gtsam  4.0.0
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)
virtual NonlinearFactor::shared_ptr clone () const
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
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< GaussianFactorlinearize (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< TransformBtwRobotsUnaryFactorEMshared_ptr
 concept check by type


class boost::serialization::access
 Serialization function.

Member Function Documentation

◆ error()

template<class VALUE >
virtual double gtsam::TransformBtwRobotsUnaryFactorEM< VALUE >::error ( const Values c) const

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 >
virtual void gtsam::TransformBtwRobotsUnaryFactorEM< VALUE >::print ( const std::string &  s,
const KeyFormatter keyFormatter = DefaultKeyFormatter 
) const

implement functions needed for Testable


Reimplemented from gtsam::NonlinearFactor.

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