#include <graph_optimizer_sparse_incremental.h>

Inheritance diagram for g2o::SparseOptimizerIncremental:

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Collaboration diagram for g2o::SparseOptimizerIncremental:

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Public Member Functions
	SparseOptimizerIncremental ()

	~SparseOptimizerIncremental ()

int	optimize (int iterations, bool online=false)

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

virtual bool	initSolver (int dimension, int batchEveryN)

Public Member Functions inherited from g2o::SparseOptimizerOnline
	SparseOptimizerOnline (bool pcg=false)

virtual	~SparseOptimizerOnline ()

int	optimize (int iterations, bool online=false)

void	update (double *update)

virtual void	gnuplotVisualization ()

Public Member Functions inherited from g2o::SparseOptimizer
	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 void	computeInitialGuess ()

virtual void	computeInitialGuess (EstimatePropagatorCost &propagator)

virtual void	setToOrigin ()

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
bool	computeCholeskyUpdate ()

void	convertTripletUpdateToSparse ()

Protected Member Functions inherited from g2o::SparseOptimizer
void	sortVectorContainers ()

bool	buildIndexMapping (SparseOptimizer::VertexContainer &vlist)

void	clearIndexMapping ()

Protected Attributes
SparseBlockMatrix< Eigen::MatrixXd >	_updateMat

cholmod_common	_cholmodCommon

CholmodExt *	_cholmodSparse

cholmod_factor *	_cholmodFactor

cholmod_triplet *	_permutedUpdate

cholmod_factor *	_L

LinearSolverCholmodOnlineInterface *	_solverInterface

HyperGraph::VertexSet	_touchedVertices

Eigen::VectorXi	_perm

Eigen::VectorXi	_cmember

Eigen::VectorXi	_tripletWorkspace

CholmodExt *	_permutedUpdateAsSparse

Protected Attributes inherited from g2o::SparseOptimizerOnline
FILE *	_gnuplot

bool	_usePcg

Solver *	_underlyingSolver

Protected Attributes inherited from g2o::SparseOptimizer
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

Additional Inherited Members
Public Types inherited from g2o::SparseOptimizer
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

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

Public Attributes inherited from g2o::SparseOptimizerOnline
int	slamDimension

HyperGraph::EdgeSet *	newEdges

bool	batchStep

bool	vizWithGnuplot

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 30 of file graph_optimizer_sparse_incremental.h.

Constructor & Destructor Documentation

g2o::SparseOptimizerIncremental::SparseOptimizerIncremental ( )

Definition at line 57 of file graph_optimizer_sparse_incremental.cpp.

   {
     _cholmodSparse = new CholmodExt();
     _cholmodFactor = 0;
     cholmod_start(&_cholmodCommon);
 
     // setup ordering strategy to not permute the matrix
     _cholmodCommon.nmethods = 1 ;
     _cholmodCommon.method[0].ordering = CHOLMOD_NATURAL;
     _cholmodCommon.postorder = 0;
     _cholmodCommon.supernodal = CHOLMOD_SIMPLICIAL;
 
     _permutedUpdate = cholmod_allocate_triplet(1000, 1000, 1024, 0, CHOLMOD_REAL, &_cholmodCommon);
     _L = 0;
     _cholmodFactor = 0;
     _solverInterface = 0;
 
     _permutedUpdateAsSparse = new CholmodExt;
   }

g2o::SparseOptimizerIncremental::~SparseOptimizerIncremental ( )

Definition at line 77 of file graph_optimizer_sparse_incremental.cpp.

   {
     delete _permutedUpdateAsSparse;
     _updateMat.clear(true);
     delete _cholmodSparse;
     if (_cholmodFactor) {
       cholmod_free_factor(&_cholmodFactor, &_cholmodCommon);
       _cholmodFactor = 0;
     }
     cholmod_free_triplet(&_permutedUpdate, &_cholmodCommon);
     cholmod_finish(&_cholmodCommon);
   }

Member Function Documentation

bool g2o::SparseOptimizerIncremental::computeCholeskyUpdate ( )

protected

Definition at line 402 of file graph_optimizer_sparse_incremental.cpp.

