#include <ISAM2.h>

Inheritance diagram for gtsam::ISAM2:

Collaboration diagram for gtsam::ISAM2:

[legend]

Public Types
using	This = ISAM2
	This class.

using	Base = BayesTree< ISAM2Clique >
	The BayesTree base class.

using	Clique = Base::Clique
	A clique.

using	sharedClique = Base::sharedClique
	Shared pointer to a clique.

using	Cliques = Base::Cliques
	List of Cliques.

typedef Clique	Node
	Synonym for Clique (TODO: remove)

typedef sharedClique	sharedNode
	Synonym for sharedClique (TODO: remove)

typedef ISAM2Clique ::ConditionalType	ConditionalType

typedef std::shared_ptr< ConditionalType >	sharedConditional

typedef ISAM2Clique ::BayesNetType	BayesNetType

typedef std::shared_ptr< BayesNetType >	sharedBayesNet

typedef ISAM2Clique ::FactorType	FactorType

typedef std::shared_ptr< FactorType >	sharedFactor

typedef ISAM2Clique ::FactorGraphType	FactorGraphType

typedef std::shared_ptr< FactorGraphType >	sharedFactorGraph

typedef FactorGraphType::Eliminate	Eliminate

typedef ISAM2Clique ::EliminationTraitsType	EliminationTraitsType

typedef ConcurrentMap< Key, sharedClique >	Nodes

typedef FastVector< sharedClique >	Roots

Public Member Functions
	ISAM2 (const ISAM2Params &params)

	ISAM2 ()

virtual	~ISAM2 ()

virtual bool	equals (const ISAM2 &other, double tol=1e-9) const

virtual ISAM2Result	update (const NonlinearFactorGraph &newFactors=NonlinearFactorGraph(), const Values &newTheta=Values(), const FactorIndices &removeFactorIndices=FactorIndices(), const std::optional< FastMap< Key, int > > &constrainedKeys={}, const std::optional< FastList< Key > > &noRelinKeys={}, const std::optional< FastList< Key > > &extraReelimKeys={}, bool force_relinearize=false)

virtual ISAM2Result	update (const NonlinearFactorGraph &newFactors, const Values &newTheta, const ISAM2UpdateParams &updateParams)

void	marginalizeLeaves (const FastList< Key > &leafKeys, FactorIndices marginalFactorsIndices=nullptr, FactorIndices deletedFactorsIndices=nullptr)

template<class... OptArgs>
void	marginalizeLeaves (const FastList< Key > &leafKeys, OptArgs &&... optArgs)

const Values &	getLinearizationPoint () const
	Access the current linearization point.

bool	valueExists (Key key) const
	Check whether variable with given key exists in linearization point.

Values	calculateEstimate () const

template<class VALUE >
VALUE	calculateEstimate (Key key) const

const Value &	calculateEstimate (Key key) const

Matrix	marginalCovariance (Key key) const

Public members for non-typical usage
Values	calculateBestEstimate () const

const VectorValues &	getDelta () const

double	error (const VectorValues &x) const

const NonlinearFactorGraph &	getFactorsUnsafe () const

const VariableIndex &	getVariableIndex () const

const KeySet &	getFixedVariables () const

const ISAM2Params &	params () const

void	printStats () const

VectorValues	gradientAtZero () const

Standard Interface
size_t	size () const

bool	empty () const

const Nodes &	nodes () const

sharedClique	operator[] (Key j) const

const Roots &	roots () const

const sharedClique &	clique (Key j) const

BayesTreeCliqueData	getCliqueData () const

size_t	numCachedSeparatorMarginals () const

sharedConditional	marginalFactor (Key j, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

sharedFactorGraph	joint (Key j1, Key j2, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

sharedBayesNet	jointBayesNet (Key j1, Key j2, const Eliminate &function=EliminationTraitsType::DefaultEliminate) const

Graph Display
void	dot (std::ostream &os, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	Output to graphviz format, stream version.

std::string	dot (const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	Output to graphviz format string.

void	saveGraph (const std::string &filename, const KeyFormatter &keyFormatter=DefaultKeyFormatter) const
	output to file with graphviz format.

