#include <sparse_optimizer.h>

Inheritance diagram for g2o::SparseOptimizer:

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Collaboration diagram for g2o::SparseOptimizer:

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Public Types
enum	{ AT_COMPUTEACTIVERROR = OptimizableGraph::AT_NUM_ELEMENTS, AT_NUM_ELEMENTS }

Public Types inherited from g2o::OptimizableGraph
enum	ActionType { AT_PREITERATION, AT_POSTITERATION, AT_NUM_ELEMENTS }

typedef std::set< HyperGraphAction * >	HyperGraphActionSet

typedef std::vector< OptimizableGraph::Vertex * >	VertexContainer
	vector container for vertices More...

typedef std::vector< OptimizableGraph::Edge * >	EdgeContainer
	vector container for edges More...

Public Types inherited from g2o::HyperGraph
typedef std::bitset< HyperGraph::HGET_NUM_ELEMS >	GraphElemBitset

typedef std::set< Edge * >	EdgeSet

typedef std::set< Vertex * >	VertexSet

typedef std::unordered_map< int, Vertex * >	VertexIDMap

typedef std::vector< Vertex * >	VertexContainer

Public Member Functions
	SparseOptimizer ()

virtual	~SparseOptimizer ()

virtual bool	initializeOptimization (HyperGraph::EdgeSet &eset)

virtual bool	initializeOptimization (HyperGraph::VertexSet &vset, int level=0)

virtual bool	initializeOptimization (int level=0)

virtual bool	updateInitialization (HyperGraph::VertexSet &vset, HyperGraph::EdgeSet &eset)

virtual void	computeInitialGuess ()

virtual void	computeInitialGuess (EstimatePropagatorCost &propagator)

virtual void	setToOrigin ()

int	optimize (int iterations, bool online=false)

bool	computeMarginals (SparseBlockMatrix< MatrixXD > &spinv, const std::vector< std::pair< int, int > > &blockIndices)

bool	computeMarginals (SparseBlockMatrix< MatrixXD > &spinv, const Vertex *vertex)

bool	computeMarginals (SparseBlockMatrix< MatrixXD > &spinv, const VertexContainer &vertices)

virtual Vertex *	findGauge ()
	finds a gauge in the graph to remove the undefined dof. More...

bool	gaugeFreedom ()

double	activeChi2 () const

double	activeRobustChi2 () const

bool	verbose () const
	verbose information during optimization More...

void	setVerbose (bool verbose)

void	setForceStopFlag (bool *flag)

bool *	forceStopFlag () const

bool	terminate ()
	if external stop flag is given, return its state. False otherwise More...

const VertexContainer &	indexMapping () const
	the index mapping of the vertices More...

const VertexContainer &	activeVertices () const
	the vertices active in the current optimization More...

const EdgeContainer &	activeEdges () const
	the edges active in the current optimization More...

virtual bool	removeVertex (HyperGraph::Vertex *v, bool detach=false)

VertexContainer::const_iterator	findActiveVertex (const OptimizableGraph::Vertex *v) const

EdgeContainer::const_iterator	findActiveEdge (const OptimizableGraph::Edge *e) const

const OptimizationAlgorithm *	algorithm () const
	the solver used by the optimizer More...

OptimizationAlgorithm *	solver ()

void	setAlgorithm (OptimizationAlgorithm *algorithm)

void	push (SparseOptimizer::VertexContainer &vlist)
	push the estimate of a subset of the variables onto a stack More...

void	push (HyperGraph::VertexSet &vlist)
	push the estimate of a subset of the variables onto a stack More...

void	push ()
	push all the active vertices onto a stack More...

void	pop (SparseOptimizer::VertexContainer &vlist)
	pop (restore) the estimate a subset of the variables from the stack More...

void	pop (HyperGraph::VertexSet &vlist)
	pop (restore) the estimate a subset of the variables from the stack More...

void	pop ()
	pop (restore) the estimate of the active vertices from the stack More...

void	discardTop (SparseOptimizer::VertexContainer &vlist)
	ignore the latest stored element on the stack, remove it from the stack but do not restore the estimate More...

void	discardTop ()
	same as above, but for the active vertices More...

virtual void	clear ()

void	computeActiveErrors ()

const BatchStatisticsContainer &	batchStatistics () const

BatchStatisticsContainer &	batchStatistics ()

void	setComputeBatchStatistics (bool computeBatchStatistics)

bool	computeBatchStatistics () const

bool	addComputeErrorAction (HyperGraphAction *action)
	add an action to be executed before the error vectors are computed More...

bool	removeComputeErrorAction (HyperGraphAction *action)
	remove an action that should no longer be execured before computing the error vectors More...

Public Member Functions inherited from g2o::OptimizableGraph
Vertex *	vertex (int id)
	returns the vertex number id appropriately casted More...

const Vertex *	vertex (int id) const
	returns the vertex number id appropriately casted More...

	OptimizableGraph ()
	empty constructor More...

virtual	~OptimizableGraph ()

void	addGraph (OptimizableGraph *g)
	adds all edges and vertices of the graph g to this graph. More...

virtual bool	addVertex (HyperGraph::Vertex v, Data userData)

virtual bool	addVertex (HyperGraph::Vertex *v)

virtual bool	addEdge (HyperGraph::Edge *e)

virtual bool	setEdgeVertex (HyperGraph::Edge e, int pos, HyperGraph::Vertex v)

double	chi2 () const
	returns the chi2 of the current configuration More...

int	maxDimension () const
	return the maximum dimension of all vertices in the graph More...

std::set< int >	dimensions () const

virtual void	preIteration (int)
	called at the beginning of an iteration (argument is the number of the iteration) More...

virtual void	postIteration (int)
	called at the end of an iteration (argument is the number of the iteration) More...

bool	addPreIterationAction (HyperGraphAction *action)
	add an action to be executed before each iteration More...

bool	addPostIterationAction (HyperGraphAction *action)
	add an action to be executed after each iteration More...

bool	removePreIterationAction (HyperGraphAction *action)
	remove an action that should no longer be execured before each iteration More...

bool	removePostIterationAction (HyperGraphAction *action)
	remove an action that should no longer be execured after each iteration More...

virtual bool	load (std::istream &is, bool createEdges=true)
	load the graph from a stream. Uses the Factory singleton for creating the vertices and edges. More...

bool	load (const char *filename, bool createEdges=true)

virtual bool	save (std::ostream &os, int level=0) const
	save the graph to a stream. Again uses the Factory system. More...

bool	save (const char *filename, int level=0) const
	function provided for convenience, see save() above More...