References g2o::SparseBlockMatrix< MatrixType >::cols(), g2o::SparseBlockMatrix< MatrixType >::fillCCS(), g2o::SparseBlockMatrix< MatrixType >::nonZeros(), and g2o::SparseBlockMatrix< MatrixType >::rows().

   {
     if (_cholmodFactor) {
       cholmod_free_factor(&_cholmodFactor, &_cholmodCommon);
       _cholmodFactor = 0;
     }
 
     const SparseBlockMatrix<MatrixXd>& A = _updateMat;
     size_t m = A.rows();
     size_t n = A.cols();
 
     if (_cholmodSparse->columnsAllocated < n) {
       //std::cerr << __PRETTY_FUNCTION__ << ": reallocating columns" << std::endl;
       _cholmodSparse->columnsAllocated = _cholmodSparse->columnsAllocated == 0 ? n : 2 * n; // pre-allocate more space if re-allocating
       delete[] (int*)_cholmodSparse->p;
       _cholmodSparse->p = new int[_cholmodSparse->columnsAllocated+1];
     }
     size_t nzmax = A.nonZeros();
     if (_cholmodSparse->nzmax < nzmax) {
       //std::cerr << __PRETTY_FUNCTION__ << ": reallocating row + values" << std::endl;
       _cholmodSparse->nzmax = _cholmodSparse->nzmax == 0 ? nzmax : 2 * nzmax; // pre-allocate more space if re-allocating
       delete[] (double*)_cholmodSparse->x;
       delete[] (int*)_cholmodSparse->i;
       _cholmodSparse->i = new int[_cholmodSparse->nzmax];
       _cholmodSparse->x = new double[_cholmodSparse->nzmax];
     }
     _cholmodSparse->ncol = n;
     _cholmodSparse->nrow = m;
 
     A.fillCCS((int*)_cholmodSparse->p, (int*)_cholmodSparse->i, (double*)_cholmodSparse->x, true);
     //writeCCSMatrix("updatesparse.txt", _cholmodSparse->nrow, _cholmodSparse->ncol, (int*)_cholmodSparse->p, (int*)_cholmodSparse->i, (double*)_cholmodSparse->x, true);
 
     _cholmodFactor = cholmod_analyze(_cholmodSparse, &_cholmodCommon);
     cholmod_factorize(_cholmodSparse, _cholmodFactor, &_cholmodCommon);
 
 #if 0
     int* p = (int*)_cholmodFactor->Perm;
     for (int i = 0; i < (int)n; ++i)
       if (i != p[i])
         cerr << "wrong permutation" << i << " -> " << p[i] << endl;
 #endif
 
     if (_cholmodCommon.status == CHOLMOD_NOT_POSDEF) {
       //std::cerr << "Cholesky failure, writing debug.txt (Hessian loadable by Octave)" << std::endl;
       //writeCCSMatrix("debug.txt", _cholmodSparse->nrow, _cholmodSparse->ncol, (int*)_cholmodSparse->p, (int*)_cholmodSparse->i, (double*)_cholmodSparse->x, true);
       return false;
     }
 
     // change to the specific format we need to have a pretty normal L
     int change_status = cholmod_change_factor(CHOLMOD_REAL, 1, 0, 1, 1, _cholmodFactor, &_cholmodCommon);
     if (! change_status) {
       return false;
     }
 
     return true;
   }

void g2o::SparseOptimizerIncremental::convertTripletUpdateToSparse ( )

protected

Definition at line 510 of file graph_optimizer_sparse_incremental.cpp.

References g2o::BlockSolver< Traits >::resize().