Protected Types
typedef std::shared_ptr< This >	shared_ptr

Protected Member Functions
void	recalculate (const ISAM2UpdateParams &updateParams, const KeySet &relinKeys, ISAM2Result *result)
	Remove marked top and either recalculate in batch or incrementally.

void	recalculateBatch (const ISAM2UpdateParams &updateParams, KeySet affectedKeysSet, ISAM2Result result)

GaussianFactorGraph	relinearizeAffectedFactors (const ISAM2UpdateParams &updateParams, const FastList< Key > &affectedKeys, const KeySet &relinKeys)

void	recalculateIncremental (const ISAM2UpdateParams &updateParams, const KeySet &relinKeys, const FastList< Key > &affectedKeys, KeySet affectedKeysSet, Cliques orphans, ISAM2Result *result)
	Perform an incremental update of the factor graph to return a new Bayes Tree with affected keys. More...

void	addVariables (const Values &newTheta, ISAM2Result::DetailedResults *detail=0)

void	removeVariables (const KeySet &unusedKeys)

void	updateDelta (bool forceFullSolve=false) const

Protected Attributes
Values	theta_

VariableIndex	variableIndex_

VectorValues	delta_

VectorValues	deltaNewton_

VectorValues	RgProd_

KeySet	deltaReplacedMask_

NonlinearFactorGraph	nonlinearFactors_

GaussianFactorGraph	linearFactors_

ISAM2Params	params_

std::optional< double >	doglegDelta_

KeySet	fixedVariables_

int	update_count_

Nodes	nodes_

Roots	roots_

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

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

Advanced Interface
Key	findParentClique (const CONTAINER &parents) const

void	clear ()

void	deleteCachedShortcuts ()

void	removePath (sharedClique clique, BayesNetType bn, Cliques orphans)

void	removeTop (const KeyVector &keys, BayesNetType bn, Cliques orphans)

Cliques	removeSubtree (const sharedClique &subtree)

void	insertRoot (const sharedClique &subtree)

void	addClique (const sharedClique &clique, const sharedClique &parent_clique=sharedClique())

void	addFactorsToGraph (FactorGraph< FactorType > *graph) const

void	getCliqueData (sharedClique clique, BayesTreeCliqueData *stats) const

void	dot (std::ostream &s, sharedClique clique, const KeyFormatter &keyFormatter, int parentnum=0) const

void	removeClique (sharedClique clique)

void	fillNodesIndex (const sharedClique &subtree)

Detailed Description

Implementation of the full ISAM2 algorithm for incremental nonlinear optimization.

The typical cycle of using this class to create an instance by providing ISAM2Params to the constructor, then add measurements and variables as they arrive using the update() method. At any time, calculateEstimate() may be called to obtain the current estimate of all variables.

Member Typedef Documentation

◆ Nodes

typedef ConcurrentMap<Key, sharedClique> gtsam::BayesTree< ISAM2Clique >::Nodes

inherited

Map from keys to Clique

◆ Roots

typedef FastVector<sharedClique> gtsam::BayesTree< ISAM2Clique >::Roots

inherited

Root cliques

Constructor & Destructor Documentation

◆ ISAM2() [1/2]

gtsam::ISAM2::ISAM2 ( const ISAM2Params & params )

explicit

Create an empty ISAM2 instance

◆ ISAM2() [2/2]

gtsam::ISAM2::ISAM2 ( )

Create an empty ISAM2 instance using the default set of parameters (see ISAM2Params)

◆ ~ISAM2()

virtual gtsam::ISAM2::~ISAM2 ( )

inlinevirtual

default virtual destructor

Member Function Documentation

◆ addClique()

void gtsam::BayesTree< ISAM2Clique >::addClique	(	const sharedClique &	clique,
		const sharedClique &	parent_clique = `sharedClique()`
	)

inherited

add a clique (top down)

◆ addFactorsToGraph()

void gtsam::BayesTree< ISAM2Clique >::addFactorsToGraph ( FactorGraph< FactorType > * graph ) const

inherited

Add all cliques in this BayesTree to the specified factor graph

◆ addVariables()

void gtsam::ISAM2::addVariables	(	const Values &	newTheta,
		ISAM2Result::DetailedResults *	detail = `0`
	)

protected

Add new variables to the ISAM2 system.

Parameters

newTheta	Initial values for new variables
variableStatus	optional detailed result structure

◆ calculateBestEstimate()

Values gtsam::ISAM2::calculateBestEstimate ( ) const

Compute an estimate using a complete delta computed by a full back-substitution.

