Base class for smart factors. This base class has no internal point, but it has a measurement, noise model and an optional sensor pose. This class mainly computes the derivatives and returns them as a variety of factors. The methods take a CameraSet<CAMERA> argument and the value of a point, which is kept in the derived class. More...

#include <SmartFactorBase.h>

Inheritance diagram for gtsam::SmartFactorBase< CAMERA >:

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Collaboration diagram for gtsam::SmartFactorBase< CAMERA >:

[legend]

Public Types
typedef Eigen::Matrix< double, ZDim, Dim >	MatrixZD

typedef std::vector< MatrixZD, Eigen::aligned_allocator< MatrixZD > >	FBlocks

typedef CameraSet< CAMERA >	Cameras
	The CameraSet data structure is used to refer to a set of cameras.

typedef KeyVector::iterator	iterator
	Iterator over keys.

typedef KeyVector::const_iterator	const_iterator
	Const iterator over keys.

Public Member Functions
	SmartFactorBase ()
	Default Constructor, for serialization.

	SmartFactorBase (const SharedNoiseModel &sharedNoiseModel, std::optional< Pose3 > body_P_sensor={}, size_t expectedNumberCameras=10)
	Construct with given noise model and optional arguments.

	~SmartFactorBase () override
	Virtual destructor, subclasses from NonlinearFactor.

void	add (const Z &measured, const Key &key)

void	add (const ZVector &measurements, const KeyVector &cameraKeys)
	Add a bunch of measurements, together with the camera keys.

template<class SFM_TRACK >
void	add (const SFM_TRACK &trackToAdd)

size_t	dim () const override
	Return the dimension (number of rows!) of the factor.

const ZVector &	measured () const
	Return the 2D measurements (ZDim, in general).

virtual Cameras	cameras (const Values &values) const
	Collect all cameras: important that in key order.

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

bool	equals (const NonlinearFactor &p, double tol=1e-9) const override
	equals

template<class POINT >
Vector	unwhitenedError (const Cameras &cameras, const POINT &point, typename Cameras::FBlocks Fs=nullptr, Matrix E=nullptr) const

template<class POINT , class ... OptArgs, typename = std::enable_if_t<sizeof...(OptArgs)!=0>>
Vector	unwhitenedError (const Cameras &cameras, const POINT &point, OptArgs &&... optArgs) const

virtual void	correctForMissingMeasurements (const Cameras &cameras, Vector &ue, typename Cameras::FBlocks Fs=nullptr, Matrix E=nullptr) const

template<class ... OptArgs>
void	correctForMissingMeasurements (const Cameras &cameras, Vector &ue, OptArgs &&... optArgs) const

template<class POINT >
Vector	whitenedError (const Cameras &cameras, const POINT &point) const

template<class POINT >
double	totalReprojectionError (const Cameras &cameras, const POINT &point) const

template<class POINT >
void	computeJacobians (FBlocks &Fs, Matrix &E, Vector &b, const Cameras &cameras, const POINT &point) const

template<class POINT >
void	computeJacobiansSVD (FBlocks &Fs, Matrix &Enull, Vector &b, const Cameras &cameras, const POINT &point) const

std::shared_ptr< RegularHessianFactor< Dim > >	createHessianFactor (const Cameras &cameras, const Point3 &point, const double lambda=0.0, bool diagonalDamping=false) const
	Linearize to a Hessianfactor.

void	updateAugmentedHessian (const Cameras &cameras, const Point3 &point, const double lambda, bool diagonalDamping, SymmetricBlockMatrix &augmentedHessian, const KeyVector allKeys) const

void	whitenJacobians (FBlocks &F, Matrix &E, Vector &b) const
	Whiten the Jacobians computed by computeJacobians using noiseModel_.

std::shared_ptr< RegularImplicitSchurFactor< CAMERA > >	createRegularImplicitSchurFactor (const Cameras &cameras, const Point3 &point, double lambda=0.0, bool diagonalDamping=false) const
	Return Jacobians as RegularImplicitSchurFactor with raw access.

std::shared_ptr< JacobianFactorQ< Dim, ZDim > >	createJacobianQFactor (const Cameras &cameras, const Point3 &point, double lambda=0.0, bool diagonalDamping=false) const
	Return Jacobians as JacobianFactorQ.

std::shared_ptr< JacobianFactor >	createJacobianSVDFactor (const Cameras &cameras, const Point3 &point, double lambda=0.0) const

Pose3	body_P_sensor () const

Testable
bool	equals (const This &other, double tol=1e-9) const
	check equality

virtual void	printKeys (const std::string &s="Factor", const KeyFormatter &formatter=DefaultKeyFormatter) const
	print only keys