   {
     // re-allocate the memory
     if (_tripletWorkspace.size() < (int)_permutedUpdate->ncol) {
       _tripletWorkspace.resize(_permutedUpdate->ncol * 2);
     }
 
     // reallocate num-zeros
     if (_permutedUpdateAsSparse->nzmax < _permutedUpdate->nzmax) {
       _permutedUpdateAsSparse->nzmax = _permutedUpdate->nzmax;
       delete[] (int*)_permutedUpdateAsSparse->i;
       delete[] (double*)_permutedUpdateAsSparse->x;
       _permutedUpdateAsSparse->x = new double[_permutedUpdateAsSparse->nzmax];
       _permutedUpdateAsSparse->i = new int[_permutedUpdateAsSparse->nzmax];
     }
 
     if (_permutedUpdateAsSparse->columnsAllocated < _permutedUpdate->ncol) {
       _permutedUpdateAsSparse->columnsAllocated = 2*_permutedUpdate->ncol;
       delete[] (int*) _permutedUpdateAsSparse->p;
       _permutedUpdateAsSparse->p = new int[_permutedUpdateAsSparse->columnsAllocated + 1];
     }
 
     _permutedUpdateAsSparse->ncol = _permutedUpdate->ncol;
     _permutedUpdateAsSparse->nrow = _permutedUpdate->nrow;
 
     int* w = _tripletWorkspace.data();
     memset(w, 0, sizeof(int) * _permutedUpdate->ncol);
 
     int* Ti = (int*) _permutedUpdate->i;
     int* Tj = (int*) _permutedUpdate->j;
     double* Tx = (double*) _permutedUpdate->x;
 
     int* Cp = (int*) _permutedUpdateAsSparse->p;
     int* Ci = (int*) _permutedUpdateAsSparse->i;
     double* Cx = (double*) _permutedUpdateAsSparse->x;
 
     for (size_t k = 0; k < _permutedUpdate->nnz; ++k) /* column counts */
       w[Tj [k]]++;
 
     /* column pointers */
     int n = _permutedUpdate->ncol;
     int nz = 0;
     for (int i = 0 ; i < n ; i++) {
       Cp[i] = nz;
       nz += w[i];
       w[i] = Cp[i];
     }
     Cp[n] = nz;
     assert((size_t)nz == _permutedUpdate->nnz);
 
     int p;
     for (size_t k = 0 ; k < _permutedUpdate->nnz ; ++k) {
       p = w[Tj[k]]++;
       Ci[p] = Ti[k] ;    /* A(i,j) is the pth entry in C */
       Cx[p] = Tx[k] ;
     }
 
   }

bool g2o::SparseOptimizerIncremental::initSolver	(	int	dimension,
		int	batchEveryN
	)

virtual

Reimplemented from g2o::SparseOptimizerOnline.

Definition at line 474 of file graph_optimizer_sparse_incremental.cpp.

References g2o::createSolver(), g2o::BlockSolver< Traits >::linearSolver(), g2o::Solver::setAdditionalVectorSpace(), g2o::BlockSolver< Traits >::setSchur(), and g2o::OptimizationAlgorithmWithHessian::solver().

   {
     //cerr << __PRETTY_FUNCTION__ << endl;
     slamDimension = dimension;
     if (dimension == 3) {
       setAlgorithm(createSolver("fix3_2_cholmod"));
       OptimizationAlgorithmGaussNewton* gaussNewton = dynamic_cast<OptimizationAlgorithmGaussNewton*>(solver());
       assert(gaussNewton);
       BlockSolver<BlockSolverTraits<3, 2> >* bs = dynamic_cast<BlockSolver<BlockSolverTraits<3, 2> >*>(gaussNewton->solver());
       assert(bs && "Unable to get internal block solver");
       LinearSolverCholmodOnline<Matrix3d>* s = dynamic_cast<LinearSolverCholmodOnline<Matrix3d>*>(bs->linearSolver());
       bs->setAdditionalVectorSpace(300);
       bs->setSchur(false);
       _solverInterface = s;
       _underlyingSolver = bs;
     } else {
       setAlgorithm(createSolver("fix6_3_cholmod"));
       OptimizationAlgorithmGaussNewton* gaussNewton = dynamic_cast<OptimizationAlgorithmGaussNewton*>(solver());
       assert(gaussNewton);
       BlockSolver<BlockSolverTraits<6, 3> >* bs = dynamic_cast<BlockSolver<BlockSolverTraits<6, 3> >*>(gaussNewton->solver());
       assert(bs && "Unable to get internal block solver");
       LinearSolverCholmodOnline<Matrix<double, 6, 6> >* s = dynamic_cast<LinearSolverCholmodOnline<Matrix<double, 6, 6> >*>(bs->linearSolver());
       bs->setAdditionalVectorSpace(600);
       bs->setSchur(false);
       _solverInterface = s;
       _underlyingSolver = bs;
     }
     _solverInterface->cmember = &_cmember;
     _solverInterface->batchEveryN = batchEveryN;
     if (! solver()) {
       cerr << "Error allocating solver. Allocating CHOLMOD solver failed!" << endl;
       return false;
     }
     return true;
   }