bool	saveSubset (std::ostream &os, HyperGraph::VertexSet &vset, int level=0)
	save a subgraph to a stream. Again uses the Factory system. More...

bool	saveSubset (std::ostream &os, HyperGraph::EdgeSet &eset)
	save a subgraph to a stream. Again uses the Factory system. More...

virtual void	discardTop (HyperGraph::VertexSet &vset)
	ignore the latest stored element on the stack, remove it from the stack but do not restore the estimate More...

virtual void	setFixed (HyperGraph::VertexSet &vset, bool fixed)
	fixes/releases a set of vertices More...

void	setRenamedTypesFromString (const std::string &types)

bool	isSolverSuitable (const OptimizationAlgorithmProperty &solverProperty, const std::set< int > &vertDims=std::set< int >()) const

virtual void	clearParameters ()

bool	addParameter (Parameter *p)

Parameter *	parameter (int id)

bool	verifyInformationMatrices (bool verbose=false) const

bool	saveVertex (std::ostream &os, Vertex *v) const

bool	saveParameter (std::ostream &os, Parameter *v) const

bool	saveEdge (std::ostream &os, Edge *e) const

bool	saveUserData (std::ostream &os, HyperGraph::Data *v) const

JacobianWorkspace &	jacobianWorkspace ()
	the workspace for storing the Jacobians of the graph More...

const JacobianWorkspace &	jacobianWorkspace () const

ParameterContainer &	parameters ()

const ParameterContainer &	parameters () const

Public Member Functions inherited from g2o::HyperGraph
	HyperGraph ()
	constructs an empty hyper graph More...

virtual	~HyperGraph ()
	destroys the hyper-graph and all the vertices of the graph More...

Vertex *	vertex (int id)
	returns a vertex id in the hyper-graph, or 0 if the vertex id is not present More...

const Vertex *	vertex (int id) const
	returns a vertex id in the hyper-graph, or 0 if the vertex id is not present More...

virtual bool	removeEdge (Edge *e)
	removes a vertex from the graph. Returns true on success (edge was present) More...

const VertexIDMap &	vertices () const

VertexIDMap &	vertices ()

const EdgeSet &	edges () const

EdgeSet &	edges ()

virtual bool	mergeVertices (Vertex vBig, Vertex vSmall, bool erase)

virtual bool	detachVertex (Vertex *v)

virtual bool	changeId (Vertex *v, int newId)

Protected Member Functions
void	sortVectorContainers ()

bool	buildIndexMapping (SparseOptimizer::VertexContainer &vlist)

void	clearIndexMapping ()

Protected Attributes
bool *	_forceStopFlag

bool	_verbose

VertexContainer	_ivMap

VertexContainer	_activeVertices
	sorted according to VertexIDCompare More...

EdgeContainer	_activeEdges
	sorted according to EdgeIDCompare More...

OptimizationAlgorithm *	_algorithm

BatchStatisticsContainer	_batchStatistics
	global statistics of the optimizer, e.g., timing, num-non-zeros More...

bool	_computeBatchStatistics

Protected Attributes inherited from g2o::OptimizableGraph
std::map< std::string, std::string >	_renamedTypesLookup

long long	_nextEdgeId

std::vector< HyperGraphActionSet >	_graphActions

bool	_edge_has_id

ParameterContainer	_parameters

JacobianWorkspace	_jacobianWorkspace

Protected Attributes inherited from g2o::HyperGraph
VertexIDMap	_vertices

EdgeSet	_edges

Friends
class	ActivePathCostFunction

Additional Inherited Members
Static Public Member Functions inherited from g2o::OptimizableGraph
static bool	initMultiThreading ()

Public Attributes inherited from g2o::OptimizableGraph
class G2O_CORE_API	Vertex

class G2O_CORE_API	Edge

Public Attributes inherited from g2o::HyperGraph
class G2O_CORE_API	Data

class G2O_CORE_API	DataContainer

class G2O_CORE_API	Vertex

class G2O_CORE_API	Edge

Static Public Attributes inherited from g2o::HyperGraph
static const int	UnassignedId = -1

static const int	InvalidId = -2

Detailed Description

Definition at line 46 of file sparse_optimizer.h.

Member Enumeration Documentation

anonymous enum

Enumerator
AT_COMPUTEACTIVERROR
AT_NUM_ELEMENTS

Definition at line 49 of file sparse_optimizer.h.

          {
       AT_COMPUTEACTIVERROR = OptimizableGraph::AT_NUM_ELEMENTS,
       AT_NUM_ELEMENTS, // keep as last element
     };

Constructor & Destructor Documentation

g2o::SparseOptimizer::SparseOptimizer ( )

Definition at line 50 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::_graphActions, and AT_NUM_ELEMENTS.

                                    :
     _forceStopFlag(0), _verbose(false), _algorithm(0), _computeBatchStatistics(false)
   {
     _graphActions.resize(AT_NUM_ELEMENTS);
   }

g2o::SparseOptimizer::~SparseOptimizer ( )

virtual

Definition at line 56 of file sparse_optimizer.cpp.

References _algorithm, and g2o::G2OBatchStatistics::setGlobalStats().

                                    {
     delete _algorithm;
     G2OBatchStatistics::setGlobalStats(0);
   }

Member Function Documentation

double g2o::SparseOptimizer::activeChi2 ( ) const

returns the cached chi2 of the active portion of the graph

Definition at line 90 of file sparse_optimizer.cpp.

References _activeEdges, and g2o::OptimizableGraph::Edge::chi2().

Referenced by computeInitialGuess(), g2o::computeSimpleStars(), main(), and g2o::SparseOptimizerOnline::optimize().

   {
     double chi = 0.0;
     for (EdgeContainer::const_iterator it = _activeEdges.begin(); it != _activeEdges.end(); ++it) {
       const OptimizableGraph::Edge* e = *it;
       chi += e->chi2();
     }
     return chi;
   }

const EdgeContainer& g2o::SparseOptimizer::activeEdges ( ) const

inline

the edges active in the current optimization

Definition at line 196 of file sparse_optimizer.h.

Referenced by g2o::activeVertexChi(), g2o::BlockSolver< Traits >::buildStructure(), g2o::BlockSolver< Traits >::buildSystem(), g2o::EstimatePropagatorCost::operator()(), g2o::EstimatePropagatorCostOdometry::operator()(), and g2o::SolverSLAM2DLinear::solveOrientation().

196 { return _activeEdges;}

g2o::SparseOptimizer::_activeEdges

EdgeContainer _activeEdges

sorted according to EdgeIDCompare

Definition: sparse_optimizer.h:296

double g2o::SparseOptimizer::activeRobustChi2 ( ) const

returns the cached chi2 of the active portion of the graph. In contrast to activeChi2() this functions considers the weighting of the error according to the robustification of the error functions.