◆ calculateEstimate() [1/3]

Values gtsam::ISAM2::calculateEstimate ( ) const

Compute an estimate from the incomplete linear delta computed during the last update. This delta is incomplete because it was not updated below wildfire_threshold. If only a single variable is needed, it is faster to call calculateEstimate(const KEY&).

◆ calculateEstimate() [2/3]

template<class VALUE >

VALUE gtsam::ISAM2::calculateEstimate ( Key key ) const

inline

Compute an estimate for a single variable using its incomplete linear delta computed during the last update. This is faster than calling the no-argument version of calculateEstimate, which operates on all variables.

Parameters

key

Returns

◆ calculateEstimate() [3/3]

const Value& gtsam::ISAM2::calculateEstimate ( Key key ) const

Compute an estimate for a single variable using its incomplete linear delta computed during the last update. This is faster than calling the no-argument version of calculateEstimate, which operates on all variables. This is a non-templated version that returns a Value base class for use with the MATLAB wrapper.

Parameters

key

Returns

◆ clear()

void gtsam::BayesTree< ISAM2Clique >::clear ( )

inherited

Remove all nodes

◆ clique()

const sharedClique& gtsam::BayesTree< ISAM2Clique >::clique ( Key j ) const

inlineinherited

alternate syntax for matlab: find the clique that contains the variable with Key j

◆ deleteCachedShortcuts()

void gtsam::BayesTree< ISAM2Clique >::deleteCachedShortcuts ( )

inherited

Clear all shortcut caches - use before timing on marginal calculation to avoid residual cache data

◆ dot()

void gtsam::BayesTree< ISAM2Clique >::dot	(	std::ostream &	s,
		sharedClique	clique,
		const KeyFormatter &	keyFormatter,
		int	parentnum = `0`
	)		const

protectedinherited

private helper method for saving the Tree to a text file in GraphViz format

◆ empty()

bool gtsam::BayesTree< ISAM2Clique >::empty ( ) const

inlineinherited

Check if there are any cliques in the tree

◆ equals() [1/2]

virtual bool gtsam::ISAM2::equals	(	const ISAM2 &	other,
		double	tol = `1e-9`
	)		const

virtual

Compare equality

◆ equals() [2/2]

bool gtsam::BayesTree< ISAM2Clique >::equals	(	const This &	other,
		double	tol = `1e-9`
	)		const

protectedinherited

check equality

◆ error()

double gtsam::ISAM2::error ( const VectorValues & x ) const

Compute the linear error

◆ fillNodesIndex()

void gtsam::BayesTree< ISAM2Clique >::fillNodesIndex ( const sharedClique & subtree )

protectedinherited

Fill the nodes index for a subtree

◆ findParentClique()

Key gtsam::BayesTree< ISAM2Clique >::findParentClique ( const CONTAINER & parents ) const

inherited

Find parent clique of a conditional. It will look at all parents and return the one with the lowest index in the ordering.

◆ getCliqueData() [1/2]

BayesTreeCliqueData gtsam::BayesTree< ISAM2Clique >::getCliqueData ( ) const

inherited

Gather data on all cliques

◆ getCliqueData() [2/2]

void gtsam::BayesTree< ISAM2Clique >::getCliqueData	(	sharedClique	clique,
		BayesTreeCliqueData *	stats
	)		const

protectedinherited

Gather data on a single clique

◆ getDelta()

const VectorValues& gtsam::ISAM2::getDelta ( ) const

Access the current delta, computed during the last call to update

◆ getFactorsUnsafe()

const NonlinearFactorGraph& gtsam::ISAM2::getFactorsUnsafe ( ) const

inline

Access the set of nonlinear factors

◆ getFixedVariables()

const KeySet& gtsam::ISAM2::getFixedVariables ( ) const

inline

Access the nonlinear variable index

◆ getVariableIndex()

const VariableIndex& gtsam::ISAM2::getVariableIndex ( ) const

inline

Access the nonlinear variable index

◆ gradientAtZero()

VectorValues gtsam::ISAM2::gradientAtZero ( ) const

Compute the gradient of the energy function, \( \nabla_{x=0} \left\Vert \Sigma^{-1} R x - d \right\Vert^2 \), centered around zero. The gradient about zero is \( -R^T d \). See also gradient(const GaussianBayesNet&, const VectorValues&).

Returns: A VectorValues storing the gradient.