int g2o::SparseOptimizerIncremental::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::SparseOptimizer.

Definition at line 90 of file graph_optimizer_sparse_incremental.cpp.

References __PRETTY_FUNCTION__, g2o::OptimizableGraph::Vertex::colInHessian(), g2o::OptimizableGraph::Vertex::copyB(), g2o::OptimizableGraph::Vertex::hessianIndex(), g2o::OptimizationAlgorithm::init(), g2o::BaseVertex< D, T >::setEstimate(), g2o::OnlineVertexSE3::updatedEstimate, g2o::OnlineVertexSE2::updatedEstimate, vertices, and g2o::HyperGraph::Edge::vertices().

   {
     (void) iterations; // we only do one iteration anyhow
     OptimizationAlgorithm* solver = _algorithm;
     solver->init(online);
 
     int cjIterations=0;
     bool ok=true;
 
     if (! online || batchStep) {
       //cerr << "performing batch step" << endl;
       if (! online) {
         ok = _underlyingSolver->buildStructure();
         if (! ok) {
           cerr << __PRETTY_FUNCTION__ << ": Failure while building CCS structure" << endl;
           return 0;
         }
       }
 
       // copy over the updated estimate as new linearization point
       if (slamDimension == 3) {
         for (size_t i = 0; i < indexMapping().size(); ++i) {
           OnlineVertexSE2* v = static_cast<OnlineVertexSE2*>(indexMapping()[i]);
           v->setEstimate(v->updatedEstimate);
         }
       }
       else if (slamDimension == 6) {
         for (size_t i = 0; i < indexMapping().size(); ++i) {
           OnlineVertexSE3* v= static_cast<OnlineVertexSE3*>(indexMapping()[i]);
           v->setEstimate(v->updatedEstimate);
         }
       }
 
       SparseOptimizer::computeActiveErrors();
       //SparseOptimizer::linearizeSystem();
       _underlyingSolver->buildSystem();
 
       // mark vertices to be sorted as last
       int numBlocksRequired = _ivMap.size();
       if (_cmember.size() < numBlocksRequired) {
         _cmember.resize(2 * numBlocksRequired);
       }
       memset(_cmember.data(), 0, numBlocksRequired * sizeof(int));
       if (_ivMap.size() > 100) {
         for (size_t i = _ivMap.size() - 20; i < _ivMap.size(); ++i) {
           const HyperGraph::EdgeSet& eset = _ivMap[i]->edges();
           for (HyperGraph::EdgeSet::const_iterator it = eset.begin(); it != eset.end(); ++it) {
             OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
             OptimizableGraph::Vertex* v1 = static_cast<OptimizableGraph::Vertex*>(e->vertices()[0]);
             OptimizableGraph::Vertex* v2 = static_cast<OptimizableGraph::Vertex*>(e->vertices()[1]);
             if (v1->hessianIndex() >= 0)
               _cmember(v1->hessianIndex()) = 1;
             if (v2->hessianIndex() >= 0)
               _cmember(v2->hessianIndex()) = 1;
           }
         }
         //OptimizableGraph::Vertex* lastPose = _ivMap.back();
         //_cmember(lastPose->hessianIndex()) = 2;
       }
 
       ok = _underlyingSolver->solve();
 