Standard Interface
virtual double	error (const Values &c) const

double	error (const HybridValues &c) const override

virtual bool	active (const Values &) const

virtual std::shared_ptr< GaussianFactor >	linearize (const Values &c) const =0

virtual shared_ptr	clone () const

virtual shared_ptr	rekey (const std::map< Key, Key > &rekey_mapping) const

virtual shared_ptr	rekey (const KeyVector &new_keys) const

virtual bool	sendable () const

Standard Interface
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

const_iterator	end () const

size_t	size () const

Advanced Interface
KeyVector &	keys ()

iterator	begin ()

iterator	end ()

Static Public Member Functions
static Matrix	PointCov (const Matrix &E)
	Computes Point Covariance P from the "point Jacobian" E.

static void	FillDiagonalF (const FBlocks &Fs, Matrix &F)
	Create BIG block-diagonal matrix F from Fblocks.

Public Attributes
GTSAM_MAKE_ALIGNED_OPERATOR_NEW typedef std::shared_ptr< This >	shared_ptr
	shorthand for a smart pointer to a factor.

Static Public Attributes
static const int	Dim = traits<CAMERA>::dimension
	Camera dimension.

static const int	ZDim = traits<Z>::dimension
	Measurement dimension.

Static Protected Member Functions
Standard Constructors
template<typename CONTAINER >
static Factor	FromKeys (const CONTAINER &keys)

template<typename ITERATOR >
static Factor	FromIterators (ITERATOR first, ITERATOR last)

Protected Attributes
SharedIsotropic	noiseModel_

ZVector	measured_

std::optional< Pose3 >	body_P_sensor_
	Pose of the camera in the body frame.

FBlocks	Fs

KeyVector	keys_
	The keys involved in this factor.

Detailed Description

template<class CAMERA>
class gtsam::SmartFactorBase< CAMERA >

Base class for smart factors. This base class has no internal point, but it has a measurement, noise model and an optional sensor pose. This class mainly computes the derivatives and returns them as a variety of factors. The methods take a CameraSet<CAMERA> argument and the value of a point, which is kept in the derived class.

Template Parameters

CAMERA should behave like a PinholeCamera.

Member Function Documentation

◆ active()

virtual bool gtsam::NonlinearFactor::active ( const Values & ) const

inlinevirtualinherited

Checks whether a factor should be used based on a set of values. This is primarily used to implement inequality constraints that require a variable active set. For all others, the default implementation returning true solves this problem.

In an inequality/bounding constraint, this active() returns true when the constraint is NOT fulfilled.

Returns: true if the constraint is active

Reimplemented in gtsam::BoundingConstraint2< VALUE1, VALUE2 >, gtsam::AntiFactor, and gtsam::BoundingConstraint1< VALUE >.

◆ add() [1/2]

template<class CAMERA>

void gtsam::SmartFactorBase< CAMERA >::add	(	const Z &	measured,
		const Key &	key
	)

inline

Add a new measurement and pose/camera key.

Parameters

measured	is the 2m dimensional projection of a single landmark
key	is the index corresponding to the camera observing the landmark

◆ add() [2/2]

template<class CAMERA>

template<class SFM_TRACK >

void gtsam::SmartFactorBase< CAMERA >::add ( const SFM_TRACK & trackToAdd )

inline

Add an entire SfM_track (collection of cameras observing a single point). The noise is assumed to be the same for all measurements.

◆ begin() [1/2]

const_iterator gtsam::Factor::begin ( ) const

inlineinherited

Iterator at beginning of involved variable keys

◆ begin() [2/2]

iterator gtsam::Factor::begin ( )

inlineinherited

Iterator at beginning of involved variable keys

◆ clone()

virtual shared_ptr gtsam::NonlinearFactor::clone ( ) const

inlinevirtualinherited

Creates a shared_ptr clone of the factor - needs to be specialized to allow for subclasses

By default, throws exception if subclass does not implement the function.

