Detailed Description

A nonlinear sum-of-squares factor with a zero-mean noise model implementing the density \( P(z|x) \propto exp -0.5*|z-h(x)|^2_C \) Templated on the parameter type X and the values structure Values There is no return type specified for h(x).

Instead, we require the derived class implements \( \mathtt{error\_vector}(x) = h(x)-z \approx A \delta x - b \) This allows a graph to have factors with measurements of mixed type.

The noise model is typically Gaussian, but robust and constrained error models are also supported.

Inheritance diagram for gtsam::NoiseModelFactor:

Public Member Functions
	NoiseModelFactor ()
	Default constructor for I/O only.
	~NoiseModelFactor () override
	Destructor.
template<typename CONTAINER>
	NoiseModelFactor (const SharedNoiseModel &noiseModel, const CONTAINER &keys)
	Constructor.
void	print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const override
	Print.
bool	equals (const NonlinearFactor &f, double tol=1e-9) const override
	Check if two factors are equal.
size_t	dim () const override
	get the dimension of the factor (number of rows on linearization)
const SharedNoiseModel &	noiseModel () const
	access to the noise model
virtual Vector	unwhitenedError (const Values &x, OptionalMatrixVecType H=nullptr) const =0
	Error function without the NoiseModel, \( z-h(x) \).
Vector	unwhitenedError (const Values &x, std::vector< Matrix > &H) const
	support taking in the actual vector instead of the pointer as well to get access to this version of the function from derived classes one will need to use the "using" keyword and specify that like this: public: using NoiseModelFactor::unwhitenedError;
Vector	whitenedError (const Values &c) const
	Vector of errors, whitened This is the raw error, i.e., i.e.
Vector	unweightedWhitenedError (const Values &c) const
	Vector of errors, whitened, but unweighted by any loss function.
double	weight (const Values &c) const
	Compute the effective weight of the factor from the noise model.
double	error (const Values &c) const override
	Calculate the error of the factor.
std::shared_ptr< GaussianFactor >	linearize (const Values &x) const override
	Linearize a non-linearFactorN to get a GaussianFactor, \( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \).
shared_ptr	cloneWithNewNoiseModel (const SharedNoiseModel newNoise) const
	Creates a shared_ptr clone of the factor with a new noise model.
double	error (const HybridValues &c) const override
	All factor types need to implement an error function.
	NonlinearFactor ()
	Default constructor for I/O only.
template<typename CONTAINER>
	NonlinearFactor (const CONTAINER &keys)
	Constructor from a collection of the keys involved in this factor.
void	print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const override
	print
double	error (const HybridValues &c) const override
	All factor types need to implement an error function.
virtual bool	active (const Values &c) const
	Checks whether a factor should be used based on a set of values.
virtual void	qcqpFactors (NonlinearFactorGraph costs, NonlinearEqualityConstraints constraints, size_t columnDimension=1) const
	Add this factor's QCQP cost and constraints over matrix-valued QCQP variables with the given column dimension.
virtual shared_ptr	clone () const
	Creates a shared_ptr clone of the factor - needs to be specialized to allow for subclasses.
virtual shared_ptr	rekey (const std::map< Key, Key > &rekey_mapping) const
	Creates a shared_ptr clone of the factor with different keys using a map from old->new keys.
virtual shared_ptr	rekey (const KeyVector &new_keys) const
	Clones a factor and fully replaces its keys.
virtual bool	sendable () const
	Should the factor be evaluated in the same thread as the caller This is to enable factors that has shared states (like the Python GIL lock).
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.

Public Types
typedef std::shared_ptr< This >	shared_ptr
	Noise model.
Public Types inherited from gtsam::NonlinearFactor
typedef std::shared_ptr< This >	shared_ptr
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 NonlinearFactor	Base
typedef NoiseModelFactor	This
Protected Types inherited from gtsam::NonlinearFactor
typedef Factor	Base
typedef NonlinearFactor	This

Protected Member Functions
	NoiseModelFactor (const SharedNoiseModel &noiseModel)
	Constructor - only for subclasses, as this does not set keys.
	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.

Protected Attributes
SharedNoiseModel	noiseModel_
Protected Attributes inherited from gtsam::Factor
KeyVector	keys_
	The keys involved in this factor.

Additional Inherited Members
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.

Member Function Documentation

◆ dim()

size_t gtsam::NoiseModelFactor::dim ( ) const

inlineoverridevirtual

get the dimension of the factor (number of rows on linearization)

Implements gtsam::NonlinearFactor.

◆ equals()

bool NoiseModelFactor::equals	(	const NonlinearFactor &	f,
		double	tol = 1e-9 ) const

overridevirtual

Check if two factors are equal.

Reimplemented from gtsam::NonlinearFactor.

◆ error() [1/2]

double NonlinearFactor::error ( const HybridValues & hybridValues ) const

overridevirtual

All factor types need to implement an error function.

In factor graphs, this is the negative log-likelihood.

Reimplemented from gtsam::Factor.

◆ error() [2/2]

double NoiseModelFactor::error ( const Values & c ) const

overridevirtual

Calculate the error of the factor.

This is the log-likelihood, e.g. \( 0.5(h(x)-z)^2/\sigma^2 \) in case of Gaussian. In this class, we take the raw prediction error \( h(x)-z \), ask the noise model to transform it to \( (h(x)-z)^2/\sigma^2 \), and then multiply by 0.5.

Reimplemented from gtsam::NonlinearFactor.

Reimplemented in gtsam::WnoaInterpFactor< PoseType >.

◆ linearize()

std::shared_ptr< GaussianFactor > NoiseModelFactor::linearize ( const Values & x ) const

overridevirtual

Linearize a non-linearFactorN to get a GaussianFactor, \( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \).

Implements gtsam::NonlinearFactor.

◆ print()

void NoiseModelFactor::print	(	const std::string &	s = "",
		const KeyFormatter &	keyFormatter = DefaultKeyFormatter ) const

overridevirtual

Print.

Reimplemented from gtsam::Factor.

◆ unwhitenedError()

virtual Vector gtsam::NoiseModelFactor::unwhitenedError	(	const Values &	x,
		OptionalMatrixVecType	H = nullptr ) const

pure virtual

Error function without the NoiseModel, \( z-h(x) \).

Override this method to finish implementing an N-way factor. If the optional arguments is specified, it should compute both the function evaluation and its derivative(s) in H.

◆ whitenedError()

Vector NoiseModelFactor::whitenedError ( const Values & c ) const

Vector of errors, whitened This is the raw error, i.e., i.e.

\( (h(x)-z)/\sigma \) in case of a Gaussian

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

/tmp/gtsam-4.3.0-doxygen.rsXPUS/source/gtsam/nonlinear/NonlinearFactor.h
/tmp/gtsam-4.3.0-doxygen.rsXPUS/source/gtsam/nonlinear/NonlinearFactor.cpp

Detailed Description

Public Member Functions

Public Types

Protected Types

Protected Member Functions

Protected Attributes

Additional Inherited Members

Member Function Documentation

◆ dim()

◆ equals()

◆ error() [1/2]

◆ error() [2/2]

◆ linearize()

◆ print()

◆ unwhitenedError()

◆ whitenedError()