       // get the current cholesky factor along with the permutation
       _L = _solverInterface->L();
       if (_perm.size() < (int)_L->n)
         _perm.resize(2*_L->n);
       int* p = (int*)_L->Perm;
       for (size_t i = 0; i < _L->n; ++i)
         _perm[p[i]] = i;
 
     }
     else {
       // update the b vector
       for (HyperGraph::VertexSet::iterator it = _touchedVertices.begin(); it != _touchedVertices.end(); ++it) {
         OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
         int iBase = v->colInHessian();
         v->copyB(_underlyingSolver->b() + iBase);
       }
       _solverInterface->solve(_underlyingSolver->x(), _underlyingSolver->b());
     }
 
     // print statistics for the non-zeros
     //static ofstream debugNonZeros("non-zeros.txt");
     //debugNonZeros << _solverInterface->nonZerosInL() << endl;
 
     update(_underlyingSolver->x());
     ++cjIterations; 
 
     if (verbose()){
       computeActiveErrors();
       cerr
         << "nodes = " << vertices().size()
         << "\t edges= " << _activeEdges.size()
         << "\t chi2= " << FIXED(activeChi2())
         << endl;
     }
 
     if (vizWithGnuplot)
       gnuplotVisualization();
 
     if (! ok)
       return 0;
     return 1;
   }

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

virtual

HACK updating the internal structures for online processing

Reimplemented from g2o::SparseOptimizerOnline.

Definition at line 195 of file graph_optimizer_sparse_incremental.cpp.

   {
     if (batchStep) {
       return SparseOptimizerOnline::updateInitialization(vset, eset);
     }
 
     for (HyperGraph::VertexSet::iterator it = vset.begin(); it != vset.end(); ++it) {
       OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
       v->clearQuadraticForm(); // be sure that b is zero for this vertex
     }
 
     // get the touched vertices
     _touchedVertices.clear();
     for (HyperGraph::EdgeSet::iterator it = eset.begin(); it != eset.end(); ++it) {
       OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
       OptimizableGraph::Vertex* v1 = static_cast<OptimizableGraph::Vertex*>(e->vertices()[0]);
       OptimizableGraph::Vertex* v2 = static_cast<OptimizableGraph::Vertex*>(e->vertices()[1]);
       if (! v1->fixed())
         _touchedVertices.insert(v1);
       if (! v2->fixed())
         _touchedVertices.insert(v2);
     }
     //cerr << PVAR(_touchedVertices.size()) << endl;
 
     // updating the internal structures
     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)
       _activeEdges.push_back(static_cast<OptimizableGraph::Edge*>(*it));
     //cerr << "updating internal done." << endl;
 
     // 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);
       }
     }
     //cerr << "updating index mapping done." << endl;
 
     // backup the tempindex and prepare sorting structure
 #ifdef _MSC_VER
     VertexBackup* backupIdx = new VertexBackup[_touchedVertices.size()];
 #else
     VertexBackup backupIdx[_touchedVertices.size()];
 #endif
     memset(backupIdx, 0, sizeof(VertexBackup) * _touchedVertices.size());
     int idx = 0;
     for (HyperGraph::VertexSet::iterator it = _touchedVertices.begin(); it != _touchedVertices.end(); ++it) {
       OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
       backupIdx[idx].hessianIndex = v->hessianIndex();
       backupIdx[idx].vertex = v;
       backupIdx[idx].hessianData = v->hessianData();
       ++idx;
     }
     sort(backupIdx, backupIdx + _touchedVertices.size()); // sort according to the hessianIndex which is the same order as used later by the optimizer
     for (int i = 0; i < idx; ++i) {
       backupIdx[i].vertex->setHessianIndex(i);
     }
     //cerr << "backup tempindex done." << endl;
 
     // building the structure of the update
     _updateMat.clear(true); // get rid of the old matrix structure
     _updateMat.rowBlockIndices().clear();
     _updateMat.colBlockIndices().clear();
     _updateMat.blockCols().clear();
 