Definition at line 100 of file sparse_optimizer.cpp.

References _activeEdges, g2o::OptimizableGraph::Edge::chi2(), g2o::RobustKernel::robustify(), and g2o::OptimizableGraph::Edge::robustKernel().

Referenced by g2o::SparseOptimizerTerminateAction::operator()(), optimize(), g2o::OptimizationAlgorithmLevenberg::solve(), and g2o::OptimizationAlgorithmDogleg::solve().

   {
     Vector3D rho;
     double chi = 0.0;
     for (EdgeContainer::const_iterator it = _activeEdges.begin(); it != _activeEdges.end(); ++it) {
       const OptimizableGraph::Edge* e = *it;
       if (e->robustKernel()) {
         e->robustKernel()->robustify(e->chi2(), rho);
         chi += rho[0];
       }
       else
         chi += e->chi2();
     }
     return chi;
   }

const VertexContainer& g2o::SparseOptimizer::activeVertices ( ) const

inline

the vertices active in the current optimization

Definition at line 194 of file sparse_optimizer.h.

Referenced by g2o::OptimizationAlgorithmWithHessian::init(), g2o::StructureOnlySolver< PointDoF >::init(), g2o::Star::labelStarEdges(), main(), and testMarginals().

194 { return _activeVertices;}

g2o::SparseOptimizer::_activeVertices

VertexContainer _activeVertices

sorted according to VertexIDCompare

Definition: sparse_optimizer.h:295

bool g2o::SparseOptimizer::addComputeErrorAction ( HyperGraphAction * action )

add an action to be executed before the error vectors are computed

Definition at line 598 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::_graphActions, and AT_COMPUTEACTIVERROR.

   {
     std::pair<HyperGraphActionSet::iterator, bool> insertResult = _graphActions[AT_COMPUTEACTIVERROR].insert(action);
     return insertResult.second;
   }

const OptimizationAlgorithm* g2o::SparseOptimizer::algorithm ( ) const

inline

the solver used by the optimizer

Definition at line 218 of file sparse_optimizer.h.

Referenced by setAlgorithm().

218 { return _algorithm;}

g2o::SparseOptimizer::_algorithm

OptimizationAlgorithm * _algorithm

Definition: sparse_optimizer.h:300

const BatchStatisticsContainer& g2o::SparseOptimizer::batchStatistics ( ) const

inline

Linearizes the system by computing the Jacobians for the nodes and edges in the graph returns the set of batch statistics about the optimisation

Definition at line 272 of file sparse_optimizer.h.

Referenced by main().

272 { return _batchStatistics;}

g2o::SparseOptimizer::_batchStatistics

BatchStatisticsContainer _batchStatistics

global statistics of the optimizer, e.g., timing, num-non-zeros

Definition: sparse_optimizer.h:308

BatchStatisticsContainer& g2o::SparseOptimizer::batchStatistics ( )

inline

returns the set of batch statistics about the optimisation

Definition at line 276 of file sparse_optimizer.h.

276 { return _batchStatistics;}

g2o::SparseOptimizer::_batchStatistics

BatchStatisticsContainer _batchStatistics

global statistics of the optimizer, e.g., timing, num-non-zeros

Definition: sparse_optimizer.h:308

bool g2o::SparseOptimizer::buildIndexMapping ( SparseOptimizer::VertexContainer & vlist )

protected

builds the mapping of the active vertices to the (block) row / column in the Hessian

Definition at line 166 of file sparse_optimizer.cpp.

References _ivMap, g2o::OptimizableGraph::Vertex::fixed(), g2o::OptimizableGraph::Vertex::marginalized(), and g2o::OptimizableGraph::Vertex::setHessianIndex().

Referenced by initializeOptimization().

                                                                               {
     if (! vlist.size()){
       _ivMap.clear();
       return false;
     }
 
     _ivMap.resize(vlist.size());
     size_t i = 0;
     for (int k=0; k<2; k++)
       for (VertexContainer::iterator it=vlist.begin(); it!=vlist.end(); ++it){
       OptimizableGraph::Vertex* v = *it;
       if (! v->fixed()){
         if (static_cast<int>(v->marginalized()) == k){
           v->setHessianIndex(i);
           _ivMap[i]=v;
           i++;
         }
       }
       else {
         v->setHessianIndex(-1);
       }
     }
     _ivMap.resize(i);
     return true;
   }

void g2o::SparseOptimizer::clear ( )

virtual

clears the graph, and polishes some intermediate structures Note that this only removes nodes / edges. Parameters can be removed with clearParameters().

Reimplemented from g2o::HyperGraph.

Definition at line 498 of file sparse_optimizer.cpp.

References _activeEdges, _activeVertices, _ivMap, and g2o::HyperGraph::clear().

Referenced by main(), and g2o::Gm2dlIO::readGm2dl().

                               {
     _ivMap.clear();
     _activeVertices.clear();
     _activeEdges.clear();
     OptimizableGraph::clear();
   }

void g2o::SparseOptimizer::clearIndexMapping ( )

protected

Definition at line 192 of file sparse_optimizer.cpp.

References _ivMap.

Referenced by initializeOptimization(), and removeVertex().

                                          {
     for (size_t i=0; i<_ivMap.size(); ++i){
       _ivMap[i]->setHessianIndex(-1);
       _ivMap[i]=0;
     }
   }

void g2o::SparseOptimizer::computeActiveErrors ( )

computes the error vectors of all edges in the activeSet, and caches them

Definition at line 61 of file sparse_optimizer.cpp.

References _activeEdges, g2o::OptimizableGraph::_graphActions, actions, g2o::arrayHasNaN(), AT_COMPUTEACTIVERROR, g2o::OptimizableGraph::Edge::computeError(), g2o::OptimizableGraph::Edge::dimension(), and g2o::OptimizableGraph::Edge::errorData().

Referenced by computeInitialGuess(), g2o::computeSimpleStars(), g2o::Star::labelStarEdges(), main(), g2o::SparseOptimizerOnline::optimize(), optimize(), g2o::OptimizationAlgorithmLevenberg::solve(), g2o::OptimizationAlgorithmGaussNewton::solve(), and g2o::OptimizationAlgorithmDogleg::solve().

