Detailed Description

noiseModel::Base is the abstract base class for all noise models.

Noise models must implement a 'whiten' function to normalize an error vector, and an 'unwhiten' function to unnormalize an error vector.

Inheritance diagram for gtsam::noiseModel::Base:

Public Member Functions
	Base (size_t dim=1)
	primary constructor More...

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 void	print (const std::string &name="") const =0

virtual bool	equals (const Base &expected, double tol=1e-9) const =0

virtual Vector	sigmas () const
	Calculate standard deviations.

virtual Vector	whiten (const Vector &v) const =0
	Whiten an error vector.

virtual Matrix	Whiten (const Matrix &H) const =0
	Whiten a matrix.

virtual Vector	unwhiten (const Vector &v) const =0
	Unwhiten an error vector.

virtual double	distance (const Vector &v) const =0

virtual void	WhitenSystem (std::vector< Matrix > &A, Vector &b) const =0

virtual void	WhitenSystem (Matrix &A, Vector &b) const =0

virtual void	WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const =0

virtual void	WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const =0

virtual void	whitenInPlace (Vector &v) const
	in-place whiten, override if can be done more efficiently

virtual void	unwhitenInPlace (Vector &v) const
	in-place unwhiten, override if can be done more efficiently

virtual void	whitenInPlace (Eigen::Block< Vector > &v) const
	in-place whiten, override if can be done more efficiently

virtual void	unwhitenInPlace (Eigen::Block< Vector > &v) const
	in-place unwhiten, override if can be done more efficiently

Public Types
typedef boost::shared_ptr< Base >	shared_ptr

Constructor & Destructor Documentation

gtsam::noiseModel::Base::Base ( size_t dim = 1 )

inline

primary constructor

Parameters

dim	is the dimension of the model

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