     // placing the current stuff in _updateMat
     MatrixXd* lastBlock = 0;
     int sizePoses = 0;
     for (int i = 0; i < idx; ++i) {
       OptimizableGraph::Vertex* v = backupIdx[i].vertex;
       int dim = v->dimension();
       sizePoses+=dim;
       _updateMat.rowBlockIndices().push_back(sizePoses);
       _updateMat.colBlockIndices().push_back(sizePoses);
       _updateMat.blockCols().push_back(SparseBlockMatrix<MatrixXd>::IntBlockMap());
       int ind = v->hessianIndex();
       //cerr << PVAR(ind) << endl;
       if (ind >= 0) {
         MatrixXd* m = _updateMat.block(ind, ind, true);
         v->mapHessianMemory(m->data());
         lastBlock = m;
       }
     }
     lastBlock->diagonal().array() += 1e-6; // HACK to get Eigen value > 0
 
 
     for (HyperGraph::EdgeSet::const_iterator it = eset.begin(); it != eset.end(); ++it) {
       OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
       OptimizableGraph::Vertex* v1 = (OptimizableGraph::Vertex*) e->vertices()[0];
       OptimizableGraph::Vertex* v2 = (OptimizableGraph::Vertex*) e->vertices()[1];
 
       int ind1 = v1->hessianIndex();
       if (ind1 == -1)
         continue;
       int ind2 = v2->hessianIndex();
       if (ind2 == -1)
         continue;
       bool transposedBlock = ind1 > ind2;
       if (transposedBlock) // make sure, we allocate the upper triangular block
         swap(ind1, ind2);
 
       MatrixXd* m = _updateMat.block(ind1, ind2, true);
       e->mapHessianMemory(m->data(), 0, 1, transposedBlock);
     }
 
     // build the system into _updateMat
     for (HyperGraph::EdgeSet::iterator it = eset.begin(); it != eset.end(); ++it) {
       OptimizableGraph::Edge * e = static_cast<OptimizableGraph::Edge*>(*it);
       e->computeError();
     }
     for (HyperGraph::EdgeSet::iterator it = eset.begin(); it != eset.end(); ++it) {
       OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
       e->linearizeOplus(jacobianWorkspace());
       e->constructQuadraticForm();
     }
 
     // restore the original data for the vertex
     for (int i = 0; i < idx; ++i) {
       backupIdx[i].vertex->setHessianIndex(backupIdx[i].hessianIndex);
       if (backupIdx[i].hessianData)
         backupIdx[i].vertex->mapHessianMemory(backupIdx[i].hessianData);
     }
 
     // update the structure of the real block matrix
     bool solverStatus = _algorithm->updateStructure(newVertices, eset);
 
     bool updateStatus = computeCholeskyUpdate();
     if (! updateStatus) {
       cerr << "Error while computing update" << endl;
     }
 
     cholmod_sparse* updateAsSparseFactor = cholmod_factor_to_sparse(_cholmodFactor, &_cholmodCommon);
 
     // convert CCS update by permuting back to the permutation of L
     if (updateAsSparseFactor->nzmax > _permutedUpdate->nzmax) {
       //cerr << "realloc _permutedUpdate" << endl;
       cholmod_reallocate_triplet(updateAsSparseFactor->nzmax, _permutedUpdate, &_cholmodCommon);
     }
     _permutedUpdate->nnz = 0;
     _permutedUpdate->nrow = _permutedUpdate->ncol = _L->n;
     {
       int* Ap = (int*)updateAsSparseFactor->p;
       int* Ai = (int*)updateAsSparseFactor->i;
       double* Ax = (double*)updateAsSparseFactor->x;
       int* Bj = (int*)_permutedUpdate->j;
       int* Bi = (int*)_permutedUpdate->i;
       double* Bx = (double*)_permutedUpdate->x;
       for (size_t c = 0; c < updateAsSparseFactor->ncol; ++c) {
         const int& rbeg = Ap[c];
         const int& rend = Ap[c+1];
         int cc = c / slamDimension;
         int coff = c % slamDimension;
         const int& cbase = backupIdx[cc].vertex->colInHessian();
         const int& ccol = _perm(cbase + coff);
         for (int j = rbeg; j < rend; j++) {
           const int& r = Ai[j];
           const double& val = Ax[j];
 