   {
     // call the callbacks in case there is something registered
     HyperGraphActionSet& actions = _graphActions[AT_COMPUTEACTIVERROR];
     if (actions.size() > 0) {
       for (HyperGraphActionSet::iterator it = actions.begin(); it != actions.end(); ++it)
         (*(*it))(this);
     }
 
 #   ifdef G2O_OPENMP
 #   pragma omp parallel for default (shared) if (_activeEdges.size() > 50)
 #   endif
     for (int k = 0; k < static_cast<int>(_activeEdges.size()); ++k) {
       OptimizableGraph::Edge* e = _activeEdges[k];
       e->computeError();
     }
 
 #  ifndef NDEBUG
     for (int k = 0; k < static_cast<int>(_activeEdges.size()); ++k) {
       OptimizableGraph::Edge* e = _activeEdges[k];
       bool hasNan = arrayHasNaN(e->errorData(), e->dimension());
       if (hasNan) {
         cerr << "computeActiveErrors(): found NaN in error for edge " << e << endl;
       }
     }
 #  endif
 
   }

bool g2o::SparseOptimizer::computeBatchStatistics ( ) const

inline

Definition at line 280 of file sparse_optimizer.h.

Referenced by setComputeBatchStatistics().

280 { return _computeBatchStatistics;}

g2o::SparseOptimizer::_computeBatchStatistics

bool _computeBatchStatistics

Definition: sparse_optimizer.h:309

void g2o::SparseOptimizer::computeInitialGuess ( )

virtual

Propagates an initial guess from the vertex specified as origin. It should be called after initializeOptimization(...), as it relies on the _activeVertices/_edges structures. It constructs a set of trees starting from the nodes in the graph which are fixed and eligible for preforming optimization. The trees are constructed by utlizing a cost-function specified.

Parameters

costFunction the cost function used maxDistance: the distance where to stop the search

Definition at line 308 of file sparse_optimizer.cpp.

Referenced by g2o::computeSimpleStars(), g2o::Star::labelStarEdges(), and main().

   {
     EstimatePropagator::PropagateCost costFunction(this);
     computeInitialGuess(costFunction);
   }

void g2o::SparseOptimizer::computeInitialGuess ( EstimatePropagatorCost & propagator )

virtual

Same as above but using a specific propagator

Definition at line 314 of file sparse_optimizer.cpp.

References _activeEdges, activeChi2(), computeActiveErrors(), g2o::HyperGraph::Vertex::edges(), g2o::OptimizableGraph::Vertex::fixed(), g2o::OptimizableGraph::Vertex::hessianIndex(), g2o::OptimizableGraph::Edge::initialEstimate(), g2o::OptimizableGraph::Edge::initialEstimatePossible(), g2o::EstimatePropagatorCost::name(), g2o::EstimatePropagator::propagate(), g2o::OptimizableGraph::Vertex::push(), verbose(), g2o::HyperGraph::Edge::vertex(), and g2o::HyperGraph::Edge::vertices().

   {
     OptimizableGraph::VertexSet emptySet;
     std::set<Vertex*> backupVertices;
     HyperGraph::VertexSet fixedVertices; // these are the root nodes where to start the initialization
     for (EdgeContainer::iterator it = _activeEdges.begin(); it != _activeEdges.end(); ++it) {
       OptimizableGraph::Edge* e = *it;
       for (size_t i = 0; i < e->vertices().size(); ++i) {
         OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(e->vertex(i));
         if (!v)
           continue;
         if (v->fixed())
           fixedVertices.insert(v);
         else { // check for having a prior which is able to fully initialize a vertex
           for (EdgeSet::const_iterator vedgeIt = v->edges().begin(); vedgeIt != v->edges().end(); ++vedgeIt) {
             OptimizableGraph::Edge* vedge = static_cast<OptimizableGraph::Edge*>(*vedgeIt);
             if (vedge->vertices().size() == 1 && vedge->initialEstimatePossible(emptySet, v) > 0.) {
               //cerr << "Initialize with prior for " << v->id() << endl;
               vedge->initialEstimate(emptySet, v);
               fixedVertices.insert(v);
             }
           }
         }
         if (v->hessianIndex() == -1) {
           std::set<Vertex*>::const_iterator foundIt = backupVertices.find(v);
           if (foundIt == backupVertices.end()) {
             v->push();
             backupVertices.insert(v);
           }
         }
       }
     }
 
     EstimatePropagator estimatePropagator(this);
     estimatePropagator.propagate(fixedVertices, costFunction);
 
     // restoring the vertices that should not be initialized
     for (std::set<Vertex*>::iterator it = backupVertices.begin(); it != backupVertices.end(); ++it) {
       Vertex* v = *it;
       v->pop();
     }
     if (verbose()) {
       computeActiveErrors();
       cerr << "iteration= -1\t chi2= " << activeChi2()
           << "\t time= 0.0"
           << "\t cumTime= 0.0"
           << "\t (using initial guess from " << costFunction.name() << ")" << endl;
     }
   }

bool g2o::SparseOptimizer::computeMarginals	(	SparseBlockMatrix< MatrixXD > &	spinv,
		const std::vector< std::pair< int, int > > &	blockIndices
	)

computes the blocks of the inverse of the specified pattern. the pattern is given via pairs <row, col> of the blocks in the hessian

Parameters

blockIndices	the pattern
spinv	the sparse block matrix with the result

Returns: false if the operation is not supported by the solver

Definition at line 579 of file sparse_optimizer.cpp.

References _algorithm, and g2o::OptimizationAlgorithm::computeMarginals().

Referenced by main(), and testMarginals().

                                                                                                                              {
     return _algorithm->computeMarginals(spinv, blockIndices);
   }

bool g2o::SparseOptimizer::computeMarginals	(	SparseBlockMatrix< MatrixXD > &	spinv,
		const Vertex *	vertex
	)

inline

computes the inverse of the specified vertex.

Parameters

vertex	the vertex whose state is to be marginalised
spinv	the sparse block matrix with the result

Returns: false if the operation is not supported by the solver

Definition at line 139 of file sparse_optimizer.h.

                                                                                     {
       if (vertex->hessianIndex() < 0) {
           return false;
       }
       std::vector<std::pair<int, int> > index;
       index.push_back(std::pair<int, int>(vertex->hessianIndex(), vertex->hessianIndex()));
       return computeMarginals(spinv, index);
     }

bool g2o::SparseOptimizer::computeMarginals	(	SparseBlockMatrix< MatrixXD > &	spinv,
		const VertexContainer &	vertices
	)

inline

computes the inverse of the set specified vertices, assembled into a single covariance matrix.

Parameters

vertex	the pattern
spinv	the sparse block matrix with the result

Returns: false if the operation is not supported by the solver

Definition at line 154 of file sparse_optimizer.h.