Reimplemented in gtsam::EssentialMatrixFactor4< CALIBRATION >, gtsam::NonlinearEquality2< T >, gtsam::CombinedImuFactor, gtsam::ImuFactor2, gtsam::EssentialMatrixFactor3, gtsam::NonlinearEquality1< VALUE >, gtsam::GeneralSFMFactor2< CALIBRATION >, gtsam::ImuFactor, gtsam::LinearizedHessianFactor, gtsam::PendulumFactorPk1, gtsam::FunctorizedFactor2< R, T1, T2 >, gtsam::MagFactor3, gtsam::Pose3AttitudeFactor, gtsam::SmartRangeFactor, gtsam::NonlinearEquality< VALUE >, gtsam::AHRSFactor, gtsam::EssentialMatrixFactor2, gtsam::ExpressionFactor< T >, gtsam::ExpressionFactor< BearingRange< A1, A2 > >, gtsam::ExpressionFactor< double >, gtsam::MagFactor2, gtsam::PendulumFactorPk, gtsam::GPSFactor2, gtsam::ProjectionFactorRollingShutter, gtsam::RangeFactorWithTransform< A1, A2, T >, gtsam::LinearContainerFactor, gtsam::LinearizedJacobianFactor, gtsam::Rot3AttitudeFactor, gtsam::MagFactor1, gtsam::GenericProjectionFactor< POSE, LANDMARK, CALIBRATION >, gtsam::DiscreteEulerPoincareHelicopter, gtsam::MultiProjectionFactor< POSE, LANDMARK, CALIBRATION >, gtsam::GeneralSFMFactor< CAMERA, LANDMARK >, gtsam::ProjectionFactorPPP< POSE, LANDMARK, CALIBRATION >, gtsam::TransformBtwRobotsUnaryFactorEM< VALUE >, gtsam::GenericStereoFactor< POSE, LANDMARK >, gtsam::TriangulationFactor< CAMERA >, gtsam::RotateDirectionsFactor, gtsam::PendulumFactor2, gtsam::ReferenceFrameFactor< POINT, TRANSFORM >, gtsam::FunctorizedFactor< R, T >, gtsam::PartialPriorFactor< VALUE >, gtsam::FunctorizedFactor< Vector, ParameterMatrix< M > >, gtsam::FunctorizedFactor< double, BASIS::Parameters >, gtsam::FunctorizedFactor< double, Vector >, gtsam::FunctorizedFactor< T, ParameterMatrix< traits< T >::dimension > >, gtsam::FunctorizedFactor< double, ParameterMatrix< P > >, gtsam::PartialPriorFactor< PoseRTV >, gtsam::MagPoseFactor< POSE >, gtsam::ProjectionFactorPPPC< POSE, LANDMARK, CALIBRATION >, gtsam::TransformBtwRobotsUnaryFactor< VALUE >, gtsam::BetweenFactor< VALUE >, gtsam::EssentialMatrixFactor, gtsam::VelocityConstraint, gtsam::PriorFactor< VALUE >, gtsam::GPSFactor, gtsam::PoseToPointFactor< POSE, POINT >, gtsam::BarometricFactor, gtsam::EssentialMatrixConstraint, gtsam::DummyFactor, gtsam::PoseBetweenFactor< POSE >, gtsam::BearingRangeFactor< A1, A2, B, R >, gtsam::PosePriorFactor< POSE >, gtsam::MagFactor, gtsam::PoseTranslationPrior< POSE >, gtsam::PoseRotationPrior< POSE >, gtsam::FullIMUFactor< POSE >, gtsam::AntiFactor, gtsam::RangeFactor< A1, A2, T >, gtsam::IMUFactor< POSE >, gtsam::RelativeElevationFactor, gtsam::PendulumFactor1, gtsam::Reconstruction, gtsam::RotateFactor, and gtsam::VelocityConstraint3.

◆ computeJacobians()

template<class CAMERA>

template<class POINT >

void gtsam::SmartFactorBase< CAMERA >::computeJacobians	(	FBlocks &	Fs,
		Matrix &	E,
		Vector &	b,
		const Cameras &	cameras,
		const POINT &	point
	)		const

inline

Compute F, E, and b (called below in both vanilla and SVD versions), where F is a vector of derivatives wrpt the cameras, and E the stacked derivatives with respect to the point. The value of cameras/point are passed as parameters.

◆ computeJacobiansSVD()

template<class CAMERA>

template<class POINT >

void gtsam::SmartFactorBase< CAMERA >::computeJacobiansSVD	(	FBlocks &	Fs,
		Matrix &	Enull,
		Vector &	b,
		const Cameras &	cameras,
		const POINT &	point
	)		const

inline

SVD version that produces smaller Jacobian matrices by doing an SVD decomposition on E, and returning the left nulkl-space of E. See JacobianFactorSVD for more documentation.

◆ correctForMissingMeasurements() [1/2]

template<class CAMERA>

virtual void gtsam::SmartFactorBase< CAMERA >::correctForMissingMeasurements	(	const Cameras &	cameras,
		Vector &	ue,
		typename Cameras::FBlocks *	Fs = `nullptr`,
		Matrix *	E = `nullptr`
	)		const

inlinevirtual

This corrects the Jacobians for the case in which some 2D measurement is missing (nan). In practice, this does not do anything in the monocular case, but it is implemented in the stereo version.