◆ insertRoot()

void gtsam::BayesTree< ISAM2Clique >::insertRoot ( const sharedClique & subtree )

inherited

Insert a new subtree with known parent clique. This function does not check that the specified parent is the correct parent. This function updates all of the internal data structures associated with adding a subtree, such as populating the nodes index.

◆ joint()

BayesTree< ISAM2Clique >::sharedFactorGraph gtsam::BayesTree< ISAM2Clique >::joint	(	Key	j1,
		Key	j2,
		const Eliminate &	function = `EliminationTraitsType::DefaultEliminate`
	)		const

inherited

return joint on two variables Limitation: can only calculate joint if cliques are disjoint or one of them is root

◆ jointBayesNet()

BayesTree< ISAM2Clique >::sharedBayesNet gtsam::BayesTree< ISAM2Clique >::jointBayesNet	(	Key	j1,
		Key	j2,
		const Eliminate &	function = `EliminationTraitsType::DefaultEliminate`
	)		const

inherited

return joint on two variables as a BayesNet Limitation: can only calculate joint if cliques are disjoint or one of them is root

◆ marginalCovariance()

Matrix gtsam::ISAM2::marginalCovariance ( Key key ) const

Return marginal on any variable as a covariance matrix

◆ marginalFactor()

BayesTree< ISAM2Clique >::sharedConditional gtsam::BayesTree< ISAM2Clique >::marginalFactor	(	Key	j,
		const Eliminate &	function = `EliminationTraitsType::DefaultEliminate`
	)		const

inherited

Return marginal on any variable. Note that this actually returns a conditional, for which a solution may be directly obtained by calling .solve() on the returned object. Alternatively, it may be directly used as its factor base class. For example, for Gaussian systems, this returns a GaussianConditional, which inherits from JacobianFactor and GaussianFactor.

◆ marginalizeLeaves() [1/2]

void gtsam::ISAM2::marginalizeLeaves	(	const FastList< Key > &	leafKeys,
		FactorIndices *	marginalFactorsIndices = `nullptr`,
		FactorIndices *	deletedFactorsIndices = `nullptr`
	)

Marginalize out variables listed in leafKeys. These keys must be leaves in the BayesTree. Throws MarginalizeNonleafException if non-leaves are requested to be marginalized. Marginalization leaves a linear approximation of the marginal in the system, and the linearization points of any variables involved in this linear marginal become fixed. The set fixed variables will include any key involved with the marginalized variables in the original factors, and possibly additional ones due to fill-in.

If provided, 'marginalFactorsIndices' will be augmented with the factor graph indices of the marginal factors added during the 'marginalizeLeaves' call

If provided, 'deletedFactorsIndices' will be augmented with the factor graph indices of any factor that was removed during the 'marginalizeLeaves' call

◆ marginalizeLeaves() [2/2]

template<class... OptArgs>

void gtsam::ISAM2::marginalizeLeaves	(	const FastList< Key > &	leafKeys,
		OptArgs &&...	optArgs
	)

inline

An overload of marginalizeLeaves that takes references to vectors instead of pointers to vectors and passes it to the pointer version of the function.

◆ nodes()

const Nodes& gtsam::BayesTree< ISAM2Clique >::nodes ( ) const

inlineinherited

Return nodes. Each node is a clique of variables obtained after elimination.

◆ numCachedSeparatorMarginals()

size_t gtsam::BayesTree< ISAM2Clique >::numCachedSeparatorMarginals ( ) const

inherited

Collect number of cliques with cached separator marginals

◆ operator[]()

sharedClique gtsam::BayesTree< ISAM2Clique >::operator[] ( Key j ) const

inlineinherited

Access node by variable

◆ print()

void gtsam::BayesTree< ISAM2Clique >::print	(	const std::string &	s = `""`,
		const KeyFormatter &	keyFormatter = `DefaultKeyFormatter`
	)		const

inherited

print

◆ printStats()

void gtsam::ISAM2::printStats ( ) const

inline

prints out clique statistics

◆ recalculateIncremental()

void gtsam::ISAM2::recalculateIncremental	(	const ISAM2UpdateParams &	updateParams,
		const KeySet &	relinKeys,
		const FastList< Key > &	affectedKeys,
		KeySet *	affectedKeysSet,
		Cliques *	orphans,
		ISAM2Result *	result
	)

protected

Perform an incremental update of the factor graph to return a new Bayes Tree with affected keys.