                                                                                                {
       std::vector<std::pair<int, int> > indices;
       for (VertexContainer::const_iterator it = vertices.begin(); it != vertices.end(); ++it) {
         indices.push_back(std::pair<int, int>((*it)->hessianIndex(),(*it)->hessianIndex()));
       }
       return computeMarginals(spinv, indices);
     }

void g2o::SparseOptimizer::discardTop ( SparseOptimizer::VertexContainer & vlist )

ignore the latest stored element on the stack, remove it from the stack but do not restore the estimate

Definition at line 559 of file sparse_optimizer.cpp.

Referenced by g2o::OptimizationAlgorithmLevenberg::solve(), and g2o::OptimizationAlgorithmDogleg::solve().

   {
     for (VertexContainer::iterator it = vlist.begin(); it != vlist.end(); ++it)
       (*it)->discardTop();
   }

void g2o::SparseOptimizer::discardTop ( )

virtual

same as above, but for the active vertices

Reimplemented from g2o::OptimizableGraph.

Definition at line 619 of file sparse_optimizer.cpp.

References _activeVertices.

   {
     discardTop(_activeVertices);
   }

SparseOptimizer::EdgeContainer::const_iterator g2o::SparseOptimizer::findActiveEdge ( const OptimizableGraph::Edge * e ) const

search for an edge in _activeEdges and return the iterator pointing to it getActiveEdges().end() if not found

Definition at line 515 of file sparse_optimizer.cpp.

References _activeEdges.

Referenced by g2o::activeVertexChi(), g2o::EstimatePropagatorCost::operator()(), and g2o::EstimatePropagatorCostOdometry::operator()().

   {
     EdgeContainer::const_iterator lower = lower_bound(_activeEdges.begin(), _activeEdges.end(), e, EdgeIDCompare());
     if (lower == _activeEdges.end())
       return _activeEdges.end();
     if ((*lower) == e)
       return lower;
     return _activeEdges.end();
   }

SparseOptimizer::VertexContainer::const_iterator g2o::SparseOptimizer::findActiveVertex ( const OptimizableGraph::Vertex * v ) const

search for an edge in _activeVertices and return the iterator pointing to it getActiveVertices().end() if not found

Definition at line 505 of file sparse_optimizer.cpp.

References _activeVertices.

   {
     VertexContainer::const_iterator lower = lower_bound(_activeVertices.begin(), _activeVertices.end(), v, VertexIDCompare());
     if (lower == _activeVertices.end())
       return _activeVertices.end();
     if ((*lower) == v)
       return lower;
     return _activeVertices.end();
   }

OptimizableGraph::Vertex * g2o::SparseOptimizer::findGauge ( )

virtual

finds a gauge in the graph to remove the undefined dof.

Definition at line 116 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::Vertex::dimension(), and g2o::HyperGraph::vertices().

Referenced by main().

                                                     {
     if (vertices().empty())
       return 0;
 
     int maxDim=0;
     for (HyperGraph::VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it){
       OptimizableGraph::Vertex* v=static_cast<OptimizableGraph::Vertex*>(it->second); 
       maxDim=std::max(maxDim,v->dimension());
     }
     
     OptimizableGraph::Vertex* rut=0;
     for (HyperGraph::VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it){
       OptimizableGraph::Vertex* v=static_cast<OptimizableGraph::Vertex*>(it->second);
       if (v->dimension()==maxDim){
         rut=v;
         break;
       }
     }
     return rut;
   }

bool* g2o::SparseOptimizer::forceStopFlag ( ) const

inline

Definition at line 186 of file sparse_optimizer.h.

Referenced by g2o::SparseOptimizerTerminateAction::setOptimizerStopFlag().

186 { return _forceStopFlag;};

g2o::SparseOptimizer::_forceStopFlag

bool * _forceStopFlag

Definition: sparse_optimizer.h:291

bool g2o::SparseOptimizer::gaugeFreedom ( )

Definition at line 137 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::Vertex::dimension(), g2o::OptimizableGraph::Edge::dimension(), g2o::HyperGraph::Vertex::edges(), g2o::OptimizableGraph::Vertex::fixed(), g2o::HyperGraph::Edge::vertices(), and g2o::HyperGraph::vertices().

Referenced by main().

   {
     if (vertices().empty())
       return false;
 
     int maxDim=0;
     for (HyperGraph::VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it){
       OptimizableGraph::Vertex* v=static_cast<OptimizableGraph::Vertex*>(it->second); 
       maxDim = std::max(maxDim,v->dimension());
     }
 
     for (HyperGraph::VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it){
       OptimizableGraph::Vertex* v=static_cast<OptimizableGraph::Vertex*>(it->second);
       if (v->dimension() == maxDim) {
         // test for fixed vertex
         if (v->fixed()) {
           return false;
         }
         // test for full dimension prior
         for (HyperGraph::EdgeSet::const_iterator eit = v->edges().begin(); eit != v->edges().end(); ++eit) {
           OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*eit);
           if (e->vertices().size() == 1 && e->dimension() == maxDim)
             return false;
         }
       }
     }
     return true;
   }

const VertexContainer& g2o::SparseOptimizer::indexMapping ( ) const

inline

the index mapping of the vertices

Definition at line 192 of file sparse_optimizer.h.

Referenced by g2o::BlockSolver< Traits >::buildStructure(), g2o::BlockSolver< Traits >::buildSystem(), g2o::OptimizationAlgorithmLevenberg::computeLambdaInit(), g2o::Star::labelStarEdges(), g2o::SparseOptimizerOnline::optimize(), and g2o::SolverSLAM2DLinear::solveOrientation().

192 {return _ivMap;}

g2o::SparseOptimizer::_ivMap

VertexContainer _ivMap

Definition: sparse_optimizer.h:294

bool g2o::SparseOptimizer::initializeOptimization ( HyperGraph::EdgeSet & eset )

virtual

Initializes the structures for optimizing a portion of the graph specified by a subset of edges. Before calling it be sure to invoke marginalized() and fixed() to the vertices you want to include in the schur complement or to set as fixed during the optimization.

Parameters

eset	the subgraph to be optimized.

Returns: false if somethings goes wrong

Definition at line 272 of file sparse_optimizer.cpp.

References _activeEdges, _activeVertices, g2o::OptimizableGraph::_jacobianWorkspace, g2o::JacobianWorkspace::allocate(), buildIndexMapping(), clearIndexMapping(), g2o::HyperGraph::Edge::numUndefinedVertices(), g2o::OptimizableGraph::postIteration(), g2o::OptimizableGraph::preIteration(), sortVectorContainers(), and g2o::HyperGraph::Edge::vertices().