           int rr = r / slamDimension;
           int roff = r % slamDimension;
           const int& rbase = backupIdx[rr].vertex->colInHessian();
           
           int row = _perm(rbase + roff);
           int col = ccol;
           if (col > row) // lower triangular entry
             swap(col, row);
           Bi[_permutedUpdate->nnz] = row;
           Bj[_permutedUpdate->nnz] = col;
           Bx[_permutedUpdate->nnz] = val;
           ++_permutedUpdate->nnz;
         }
       }
     }
     cholmod_free_sparse(&updateAsSparseFactor, &_cholmodCommon);
 #ifdef _MSC_VER
     delete[] backupIdx;
 #endif
 
 #if 0
     cholmod_sparse* updatePermuted = cholmod_triplet_to_sparse(_permutedUpdate, _permutedUpdate->nnz, &_cholmodCommon);
     //writeCCSMatrix("update-permuted.txt", updatePermuted->nrow, updatePermuted->ncol, (int*)updatePermuted->p, (int*)updatePermuted->i, (double*)updatePermuted->x, false);
     _solverInterface->choleskyUpdate(updatePermuted);
     cholmod_free_sparse(&updatePermuted, &_cholmodCommon);
 #else
     convertTripletUpdateToSparse();
     _solverInterface->choleskyUpdate(_permutedUpdateAsSparse);
 #endif
 
     return solverStatus;
   }

Member Data Documentation

cholmod_common g2o::SparseOptimizerIncremental::_cholmodCommon

protected

Definition at line 44 of file graph_optimizer_sparse_incremental.h.

cholmod_factor* g2o::SparseOptimizerIncremental::_cholmodFactor

protected

Definition at line 46 of file graph_optimizer_sparse_incremental.h.

CholmodExt* g2o::SparseOptimizerIncremental::_cholmodSparse

protected

Definition at line 45 of file graph_optimizer_sparse_incremental.h.

Eigen::VectorXi g2o::SparseOptimizerIncremental::_cmember

protected

Definition at line 53 of file graph_optimizer_sparse_incremental.h.

cholmod_factor* g2o::SparseOptimizerIncremental::_L

protected

Definition at line 48 of file graph_optimizer_sparse_incremental.h.

Eigen::VectorXi g2o::SparseOptimizerIncremental::_perm

protected

Definition at line 52 of file graph_optimizer_sparse_incremental.h.

cholmod_triplet* g2o::SparseOptimizerIncremental::_permutedUpdate

protected

Definition at line 47 of file graph_optimizer_sparse_incremental.h.

CholmodExt* g2o::SparseOptimizerIncremental::_permutedUpdateAsSparse

protected

Definition at line 56 of file graph_optimizer_sparse_incremental.h.

LinearSolverCholmodOnlineInterface* g2o::SparseOptimizerIncremental::_solverInterface

protected

Definition at line 49 of file graph_optimizer_sparse_incremental.h.

HyperGraph::VertexSet g2o::SparseOptimizerIncremental::_touchedVertices

protected

Definition at line 51 of file graph_optimizer_sparse_incremental.h.

Eigen::VectorXi g2o::SparseOptimizerIncremental::_tripletWorkspace

protected

Definition at line 55 of file graph_optimizer_sparse_incremental.h.

SparseBlockMatrix<Eigen::MatrixXd> g2o::SparseOptimizerIncremental::_updateMat

protected

Definition at line 43 of file graph_optimizer_sparse_incremental.h.

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

/home/xuezhisd/CLionProjects/g2o/g2o/examples/interactive_slam/g2o_incremental/graph_optimizer_sparse_incremental.h
/home/xuezhisd/CLionProjects/g2o/g2o/examples/interactive_slam/g2o_incremental/graph_optimizer_sparse_incremental.cpp

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Protected Member Functions

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Detailed Description

Constructor & Destructor Documentation

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