Reimplemented in gtsam::SmartStereoProjectionFactor.

◆ correctForMissingMeasurements() [2/2]

template<class CAMERA>

template<class ... OptArgs>

void gtsam::SmartFactorBase< CAMERA >::correctForMissingMeasurements	(	const Cameras &	cameras,
		Vector &	ue,
		OptArgs &&...	optArgs
	)		const

inline

An overload of correctForMissingMeasurements. This allows end users to provide optional arguments that are l-value references to the matrices and vectors that will be used to store the results instead of pointers.

◆ createJacobianSVDFactor()

template<class CAMERA>

std::shared_ptr<JacobianFactor> gtsam::SmartFactorBase< CAMERA >::createJacobianSVDFactor	(	const Cameras &	cameras,
		const Point3 &	point,
		double	lambda = `0.0`
	)		const

inline

Return Jacobians as JacobianFactorSVD. TODO(dellaert): lambda is currently ignored

◆ end() [1/2]

const_iterator gtsam::Factor::end ( ) const

inlineinherited

Iterator at end of involved variable keys

◆ end() [2/2]

iterator gtsam::Factor::end ( )

inlineinherited

Iterator at end of involved variable keys

◆ error()

double gtsam::NonlinearFactor::error ( const HybridValues & c ) const

overridevirtualinherited

All factor types need to implement an error function. In factor graphs, this is the negative log-likelihood.

Reimplemented from gtsam::Factor.

◆ FromIterators()

template<typename ITERATOR >

static Factor gtsam::Factor::FromIterators	(	ITERATOR	first,
		ITERATOR	last
	)

inlinestaticprotectedinherited

Construct factor from iterator keys. This is called internally from derived factor static factor methods, as a workaround for not being able to call the protected constructors above.

◆ FromKeys()

template<typename CONTAINER >

static Factor gtsam::Factor::FromKeys ( const CONTAINER & keys )

inlinestaticprotectedinherited

Construct factor from container of keys. This is called internally from derived factor static factor methods, as a workaround for not being able to call the protected constructors above.

◆ keys()

KeyVector& gtsam::Factor::keys ( )

inlineinherited

Returns: keys involved in this factor

◆ linearize()

virtual std::shared_ptr<GaussianFactor> gtsam::NonlinearFactor::linearize ( const Values & c ) const

pure virtualinherited

linearize to a GaussianFactor

Implemented in gtsam::SmartProjectionPoseFactorRollingShutter< CAMERA >, gtsam::SmartProjectionRigFactor< CAMERA >, gtsam::SmartStereoProjectionFactor, gtsam::SmartProjectionFactor< CAMERA >, gtsam::SmartProjectionFactor< PinholePose< CALIBRATION > >, gtsam::NoiseModelFactor, gtsam::SmartStereoProjectionFactorPP, gtsam::LinearizedHessianFactor, gtsam::TransformBtwRobotsUnaryFactorEM< VALUE >, gtsam::NonlinearEquality< VALUE >, gtsam::WhiteNoiseFactor, gtsam::TriangulationFactor< CAMERA >, gtsam::LinearizedJacobianFactor, gtsam::TransformBtwRobotsUnaryFactor< VALUE >, gtsam::GeneralSFMFactor< CAMERA, LANDMARK >, gtsam::BetweenFactorEM< VALUE >, gtsam::ExpressionFactor< T >, gtsam::ExpressionFactor< BearingRange< A1, A2 > >, gtsam::ExpressionFactor< double >, gtsam::LinearContainerFactor, gtsam::ShonanGaugeFactor, gtsam::AntiFactor, gtsam::KarcherMeanFactor< T >, gtsam::DummyFactor, and gtsam::PinholeFactor.

◆ print()

template<class CAMERA>

void gtsam::SmartFactorBase< 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::NonlinearFactor.

Reimplemented in gtsam::SmartProjectionPoseFactorRollingShutter< CAMERA >, gtsam::SmartProjectionRigFactor< CAMERA >, gtsam::SmartProjectionFactor< CAMERA >, and gtsam::SmartProjectionFactor< PinholePose< CALIBRATION > >.

◆ rekey() [1/2]

virtual shared_ptr gtsam::NonlinearFactor::rekey ( const std::map< Key, Key > & rekey_mapping ) const

virtualinherited

Creates a shared_ptr clone of the factor with different keys using a map from old->new keys

Reimplemented in gtsam::LinearContainerFactor.

