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)
  {
    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);
  }
Beispiel #3
0
  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;
  }
Beispiel #4
0
bool BlockSolver<Traits>::updateStructure(const std::vector<HyperGraph::Vertex*>& vset, const HyperGraph::EdgeSet& edges)
{
  for (std::vector<HyperGraph::Vertex*>::const_iterator vit = vset.begin(); vit != vset.end(); ++vit) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*vit);
    int dim = v->dimension();
    if (! v->marginalized()){
      v->setColInHessian(_sizePoses);
      _sizePoses+=dim;
      _Hpp->rowBlockIndices().push_back(_sizePoses);
      _Hpp->colBlockIndices().push_back(_sizePoses);
      _Hpp->blockCols().push_back(typename SparseBlockMatrix<PoseMatrixType>::IntBlockMap());
      ++_numPoses;
      int ind = v->hessianIndex();
      PoseMatrixType* m = _Hpp->block(ind, ind, true);
      v->mapHessianMemory(m->data());
    } else {
      std::cerr << "updateStructure(): Schur not supported" << std::endl;
      abort();
    }
  }
  resizeVector(_sizePoses + _sizeLandmarks);

  for (HyperGraph::EdgeSet::const_iterator it = edges.begin(); it != edges.end(); ++it) {
    OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);

    for (size_t viIdx = 0; viIdx < e->vertices().size(); ++viIdx) {
      OptimizableGraph::Vertex* v1 = (OptimizableGraph::Vertex*) e->vertex(viIdx);
      int ind1 = v1->hessianIndex();
      int indexV1Bak = ind1;
      if (ind1 == -1)
        continue;
      for (size_t vjIdx = viIdx + 1; vjIdx < e->vertices().size(); ++vjIdx) {
        OptimizableGraph::Vertex* v2 = (OptimizableGraph::Vertex*) e->vertex(vjIdx);
        int ind2 = v2->hessianIndex();
        if (ind2 == -1)
          continue;
        ind1 = indexV1Bak;
        bool transposedBlock = ind1 > ind2;
        if (transposedBlock) // make sure, we allocate the upper triangular block
          std::swap(ind1, ind2);

        if (! v1->marginalized() && !v2->marginalized()) {
          PoseMatrixType* m = _Hpp->block(ind1, ind2, true);
          e->mapHessianMemory(m->data(), viIdx, vjIdx, transposedBlock);
        } else { 
          std::cerr << __PRETTY_FUNCTION__ << ": not supported" << std::endl;
        }
      }
    }

  }

  return true;
}
int main(int argc, char** argv) {
  CommandArgs arg;


  std::string outputFilename;
  std::string inputFilename;

  arg.param("o", outputFilename, "", "output file name"); 
  arg.paramLeftOver("input-filename ", inputFilename, "", "graph file to read", true);
  arg.parseArgs(argc, argv);
  OptimizableGraph graph;
  if (!graph.load(inputFilename.c_str())){
    cerr << "Error: cannot load a file from \"" << inputFilename << "\", aborting." << endl;
    return 0;
  }
  HyperGraph::EdgeSet removedEdges;
  HyperGraph::VertexSet removedVertices;
  for (HyperGraph::EdgeSet::iterator it = graph.edges().begin(); it!=graph.edges().end(); it++) {
    HyperGraph::Edge* e = *it;
    EdgeSE2PointXY* edgePointXY = dynamic_cast<EdgeSE2PointXY*>(e);
    if (edgePointXY) {
      VertexSE2* pose    = dynamic_cast<VertexSE2*>(edgePointXY->vertex(0));
      VertexPointXY* landmark = dynamic_cast<VertexPointXY*>(edgePointXY->vertex(1));
      FeaturePointXYData * feature = new FeaturePointXYData();
      feature->setPositionMeasurement(edgePointXY->measurement());
      feature->setPositionInformation(edgePointXY->information());
      pose->addUserData(feature); 
      removedEdges.insert(edgePointXY);
      removedVertices.insert(landmark);
    }
  }
  
