gtsam::TransformBtwRobotsUnaryFactorEM< VALUE > Class Template Reference
Inheritance diagram for gtsam::TransformBtwRobotsUnaryFactorEM< VALUE >:
Public Member Functions | |
| TransformBtwRobotsUnaryFactorEM () | |
| default constructor - only use for serialization | |
| TransformBtwRobotsUnaryFactorEM (Key key, const VALUE &measured, Key keyA, Key keyB, const Values &valA, const Values &valB, const SharedGaussian &model_inlier, const SharedGaussian &model_outlier, const double prior_inlier, const double prior_outlier, const bool flag_bump_up_near_zero_probs=false, const bool start_with_M_step=false) | |
| Constructor. | |
| virtual NonlinearFactor::shared_ptr | clone () const |
| Clone. | |
| virtual void | print (const std::string &s, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const |
| implement functions needed for Testable More... | |
| virtual bool | equals (const NonlinearFactor &f, double tol=1e-9) const |
| equals | |
| void | setValAValB (const Values &valA, const Values &valB) |
| implement functions needed to derive from Factor | |
| virtual double | error (const Values &x) const |
| Calculate the error of the factor This is typically equal to log-likelihood, e.g. More... | |
| virtual boost::shared_ptr< GaussianFactor > | linearize (const Values &x) const |
| Linearize a non-linearFactorN to get a GaussianFactor, \( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \). | |
| Vector | whitenedError (const Values &x, boost::optional< std::vector< Matrix > & > H=boost::none) const |
| Vector | calcIndicatorProb (const Values &x) const |
| Vector | calcIndicatorProb (const Values &x, const Vector &err) const |
| Vector | unwhitenedError (const Values &x) const |
| SharedGaussian | get_model_inlier () const |
| SharedGaussian | get_model_outlier () const |
| Matrix | get_model_inlier_cov () const |
| Matrix | get_model_outlier_cov () const |
| void | updateNoiseModels (const Values &values, const Marginals &marginals) |
| void | updateNoiseModels (const Values &values, const NonlinearFactorGraph &graph) |
| void | updateNoiseModels_givenCovs (const Values &values, const Matrix &cov1, const Matrix &cov2, const Matrix &cov12) |
| std::size_t | size () const |
| number of variables attached to this factor | |
| virtual size_t | dim () const |
| get the dimension of the factor (number of rows on linearization) | |
Public Types | |
| typedef VALUE | T |
| typedef boost::shared_ptr< TransformBtwRobotsUnaryFactorEM > | shared_ptr |
| concept check by type | |
Friends | |
| class | boost::serialization::access |
| Serialization function. | |
Member Function Documentation
◆ error()
template<class VALUE >
|
inlinevirtual |
Calculate the error of the factor This is typically equal to log-likelihood, e.g.
\( 0.5(h(x)-z)^2/sigma^2 \) in case of Gaussian. You can override this for systems with unusual noise models.
Implements gtsam::NonlinearFactor.
◆ print()
template<class VALUE >
|
inlinevirtual |
The documentation for this class was generated from the following files:
- /Users/dellaert/git/gtsam/gtsam_unstable/slam/TransformBtwRobotsUnaryFactorEM.h
- /Users/dellaert/git/gtsam/gtsam_unstable/gtsam_unstable.h