◆ rekey() [2/2]

virtual shared_ptr gtsam::NonlinearFactor::rekey ( const KeyVector & new_keys ) const

virtualinherited

Clones a factor and fully replaces its keys

Parameters

new_keys is the full replacement set of keys

Reimplemented in gtsam::LinearContainerFactor.

◆ sendable()

virtual bool gtsam::NonlinearFactor::sendable ( ) const

inlinevirtualinherited

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)

Reimplemented in gtsam::CustomFactor.

◆ size()

size_t gtsam::Factor::size ( ) const

inlineinherited

Returns: the number of variables involved in this factor

◆ totalReprojectionError()

template<class CAMERA>

template<class POINT >

double gtsam::SmartFactorBase< CAMERA >::totalReprojectionError	(	const Cameras &	cameras,
		const POINT &	point
	)		const

inline

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. Will be used in "error(Values)" function required by NonlinearFactor base class

◆ unwhitenedError() [1/2]

template<class CAMERA>

template<class POINT >

Vector gtsam::SmartFactorBase< CAMERA >::unwhitenedError	(	const Cameras &	cameras,
		const POINT &	point,
		typename Cameras::FBlocks *	Fs = `nullptr`,
		Matrix *	E = `nullptr`
	)		const

inline

Compute reprojection errors [h(x)-z] = [cameras.project(p)-z] and derivatives. This is the error before the noise model is applied. The templated version described above must finally get resolved to this function.

◆ unwhitenedError() [2/2]

template<class CAMERA>

template<class POINT , class ... OptArgs, typename = std::enable_if_t<sizeof...(OptArgs)!=0>>

Vector gtsam::SmartFactorBase< CAMERA >::unwhitenedError	(	const Cameras &	cameras,
		const POINT &	point,
		OptArgs &&...	optArgs
	)		const

inline

An overload of unwhitenedError. This allows end users to provide optional arguments that are l-value references to the matrices and vectors that will be used to store the results instead of pointers.

◆ updateAugmentedHessian()

template<class CAMERA>

void gtsam::SmartFactorBase< CAMERA >::updateAugmentedHessian	(	const Cameras &	cameras,
		const Point3 &	point,
		const double	lambda,
		bool	diagonalDamping,
		SymmetricBlockMatrix &	augmentedHessian,
		const KeyVector	allKeys
	)		const

inline

Add the contribution of the smart factor to a pre-allocated Hessian, using sparse linear algebra. More efficient than the creation of the Hessian without preallocation of the SymmetricBlockMatrix

◆ whitenedError()

template<class CAMERA>

template<class POINT >

Vector gtsam::SmartFactorBase< CAMERA >::whitenedError	(	const Cameras &	cameras,
		const POINT &	point
	)		const

inline

Calculate vector of re-projection errors [h(x)-z] = [cameras.project(p) - z], with the noise model applied.

Member Data Documentation

◆ measured_

template<class CAMERA>

ZVector gtsam::SmartFactorBase< CAMERA >::measured_

protected

Measurements for each of the m views. We keep a copy of the measurements for I/O and computing the error. The order is kept the same as the keys that we use to create the factor.

◆ noiseModel_

template<class CAMERA>

SharedIsotropic gtsam::SmartFactorBase< CAMERA >::noiseModel_

protected

As of Feb 22, 2015, the noise model is the same for all measurements and is isotropic. This allows for moving most calculations of Schur complement etc. to be easily moved to CameraSet, and also agrees pragmatically with what is normally done.

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

/home/docs/checkouts/readthedocs.org/user_builds/gtsam-jlblanco-docs/checkouts/latest/gtsam/slam/SmartFactorBase.h

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Static Protected Member Functions

Protected Attributes

Detailed Description

template<class CAMERA> class gtsam::SmartFactorBase< CAMERA >

Member Function Documentation

◆ active()

◆ add() [1/2]

◆ add() [2/2]

◆ begin() [1/2]

◆ begin() [2/2]

◆ clone()

◆ computeJacobians()

◆ computeJacobiansSVD()

◆ correctForMissingMeasurements() [1/2]

◆ correctForMissingMeasurements() [2/2]

◆ createJacobianSVDFactor()

◆ end() [1/2]

◆ end() [2/2]

◆ error()

◆ FromIterators()

◆ FromKeys()

◆ keys()

◆ linearize()

◆ print()

◆ rekey() [1/2]

◆ rekey() [2/2]

◆ sendable()

◆ size()

◆ totalReprojectionError()

◆ unwhitenedError() [1/2]

◆ unwhitenedError() [2/2]

◆ updateAugmentedHessian()

◆ whitenedError()

Member Data Documentation

◆ measured_

◆ noiseModel_

template<class CAMERA>
class gtsam::SmartFactorBase< CAMERA >