bool SparseOptimizer::initializeOptimization(HyperGraph::EdgeSet& eset)
{
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);
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();
return buildIndexMapping(_activeVertices);
}
bool SparseOptimizer::updateInitialization(HyperGraph::VertexSet& vset, HyperGraph::EdgeSet& eset)
{
std::vector<HyperGraph::Vertex*> newVertices;
newVertices.reserve(vset.size());
_activeVertices.reserve(_activeVertices.size() + vset.size());
//for (HyperGraph::VertexSet::iterator it = vset.begin(); it != vset.end(); ++it)
//_activeVertices.push_back(static_cast<OptimizableGraph::Vertex*>(*it));
_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));
// 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->setTempIndex(next);
_ivMap.push_back(v);
newVertices.push_back(v);
_activeVertices.push_back(v);
next++;
}
else // not supported right now
abort();
}
else {
v->setTempIndex(-1);
}
}
//if (newVertices.size() != vset.size())
//cerr << __PRETTY_FUNCTION__ << ": something went wrong " << PVAR(vset.size()) << " " << PVAR(newVertices.size()) << endl;
return _solver->updateStructure(newVertices, eset);
}
bool SparseOptimizer::initializeOptimization(HyperGraph::EdgeSet& eset){
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;
}
size_t vertexEdgesInStar(HyperGraph::EdgeSet& eset, HyperGraph::Vertex* v, Star* s, EdgeStarMap& esmap){
eset.clear();
for (HyperGraph::EdgeSet::iterator it=v->edges().begin(); it!=v->edges().end(); it++){
HyperGraph::Edge* e=*it;
EdgeStarMap::iterator eit=esmap.find(e);
if (eit!=esmap.end() && eit->second == s)
eset.insert(e);
}
return eset.size();
}
bool SparseOptimizerIncremental::updateInitialization(HyperGraph::VertexSet& vset, HyperGraph::EdgeSet& eset)
{
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
VertexBackup backupIdx[_touchedVertices.size()];
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();
}
for (HyperGraph::EdgeSet::iterator it = eset.begin(); it != eset.end(); ++it) {
OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
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);
#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;
}
