Detailed Description

template<class CAMERA>
class gtsam::TriangulationFactor< CAMERA >

Non-linear factor for a constraint derived from a 2D measurement.

The calibration and pose are assumed known.

Inheritance diagram for gtsam::TriangulationFactor< CAMERA >:

Public Member Functions
	TriangulationFactor ()
	Default constructor.
	TriangulationFactor (const CAMERA &camera, const Measurement &measured, const SharedNoiseModel &model, Key pointKey, bool throwCheirality=false, bool verboseCheirality=false)
	Constructor with exception-handling flags.
	~TriangulationFactor () override
	Virtual destructor.
gtsam::NonlinearFactor::shared_ptr	clone () const override
void	print (const std::string &s="", const KeyFormatter &keyFormatter=DefaultKeyFormatter) const override
	print
bool	equals (const NonlinearFactor &p, double tol=1e-9) const override
	equals
Vector	evaluateError (const Point3 &point, OptionalMatrixType H2) const override
	Evaluate error h(x)-z and optionally derivatives.
std::shared_ptr< GaussianFactor >	linearize (const Values &x) const override
	Linearize to a JacobianFactor, does not support constrained noise model !
const Measurement &	measured () const
	return the measurement
bool	verboseCheirality () const
	return verbosity
bool	throwCheirality () const
	return flag for throwing cheirality exceptions
Public Member Functions inherited from gtsam::NoiseModelFactorT< Vector, ValueTypes... >
Key	key () const
	Returns a key.
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;
	NoiseModelFactorT ()
	Default Constructor for I/O.
	NoiseModelFactorT (const SharedNoiseModel &noiseModel, KeyType< ValueTypes >... keys)
	Constructor.
	NoiseModelFactorT (const SharedNoiseModel &noiseModel, CONTAINER keys)
	Constructor.
virtual Vector	evaluateError (const ValueTypes &... x, OptionalMatrixTypeT< ValueTypes >... H) const=0
	Override evaluateError to finish implementing an n-way factor.
Vector	evaluateError (const ValueTypes &... x, MatrixTypeT< ValueTypes > &... H) const
	If all the optional arguments are matrices then redirect the call to the one which takes pointers.
Vector	evaluateError (const ValueTypes &... x) const
	No-Jacobians requested function overload.
AreAllMatrixRefs< Vector, OptionalJacArgs... >	evaluateError (const ValueTypes &... x, OptionalJacArgs &&... H) const
	Some (but not all) optional Jacobians are omitted (function overload) and the jacobians are l-value references to matrices.
AreAllMatrixPtrs< Vector, OptionalJacArgs... >	evaluateError (const ValueTypes &... x, OptionalJacArgs &&... H) const
	Some (but not all) optional Jacobians are omitted (function overload) and the jacobians are pointers to matrices.
Key	key1 () const
Key	key2 () const
Key	key3 () const
Key	key4 () const
Key	key5 () const
Key	key6 () const
Vector	unwhitenedError (const Values &x, OptionalMatrixVecType H=nullptr) const override
	This implements the unwhitenedError virtual function by calling the n-key specific version of evaluateError, which is pure virtual so must be implemented in the derived class.
Public Member Functions inherited from gtsam::NoiseModelFactor
	NoiseModelFactor ()
	Default constructor for I/O only.
	~NoiseModelFactor () override
	Destructor.
template<typename CONTAINER>
	NoiseModelFactor (const SharedNoiseModel &noiseModel, const CONTAINER &keys)
	Constructor.
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
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.
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.
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	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 Attributes
VerticalBlockMatrix	Ab
	thread-safe (?) scratch memory for linearize
Matrix	A
Vector	b