Referenced by g2o::computeSimpleStars(), initializeOptimization(), g2o::Star::labelStarEdges(), main(), and g2o::G2oSlamInterface::solve().

                                                                      {
     preIteration(-1);
     bool workspaceAllocated = _jacobianWorkspace.allocate(); (void) workspaceAllocated;
     assert(workspaceAllocated && "Error while allocating memory for the Jacobians");
     clearIndexMapping();
     _activeVertices.clear();
     _activeEdges.clear();
     _activeEdges.reserve(eset.size());
     set<Vertex*> auxVertexSet; // temporary structure to avoid duplicates
     for (HyperGraph::EdgeSet::iterator it=eset.begin(); it!=eset.end(); ++it){
       OptimizableGraph::Edge* e=(OptimizableGraph::Edge*)(*it);
       if (e->numUndefinedVertices())
         continue;
       for (vector<HyperGraph::Vertex*>::const_iterator vit = e->vertices().begin(); vit != e->vertices().end(); ++vit) {
         auxVertexSet.insert(static_cast<OptimizableGraph::Vertex*>(*vit));
       }
       _activeEdges.push_back(reinterpret_cast<OptimizableGraph::Edge*>(*it));
     }
 
     _activeVertices.reserve(auxVertexSet.size());
     for (set<Vertex*>::iterator it = auxVertexSet.begin(); it != auxVertexSet.end(); ++it)
       _activeVertices.push_back(*it);
 
     sortVectorContainers();
     bool indexMappingStatus = buildIndexMapping(_activeVertices);
     postIteration(-1);
     return indexMappingStatus;
   }

bool g2o::SparseOptimizer::initializeOptimization	(	HyperGraph::VertexSet &	vset,
		int	level = `0`
	)

virtual

Initializes the structures for optimizing a portion of the graph specified by a subset of vertices. Before calling it be sure to invoke marginalized() and fixed() to the vertices you want to include in the schur complement or to set as fixed during the optimization.

Parameters

vset	the subgraph to be optimized.
level	is the level (in multilevel optimization)

Returns: false if somethings goes wrong

Definition at line 206 of file sparse_optimizer.cpp.

References __PRETTY_FUNCTION__, _activeEdges, _activeVertices, g2o::OptimizableGraph::_jacobianWorkspace, g2o::JacobianWorkspace::allocate(), g2o::OptimizableGraph::Edge::allVerticesFixed(), g2o::arrayHasNaN(), buildIndexMapping(), clearIndexMapping(), g2o::HyperGraph::Vertex::edges(), g2o::HyperGraph::edges(), g2o::OptimizableGraph::Vertex::estimateDimension(), g2o::OptimizableGraph::Vertex::getEstimateData(), g2o::HyperGraph::Vertex::id(), g2o::OptimizableGraph::postIteration(), g2o::OptimizableGraph::preIteration(), sortVectorContainers(), and g2o::HyperGraph::Edge::vertices().

                                                                                   {
     if (edges().size() == 0) {
       cerr << __PRETTY_FUNCTION__ << ": Attempt to initialize an empty graph" << endl;
       return false;
     }
     preIteration(-1);
     bool workspaceAllocated = _jacobianWorkspace.allocate(); (void) workspaceAllocated;
     assert(workspaceAllocated && "Error while allocating memory for the Jacobians");
     clearIndexMapping();
     _activeVertices.clear();
     _activeVertices.reserve(vset.size());
     _activeEdges.clear();
     set<Edge*> auxEdgeSet; // temporary structure to avoid duplicates
     for (HyperGraph::VertexSet::iterator it=vset.begin(); it!=vset.end(); ++it){
       OptimizableGraph::Vertex* v= (OptimizableGraph::Vertex*) *it;
       const OptimizableGraph::EdgeSet& vEdges=v->edges();
       // count if there are edges in that level. If not remove from the pool
       int levelEdges=0;
       for (OptimizableGraph::EdgeSet::const_iterator it=vEdges.begin(); it!=vEdges.end(); ++it){
         OptimizableGraph::Edge* e=reinterpret_cast<OptimizableGraph::Edge*>(*it);
         if (level < 0 || e->level() == level) {
 
           bool allVerticesOK = true;
           for (vector<HyperGraph::Vertex*>::const_iterator vit = e->vertices().begin(); vit != e->vertices().end(); ++vit) {
             if (vset.find(*vit) == vset.end()) {
               allVerticesOK = false;
               break;
             }
           }
           if (allVerticesOK && !e->allVerticesFixed()) {
             auxEdgeSet.insert(e);
             levelEdges++;
           }
 
         }
       }
       if (levelEdges){
         _activeVertices.push_back(v);
 
         // test for NANs in the current estimate if we are debugging
 #      ifndef NDEBUG
         int estimateDim = v->estimateDimension();
         if (estimateDim > 0) {
           VectorXD estimateData(estimateDim);
           if (v->getEstimateData(estimateData.data()) == true) {
             int k;
             bool hasNan = arrayHasNaN(estimateData.data(), estimateDim, &k);
             if (hasNan)
               cerr << __PRETTY_FUNCTION__ << ": Vertex " << v->id() << " contains a nan entry at index " << k << endl;
           }
         }
 #      endif
 
       }
     }
 
     _activeEdges.reserve(auxEdgeSet.size());
     for (set<Edge*>::iterator it = auxEdgeSet.begin(); it != auxEdgeSet.end(); ++it)
       _activeEdges.push_back(*it);
 
     sortVectorContainers();
     bool indexMappingStatus = buildIndexMapping(_activeVertices);
     postIteration(-1);
     return indexMappingStatus;
   }

bool g2o::SparseOptimizer::initializeOptimization ( int level = 0 )

virtual

Initializes the structures for optimizing the whole graph. Before calling it be sure to invoke marginalized() and fixed() to the vertices you want to include in the schur complement or to set as fixed during the optimization.

Parameters

level is the level (in multilevel optimization)

Returns: false if somethings goes wrong

Definition at line 199 of file sparse_optimizer.cpp.

References initializeOptimization(), and g2o::HyperGraph::vertices().

                                                        {
     HyperGraph::VertexSet vset;
     for (VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it)
       vset.insert(it->second);
     return initializeOptimization(vset,level);
   }

int g2o::SparseOptimizer::optimize	(	int	iterations,
		bool	online = `false`
	)

virtual

starts one optimization run given the current configuration of the graph, and the current settings stored in the class instance. It can be called only after initializeOptimization

Reimplemented from g2o::OptimizableGraph.

