#include <NoiseModel.h>
Public Types | |
| typedef std::shared_ptr< Robust > | shared_ptr |
Public Member Functions | |
| Robust () | |
| Default Constructor for serialization. | |
| Robust (const RobustModel::shared_ptr robust, const NoiseModel::shared_ptr noise) | |
| Constructor. | |
| ~Robust () override | |
| Destructor. | |
| void | print (const std::string &name) const override |
| bool | equals (const Base &expected, double tol=1e-9) const override |
| const RobustModel::shared_ptr & | robust () const |
| Return the contained robust error function. | |
| const NoiseModel::shared_ptr & | noise () const |
| Return the contained noise model. | |
| Vector | whiten (const Vector &v) const override |
| Whiten an error vector. | |
| Matrix | Whiten (const Matrix &A) const override |
| Whiten a matrix. | |
| Vector | unwhiten (const Vector &) const override |
| Unwhiten an error vector. | |
| double | loss (const double squared_distance) const override |
| Compute loss from the m-estimator using the Mahalanobis distance. | |
| double | squaredMahalanobisDistance (const Vector &v) const override |
| Squared Mahalanobis distance v'*R'*R*v = <R*v,R*v> | |
| virtual void | WhitenSystem (Vector &b) const |
| void | WhitenSystem (std::vector< Matrix > &A, Vector &b) const override |
| void | WhitenSystem (Matrix &A, Vector &b) const override |
| void | WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const override |
| void | WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const override |
| Vector | unweightedWhiten (const Vector &v) const override |
| double | weight (const Vector &v) const override |
| virtual bool | isConstrained () const |
| true if a constrained noise model, saves slow/clumsy dynamic casting | |
| virtual bool | isUnit () const |
| true if a unit noise model, saves slow/clumsy dynamic casting | |
| size_t | dim () const |
| Dimensionality. | |
| virtual Vector | sigmas () const |
| Calculate standard deviations. | |
| virtual double | mahalanobisDistance (const Vector &v) const |
| Mahalanobis distance. | |
| virtual void | whitenInPlace (Vector &v) const |
| virtual void | whitenInPlace (Eigen::Block< Vector > &v) const |
| virtual void | unwhitenInPlace (Vector &v) const |
| virtual void | unwhitenInPlace (Eigen::Block< Vector > &v) const |
Static Public Member Functions | |
| static shared_ptr | Create (const RobustModel::shared_ptr &robust, const NoiseModel::shared_ptr noise) |
Protected Types | |
| typedef mEstimator::Base | RobustModel |
| typedef noiseModel::Base | NoiseModel |
Protected Attributes | |
| const RobustModel::shared_ptr | robust_ |
| robust error function used | |
| const NoiseModel::shared_ptr | noise_ |
| noise model used | |
| size_t | dim_ |
Detailed Description
Base class for robust error models The robust M-estimators above simply tell us how to re-weight the residual, and are isotropic kernels, in that they do not allow for correlated noise. They also have no way to scale the residual values, e.g., dividing by a single standard deviation. Hence, the actual robust noise model below does this scaling/whitening in sequence, by passing both a standard noise model and a robust estimator.
Taking as an example noise = Isotropic::Create(d, sigma), we first divide the residuals uw = |Ax-b| by sigma by "whitening" the system (A,b), obtaining r = |Ax-b|/sigma, and then we pass the now whitened residual 'r' through the robust M-estimator. This is currently done by multiplying with sqrt(w), because the residuals will be squared again in error, yielding 0.5 w(r)*r^2.
In other words, while sigma is expressed in the native residual units, a parameter like k in the Huber norm is expressed in whitened units, i.e., "nr of sigmas".
Member Function Documentation
◆ unweightedWhiten()
|
overridevirtual |
Useful function for robust noise models to get the unweighted but whitened error
Reimplemented from gtsam::noiseModel::Base.
◆ unwhitenInPlace() [1/2]
|
inlinevirtualinherited |
in-place unwhiten, override if can be done more efficiently
Reimplemented in gtsam::noiseModel::Unit.
◆ unwhitenInPlace() [2/2]
|
inlinevirtualinherited |
in-place unwhiten, override if can be done more efficiently
Reimplemented in gtsam::noiseModel::Unit.
◆ weight()
|
overridevirtual |
get the weight from the effective loss function on residual vector v
Reimplemented from gtsam::noiseModel::Base.
◆ whitenInPlace() [1/2]
|
inlinevirtualinherited |
in-place whiten, override if can be done more efficiently
Reimplemented in gtsam::noiseModel::Unit, and gtsam::noiseModel::Isotropic.
◆ whitenInPlace() [2/2]
|
inlinevirtualinherited |
in-place whiten, override if can be done more efficiently
Reimplemented in gtsam::noiseModel::Unit.
The documentation for this class was generated from the following file:
- /home/docs/checkouts/readthedocs.org/user_builds/gtsam-jlblanco-docs/checkouts/latest/gtsam/linear/NoiseModel.h