Public Types
using	Camera = CAMERA
	CAMERA type.
using	Measurement = typename CAMERA::Measurement
	shorthand for measurement type, e.g. Point2 or StereoPoint2
using	shared_ptr = std::shared_ptr<This>
	shorthand for a smart pointer to a factor
Public Types inherited from gtsam::NoiseModelFactorT< Vector, ValueTypes... >
using	ValueType
	The type of the I'th template param can be obtained as ValueType.
Public Types inherited from gtsam::NoiseModelFactor
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
using	Base = NoiseModelFactorN<Point3>
	shorthand for base class type
using	This = TriangulationFactor<CAMERA>
	shorthand for this class
Protected Types inherited from gtsam::NoiseModelFactorT< Vector, ValueTypes... >
using	Base
using	This
using	OptionalMatrixTypeT
using	KeyType
using	MatrixTypeT
using	IsConvertible
using	IndexIsValid
using	ContainerElementType
using	IsContainerOfKeys
using	AreAllMatrixRefs
	A helper alias to check if a list of args are all references to a matrix or not.
using	IsMatrixPointer
using	IsNullpointer
using	AreAllMatrixPtrs
	A helper alias to check if a list of args are all pointers to a matrix or not.
Protected Types inherited from gtsam::NoiseModelFactor
typedef NonlinearFactor	Base
typedef NoiseModelFactor	This
Protected Types inherited from gtsam::NonlinearFactor
typedef Factor	Base
typedef NonlinearFactor	This

Protected Attributes
const CAMERA	camera_
	CAMERA in which this landmark was seen.
const Measurement	measured_
	2D measurement
const bool	throwCheirality_
	If true, rethrows Cheirality exceptions (default: false).
const bool	verboseCheirality_
	If true, prints text for Cheirality exceptions (default: false).
Protected Attributes inherited from gtsam::NoiseModelFactor
SharedNoiseModel	noiseModel_
Protected Attributes inherited from gtsam::Factor
KeyVector	keys_
	The keys involved in this factor.

Additional Inherited Members
Static Public Attributes inherited from gtsam::NoiseModelFactorT< Vector, ValueTypes... >
static constexpr auto	N
	N is the number of variables (N-way factor).
Protected Member Functions inherited from gtsam::NoiseModelFactor
	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.
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.

Constructor & Destructor Documentation

◆ TriangulationFactor()

template<class CAMERA>

gtsam::TriangulationFactor< CAMERA >::TriangulationFactor	(	const CAMERA &	camera,
		const Measurement &	measured,
		const SharedNoiseModel &	model,
		Key	pointKey,
		bool	throwCheirality = false,
		bool	verboseCheirality = false )

inline

Constructor with exception-handling flags.

Parameters

camera	is the camera in which unknown landmark is seen
measured	is the 2 dimensional location of point in image (the measurement)
model	is the standard deviation
pointKey	is the index of the landmark
throwCheirality	determines whether Cheirality exceptions are rethrown
verboseCheirality	determines whether exceptions are printed for Cheirality

Member Function Documentation

◆ clone()

template<class CAMERA>

gtsam::NonlinearFactor::shared_ptr gtsam::TriangulationFactor< CAMERA >::clone ( ) const

inlineoverridevirtual

Returns: a deep copy of this factor

Reimplemented from gtsam::NonlinearFactor.

◆ equals()

template<class CAMERA>

bool gtsam::TriangulationFactor< CAMERA >::equals	(	const NonlinearFactor &	p,
		double	tol = 1e-9 ) const

inlineoverridevirtual

equals

Reimplemented from gtsam::NoiseModelFactor.

◆ linearize()

template<class CAMERA>

std::shared_ptr< GaussianFactor > gtsam::TriangulationFactor< CAMERA >::linearize ( const Values & x ) const

inlineoverridevirtual

Linearize to a JacobianFactor, does not support constrained noise model !

\( Ax-b \approx h(x+\delta x)-z = h(x) + A \delta x - z \) Hence \( b = z - h(x) = - \mathtt{error\_vector}(x) \)

Reimplemented from gtsam::NoiseModelFactorT< Vector, ValueTypes... >.

◆ print()

template<class CAMERA>

void gtsam::TriangulationFactor< CAMERA >::print	(	const std::string &	s = "",
		const KeyFormatter &	keyFormatter = DefaultKeyFormatter ) const

inlineoverridevirtual

print

Parameters

s	optional string naming the factor
keyFormatter	optional formatter useful for printing Symbols

Reimplemented from gtsam::NoiseModelFactor.

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

/tmp/gtsam-4.3.0-doxygen.rsXPUS/source/gtsam/slam/TriangulationFactor.h

Detailed Description

Public Member Functions

Public Attributes

Public Types

Protected Types

Protected Attributes

Additional Inherited Members

Constructor & Destructor Documentation

◆ TriangulationFactor()

Member Function Documentation

◆ clone()

◆ equals()

◆ linearize()

◆ print()