Parameters

updateParams	Parameters for the ISAM2 update.
relinKeys	Keys of variables to relinearize.
affectedKeys	The set of keys which are affected in the update.
affectedKeysSet	[output] Affected and contaminated keys.
orphans	[output] List of orphanes cliques after elimination.
result	[output] The result of the incremental update step.

◆ removeClique()

void gtsam::BayesTree< ISAM2Clique >::removeClique ( sharedClique clique )

protectedinherited

remove a clique: warning, can result in a forest

◆ removePath()

void gtsam::BayesTree< ISAM2Clique >::removePath	(	sharedClique	clique,
		BayesNetType *	bn,
		Cliques *	orphans
	)

inherited

Remove path from clique to root and return that path as factors plus a list of orphaned subtree roots. Used in removeTop below.

◆ removeSubtree()

BayesTree< ISAM2Clique >::Cliques gtsam::BayesTree< ISAM2Clique >::removeSubtree ( const sharedClique & subtree )

inherited

Remove the requested subtree.

◆ removeTop()

void gtsam::BayesTree< ISAM2Clique >::removeTop	(	const KeyVector &	keys,
		BayesNetType *	bn,
		Cliques *	orphans
	)

inherited

Given a list of indices, turn "contaminated" part of the tree back into a factor graph. Factors and orphans are added to the in/out arguments.

◆ removeVariables()

void gtsam::ISAM2::removeVariables ( const KeySet & unusedKeys )

protected

Remove variables from the ISAM2 system.

◆ roots()

const Roots& gtsam::BayesTree< ISAM2Clique >::roots ( ) const

inlineinherited

return root cliques

◆ size()

size_t gtsam::BayesTree< ISAM2Clique >::size ( ) const

inherited

number of cliques

◆ update() [1/2]

virtual ISAM2Result gtsam::ISAM2::update	(	const NonlinearFactorGraph &	newFactors = `NonlinearFactorGraph()`,
		const Values &	newTheta = `Values()`,
		const FactorIndices &	removeFactorIndices = `FactorIndices()`,
		const std::optional< FastMap< Key, int > > &	constrainedKeys = `{}`,
		const std::optional< FastList< Key > > &	noRelinKeys = `{}`,
		const std::optional< FastList< Key > > &	extraReelimKeys = `{}`,
		bool	force_relinearize = `false`
	)

virtual

Add new factors, updating the solution and relinearizing as needed.

Optionally, this function remove existing factors from the system to enable behaviors such as swapping existing factors with new ones.

Add new measurements, and optionally new variables, to the current system. This runs a full step of the ISAM2 algorithm, relinearizing and updating the solution as needed, according to the wildfire and relinearize thresholds.

Parameters

newFactors	The new factors to be added to the system
newTheta	Initialization points for new variables to be added to the system. You must include here all new variables occuring in newFactors (which were not already in the system). There must not be any variables here that do not occur in newFactors, and additionally, variables that were already in the system must not be included here.
removeFactorIndices	Indices of factors to remove from system
force_relinearize	Relinearize any variables whose delta magnitude is sufficiently large (Params::relinearizeThreshold), regardless of the relinearization interval (Params::relinearizeSkip).
constrainedKeys	is an optional map of keys to group labels, such that a variable can be constrained to a particular grouping in the BayesTree
noRelinKeys	is an optional set of nonlinear keys that iSAM2 will hold at a constant linearization point, regardless of the size of the linear delta
extraReelimKeys	is an optional set of nonlinear keys that iSAM2 will re-eliminate, regardless of the size of the linear delta. This allows the provided keys to be reordered.

Returns: An ISAM2Result struct containing information about the update

◆ update() [2/2]

virtual ISAM2Result gtsam::ISAM2::update	(	const NonlinearFactorGraph &	newFactors,
		const Values &	newTheta,
		const ISAM2UpdateParams &	updateParams
	)

virtual

Add new factors, updating the solution and relinearizing as needed.

Alternative signature of update() (see its documentation above), with all additional parameters in one structure. This form makes easier to keep future API/ABI compatibility if parameters change.

Parameters

newFactors	The new factors to be added to the system
newTheta	Initialization points for new variables to be added to the system. You must include here all new variables occuring in newFactors (which were not already in the system). There must not be any variables here that do not occur in newFactors, and additionally, variables that were already in the system must not be included here.
updateParams	Additional parameters to control relinearization, constrained keys, etc.