Reimplemented in g2o::SparseOptimizerOnline, and g2o::SparseOptimizerIncremental.

Definition at line 364 of file sparse_optimizer.cpp.

References __PRETTY_FUNCTION__, _activeEdges, _activeVertices, _algorithm, _batchStatistics, _computeBatchStatistics, _ivMap, activeRobustChi2(), g2o::arrayHasNaN(), computeActiveErrors(), g2o::OptimizableGraph::Vertex::dimension(), g2o::get_monotonic_time(), g2o::HyperGraph::Vertex::id(), g2o::OptimizationAlgorithm::init(), g2o::G2OBatchStatistics::iteration, g2o::G2OBatchStatistics::numEdges, g2o::G2OBatchStatistics::numVertices, OK, g2o::OptimizableGraph::Vertex::oplus(), g2o::OptimizableGraph::postIteration(), g2o::OptimizableGraph::preIteration(), g2o::OptimizationAlgorithm::printVerbose(), g2o::G2OBatchStatistics::setGlobalStats(), g2o::OptimizationAlgorithm::solve(), terminate(), and verbose().

Referenced by g2o::computeSimpleStars(), g2o::Star::labelStarEdges(), and main().

   {
     if (_ivMap.size() == 0) {
       cerr << __PRETTY_FUNCTION__ << ": 0 vertices to optimize, maybe forgot to call initializeOptimization()" << endl;
       return -1;
     }
 
     int cjIterations=0;
     double cumTime=0;
     bool ok=true;
 
     ok = _algorithm->init(online);
     if (! ok) {
       cerr << __PRETTY_FUNCTION__ << " Error while initializing" << endl;
       return -1;
     }
 
     _batchStatistics.clear();
     if (_computeBatchStatistics)
       _batchStatistics.resize(iterations);
     
     OptimizationAlgorithm::SolverResult result = OptimizationAlgorithm::OK;
     for (int i=0; i<iterations && ! terminate() && ok; i++){
       preIteration(i);
 
       if (_computeBatchStatistics) {
         G2OBatchStatistics& cstat = _batchStatistics[i];
         G2OBatchStatistics::setGlobalStats(&cstat);
         cstat.iteration = i;
         cstat.numEdges =  _activeEdges.size();
         cstat.numVertices = _activeVertices.size();
       }
       
       double ts = get_monotonic_time();
       result = _algorithm->solve(i, online);
       ok = ( result == OptimizationAlgorithm::OK );
 
       bool errorComputed = false;
       if (_computeBatchStatistics) {
         computeActiveErrors();
         errorComputed = true;
         _batchStatistics[i].chi2 = activeRobustChi2();
         _batchStatistics[i].timeIteration = get_monotonic_time()-ts;
       }
 
       if (verbose()){
         double dts = get_monotonic_time()-ts;
         cumTime += dts;
         if (! errorComputed)
           computeActiveErrors();
         cerr << "iteration= " << i
           << "\t chi2= " << FIXED(activeRobustChi2())
           << "\t time= " << dts
           << "\t cumTime= " << cumTime
           << "\t edges= " << _activeEdges.size();
         _algorithm->printVerbose(cerr);
         cerr << endl;
       }
       ++cjIterations; 
       postIteration(i);
     }
     if (result == OptimizationAlgorithm::Fail) {
       return 0;
     }
     return cjIterations;
   }

void g2o::SparseOptimizer::pop ( SparseOptimizer::VertexContainer & vlist )

pop (restore) the estimate a subset of the variables from the stack

Definition at line 531 of file sparse_optimizer.cpp.

Referenced by g2o::computeSimpleStars(), g2o::OptimizationAlgorithmLevenberg::solve(), and g2o::OptimizationAlgorithmDogleg::solve().

   {
     for (VertexContainer::iterator it = vlist.begin(); it != vlist.end(); ++it)
       (*it)->pop();
   }

void g2o::SparseOptimizer::pop ( HyperGraph::VertexSet & vlist )

virtual

pop (restore) the estimate a subset of the variables from the stack

Reimplemented from g2o::OptimizableGraph.

Definition at line 548 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::Vertex::pop().

   {
     for (HyperGraph::VertexSet::iterator it = vlist.begin(); it != vlist.end(); ++it){
       OptimizableGraph::Vertex* v = dynamic_cast<OptimizableGraph::Vertex*> (*it);
       if (v)
         v->pop();
       else 
         cerr << __FUNCTION__ << ": FATAL POP SET" << endl;
     }
   }

void g2o::SparseOptimizer::pop ( )

virtual

pop (restore) the estimate of the active vertices from the stack

Reimplemented from g2o::OptimizableGraph.

Definition at line 614 of file sparse_optimizer.cpp.

References _activeVertices.

   {
     pop(_activeVertices);
   }

void g2o::SparseOptimizer::push ( SparseOptimizer::VertexContainer & vlist )

push the estimate of a subset of the variables onto a stack

Definition at line 525 of file sparse_optimizer.cpp.

Referenced by g2o::computeSimpleStars(), g2o::OptimizationAlgorithmLevenberg::solve(), and g2o::OptimizationAlgorithmDogleg::solve().

   {
     for (VertexContainer::iterator it = vlist.begin(); it != vlist.end(); ++it)
       (*it)->push();
   }

void g2o::SparseOptimizer::push ( HyperGraph::VertexSet & vlist )

virtual

push the estimate of a subset of the variables onto a stack

Reimplemented from g2o::OptimizableGraph.

Definition at line 537 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::Vertex::push().

   {
     for (HyperGraph::VertexSet::iterator it = vlist.begin(); it != vlist.end(); ++it) {
       OptimizableGraph::Vertex* v = dynamic_cast<OptimizableGraph::Vertex*>(*it);
       if (v)
         v->push();
       else 
         cerr << __FUNCTION__ << ": FATAL PUSH SET" << endl;
     }
   }

void g2o::SparseOptimizer::push ( )

virtual

push all the active vertices onto a stack

Reimplemented from g2o::OptimizableGraph.

Definition at line 609 of file sparse_optimizer.cpp.

References _activeVertices.

   {
     push(_activeVertices);
   }

bool g2o::SparseOptimizer::removeComputeErrorAction ( HyperGraphAction * action )

remove an action that should no longer be execured before computing the error vectors

Definition at line 604 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::_graphActions, and AT_COMPUTEACTIVERROR.

   {
     return _graphActions[AT_COMPUTEACTIVERROR].erase(action) > 0;
   }

bool g2o::SparseOptimizer::removeVertex	(	HyperGraph::Vertex *	v,
		bool	detach = `false`
	)

virtual

Remove a vertex. If the vertex is contained in the currently active set of vertices, then the internal temporary structures are cleaned, e.g., the index mapping is erased. In case you need the index mapping for manipulating the graph, you have to store it in your own copy.

