys) |
| Construct factor from container of keys. | |
| template<typename ITERATOR > | |
| static Factor | FromIterators (ITERATOR first, ITERATOR last) |
| Construct factor from iterator keys. | |
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inline |
Construct from blocks of F, E, inv(E'*E), and RHS vector b.
Construct a new RegularImplicitSchurFactor object.
| keys | keys corresponding to cameras |
| Fs | All ZDim*D F blocks (one for each camera) |
| E | Jacobian of measurements wrpt point. |
| P | point covariance matrix |
| b | RHS vector |
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inlineoverridevirtual |
Compute full augmented information matrix
Implements gtsam::GaussianFactor.
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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.
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inlineoverridevirtual |
Clone a factor (make a deep copy)
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
equals
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Reimplemented from gtsam::GaussianFactor.
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inlineoverridevirtual |
Degrees of freedom of camera.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Gradient wrt a key at any values.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Calculate gradient, which is -F'Q*b, see paper.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Calculate gradient, which is -F'Q*b, see paper - RAW MEMORY ACCESS.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Return the block diagonal of the Hessian for this factor.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
add the contribution of this factor to the diagonal of the hessian d(output) = d(input) + deltaHessianFactor
Implements gtsam::GaussianFactor.
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virtual |
Using the base method.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Add the diagonal of the Hessian for this factor to existing VectorValues.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Compute full information matrix
Implements gtsam::GaussianFactor.
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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.
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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
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inlineoverridevirtual |
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inlineoverridevirtual |
Construct the corresponding anti-factor to negate information stored stored in this factor.
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Implements gtsam::GaussianFactor.
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inlineoverridevirtual |
Update an information matrix by adding the information corresponding to this factor (used internally during elimination).
| scatter | A mapping from variable index to slot index in this HessianFactor |
| info | The information matrix to be updated |
Implements gtsam::GaussianFactor.