Returns: An ISAM2Result struct containing information about the update

Note: No default parameters to avoid ambiguous call errors.

Member Data Documentation

◆ delta_

VectorValues gtsam::ISAM2::delta_

mutableprotected

The linear delta from the last linear solution, an update to the estimate in theta

This is mutable because it is a "cached" variable - it is not updated until either requested with getDelta() or calculateEstimate(), or needed during update() to evaluate whether to relinearize variables.

◆ deltaReplacedMask_

KeySet gtsam::ISAM2::deltaReplacedMask_

mutableprotected

A cumulative mask for the variables that were replaced and have not yet been updated in the linear solution delta_, this is only used internally, delta will always be updated if necessary when requested with getDelta() or calculateEstimate().

This is mutable because it is used internally to not update delta_ until it is needed.

◆ doglegDelta_

std::optional<double> gtsam::ISAM2::doglegDelta_

mutableprotected

The current Dogleg Delta (trust region radius)

◆ fixedVariables_

KeySet gtsam::ISAM2::fixedVariables_

protected

Set of variables that are involved with linear factors from marginalized variables and thus cannot have their linearization points changed.

◆ linearFactors_

GaussianFactorGraph gtsam::ISAM2::linearFactors_

mutableprotected

The current linear factors, which are only updated as needed

◆ nodes_

Nodes gtsam::BayesTree< ISAM2Clique >::nodes_

protectedinherited

Map from indices to Clique

◆ nonlinearFactors_

NonlinearFactorGraph gtsam::ISAM2::nonlinearFactors_

protected

All original nonlinear factors are stored here to use during relinearization

◆ params_

ISAM2Params gtsam::ISAM2::params_

protected

The current parameters

◆ roots_

Roots gtsam::BayesTree< ISAM2Clique >::roots_

protectedinherited

Root cliques

◆ theta_

Values gtsam::ISAM2::theta_

protected

The current linearization point

◆ update_count_

int gtsam::ISAM2::update_count_

protected

Counter incremented every update(), used to determine periodic relinearization

◆ variableIndex_

VariableIndex gtsam::ISAM2::variableIndex_

protected

VariableIndex lets us look up factors by involved variable and keeps track of dimensions

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

/home/docs/checkouts/readthedocs.org/user_builds/gtsam-jlblanco-docs/checkouts/latest/gtsam/nonlinear/ISAM2.h

Public Types

Public Member Functions

Protected Types

Protected Member Functions

Protected Attributes

Testable

Advanced Interface

Detailed Description

Member Typedef Documentation

◆ Nodes

◆ Roots

Constructor & Destructor Documentation

◆ ISAM2() [1/2]

◆ ISAM2() [2/2]

◆ ~ISAM2()

Member Function Documentation

◆ addClique()

◆ addFactorsToGraph()

◆ addVariables()

◆ calculateBestEstimate()

◆ calculateEstimate() [1/3]

◆ calculateEstimate() [2/3]

◆ calculateEstimate() [3/3]

◆ clear()

◆ clique()

◆ deleteCachedShortcuts()

◆ dot()

◆ empty()

◆ equals() [1/2]

◆ equals() [2/2]

◆ error()

◆ fillNodesIndex()

◆ findParentClique()

◆ getCliqueData() [1/2]

◆ getCliqueData() [2/2]

◆ getDelta()

◆ getFactorsUnsafe()

◆ getFixedVariables()

◆ getVariableIndex()

◆ gradientAtZero()

◆ insertRoot()

◆ joint()

◆ jointBayesNet()

◆ marginalCovariance()

◆ marginalFactor()

◆ marginalizeLeaves() [1/2]

◆ marginalizeLeaves() [2/2]

◆ nodes()

◆ numCachedSeparatorMarginals()

◆ operator[]()

◆ print()

◆ printStats()

◆ recalculateIncremental()

◆ removeClique()

◆ removePath()

◆ removeSubtree()

◆ removeTop()

◆ removeVariables()

◆ roots()

◆ size()

◆ update() [1/2]

◆ update() [2/2]

Member Data Documentation

◆ delta_

◆ deltaReplacedMask_

◆ doglegDelta_

◆ fixedVariables_

◆ linearFactors_

◆ nodes_

◆ nonlinearFactors_

◆ params_

◆ roots_

◆ theta_

◆ update_count_

◆ variableIndex_