Reimplemented from g2o::HyperGraph.

Definition at line 588 of file sparse_optimizer.cpp.

References _ivMap, clearIndexMapping(), g2o::OptimizableGraph::Vertex::hessianIndex(), and g2o::HyperGraph::removeVertex().

   {
     OptimizableGraph::Vertex* vv = static_cast<OptimizableGraph::Vertex*>(v);
     if (vv->hessianIndex() >= 0) {
       clearIndexMapping();
       _ivMap.clear();
     }
     return HyperGraph::removeVertex(v, detach);
   }

void g2o::SparseOptimizer::setAlgorithm ( OptimizationAlgorithm * algorithm )

Definition at line 570 of file sparse_optimizer.cpp.

References _algorithm, algorithm(), and g2o::OptimizationAlgorithm::setOptimizer().

Referenced by g2o::allocateSolverForSclam(), g2o::SparseOptimizerOnline::initSolver(), and main().

   {
     if (_algorithm) // reset the optimizer for the formerly used solver
       _algorithm->setOptimizer(0);
     _algorithm = algorithm;
     if (_algorithm)
       _algorithm->setOptimizer(this);
   }

void g2o::SparseOptimizer::setComputeBatchStatistics ( bool computeBatchStatistics )

Definition at line 446 of file sparse_optimizer.cpp.

References _batchStatistics, _computeBatchStatistics, computeBatchStatistics(), and g2o::G2OBatchStatistics::setGlobalStats().

Referenced by main().

   {
     if ((_computeBatchStatistics == true) && (computeBatchStatistics == false)) {
       G2OBatchStatistics::setGlobalStats(0);
       _batchStatistics.clear();
     }
     _computeBatchStatistics = computeBatchStatistics;
   }

void g2o::SparseOptimizer::setForceStopFlag ( bool * flag )

sets a variable checked at every iteration to force a user stop. The iteration exits when the variable is true;

Definition at line 583 of file sparse_optimizer.cpp.

References _forceStopFlag.

Referenced by main().

   {
     _forceStopFlag=flag;
   }

void g2o::SparseOptimizer::setToOrigin ( )

virtual

sets all vertices to their origin.

Definition at line 301 of file sparse_optimizer.cpp.

References g2o::OptimizableGraph::Vertex::setToOrigin(), and g2o::HyperGraph::vertices().

                                    {
     for (VertexIDMap::iterator it=vertices().begin(); it!=vertices().end(); ++it) {
       OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(it->second);
       v->setToOrigin();
     }
   }

void g2o::SparseOptimizer::setVerbose ( bool verbose )

Definition at line 565 of file sparse_optimizer.cpp.

References _verbose, and verbose().

Referenced by main().

   {
     _verbose = verbose;
   }

OptimizationAlgorithm* g2o::SparseOptimizer::solver ( )

inline

Definition at line 219 of file sparse_optimizer.h.

References g2o::OptimizableGraph::discardTop(), and G2O_ATTRIBUTE_DEPRECATED.

Referenced by g2o::computeSimpleStars(), g2o::SparseOptimizerOnline::initSolver(), g2o::Star::labelStarEdges(), main(), and g2o::SparseOptimizerOnline::optimize().

219 { return _algorithm;}

g2o::SparseOptimizer::_algorithm

OptimizationAlgorithm * _algorithm

Definition: sparse_optimizer.h:300

void g2o::SparseOptimizer::sortVectorContainers ( )

protected

Definition at line 491 of file sparse_optimizer.cpp.

References _activeEdges, and _activeVertices.

Referenced by initializeOptimization().

   {
     // sort vector structures to get deterministic ordering based on IDs
     sort(_activeVertices.begin(), _activeVertices.end(), VertexIDCompare());
     sort(_activeEdges.begin(), _activeEdges.end(), EdgeIDCompare());
   }

bool g2o::SparseOptimizer::terminate ( )

inline

if external stop flag is given, return its state. False otherwise

Definition at line 189 of file sparse_optimizer.h.

Referenced by optimize(), and g2o::OptimizationAlgorithmLevenberg::solve().

189 {return _forceStopFlag ? (*_forceStopFlag) : false; }

g2o::SparseOptimizer::_forceStopFlag

bool * _forceStopFlag

Definition: sparse_optimizer.h:291

bool g2o::SparseOptimizer::updateInitialization	(	HyperGraph::VertexSet &	vset,
		HyperGraph::EdgeSet &	eset
	)

virtual

HACK updating the internal structures for online processing

Reimplemented in g2o::SparseOptimizerOnline, and g2o::SparseOptimizerIncremental.

Definition at line 455 of file sparse_optimizer.cpp.

References _activeEdges, _activeVertices, _algorithm, _ivMap, g2o::OptimizableGraph::Edge::allVerticesFixed(), g2o::OptimizableGraph::Vertex::fixed(), g2o::OptimizableGraph::Vertex::marginalized(), g2o::OptimizableGraph::Vertex::setHessianIndex(), and g2o::OptimizationAlgorithm::updateStructure().

Referenced by main(), and g2o::SparseOptimizerOnline::updateInitialization().

   {
     std::vector<HyperGraph::Vertex*> newVertices;
     newVertices.reserve(vset.size());
     _activeVertices.reserve(_activeVertices.size() + vset.size());
     _activeEdges.reserve(_activeEdges.size() + eset.size());
     for (HyperGraph::EdgeSet::iterator it = eset.begin(); it != eset.end(); ++it) {
       OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
       if (!e->allVerticesFixed()) _activeEdges.push_back(e);
     }
     
     // update the index mapping
     size_t next = _ivMap.size();
     for (HyperGraph::VertexSet::iterator it = vset.begin(); it != vset.end(); ++it) {
       OptimizableGraph::Vertex* v=static_cast<OptimizableGraph::Vertex*>(*it);
       if (! v->fixed()){
         if (! v->marginalized()){
           v->setHessianIndex(next);
           _ivMap.push_back(v);
           newVertices.push_back(v);
           _activeVertices.push_back(v);
           next++;
         } 
         else // not supported right now
           abort();
       }
       else {
         v->setHessianIndex(-1);
       }
     }
 
     //if (newVertices.size() != vset.size())
     //cerr << __PRETTY_FUNCTION__ << ": something went wrong " << PVAR(vset.size()) << " " << PVAR(newVertices.size()) << endl;
     return _algorithm->updateStructure(newVertices, eset);
   }