  for (HyperGraph::EdgeSet::iterator it = removedEdges.begin(); it!=removedEdges.end(); it++){
    OptimizableGraph::Edge* e = dynamic_cast<OptimizableGraph::Edge*>(*it);
    graph.removeEdge(e);
  }

  for (HyperGraph::VertexSet::iterator it = removedVertices.begin(); it!=removedVertices.end(); it++){
    OptimizableGraph::Vertex* v = dynamic_cast<OptimizableGraph::Vertex*>(*it);
    graph.removeVertex(v);
  }

  
  if (outputFilename.length()){
    graph.save(outputFilename.c_str());
  }
 
}
  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;
  }
Beispiel #7
0
void assignHierarchicalEdges(StarSet& stars, EdgeStarMap& esmap, EdgeLabeler* labeler, EdgeCreator* creator, SparseOptimizer* optimizer, int minNumEdges, int maxIterations){
  // now construct the hierarchical edges for all the stars
  int starNum=0;
  for (StarSet::iterator it=stars.begin(); it!=stars.end(); it++){
    cerr << "STAR# " << starNum << endl;
    Star* s=*it;
    std::vector<OptimizableGraph::Vertex*> vertices(2);
    vertices[0]= (OptimizableGraph::Vertex*) *s->_gauge.begin();
    cerr << "eIs"  << endl;
    HyperGraph::VertexSet vNew =s->lowLevelVertices();
    for (HyperGraph::VertexSet::iterator vit=s->_lowLevelVertices.begin(); vit!=s->_lowLevelVertices.end(); vit++){
      OptimizableGraph::Vertex* v=(OptimizableGraph::Vertex*)*vit;
      vertices[1]=v;
      if (v==vertices[0])
        continue;
      HyperGraph::EdgeSet eInSt;
      int numEdges = vertexEdgesInStar(eInSt, v, s, esmap);
      if (Factory::instance()->tag(v)==Factory::instance()->tag(vertices[0]) || numEdges>minNumEdges) {
        OptimizableGraph::Edge* e=creator->createEdge(vertices);
        //cerr << "creating edge" << e << endl;
        if (e) {
          e->setLevel(1);
          optimizer->addEdge(e);
          s->_starEdges.insert(e);
        } else {
          cerr << "THERE" << endl;
          cerr << "FATAL, cannot create edge" << endl;
        }
      } else {
        vNew.erase(v);
        // cerr << numEdges << " ";
        // cerr << "r " <<  v-> id() << endl;
        // remove from the star all edges that are not sufficiently connected
        for (HyperGraph::EdgeSet::iterator it=eInSt.begin(); it!=eInSt.end(); it++){
          HyperGraph::Edge* e=*it;
          s->lowLevelEdges().erase(e);
        }
      }
    }
    s->lowLevelVertices()=vNew;
    //cerr << endl;
    cerr <<  "gauge: " << (*s->_gauge.begin())->id()
      << " edges:" << s->_lowLevelEdges.size()
      << " hedges" << s->_starEdges.size() << endl;

    const bool debug = false;
    if (debug){
      char starLowName[100];
      sprintf(starLowName, "star-%04d-low.g2o", starNum);
      ofstream starLowStream(starLowName);
      optimizer->saveSubset(starLowStream, s->_lowLevelEdges);
    }
    bool labelOk=s->labelStarEdges(maxIterations, labeler);
    if (labelOk) {
      if (debug) {
        char starHighName[100];
        sprintf(starHighName, "star-%04d-high.g2o", starNum);
        ofstream starHighStream(starHighName);
        optimizer->saveSubset(starHighStream, s->_starEdges);
      }
    } else {
      cerr << "FAILURE" << endl;
    }
    starNum++;
  }
}
Beispiel #8
0
bool saveGnuplot(const std::string& gnudump, const HyperGraph::VertexSet& vertices, const HyperGraph::EdgeSet& edges)
{
  // seek for an action whose name is writeGnuplot in the library
  HyperGraphElementAction* saveGnuplot = HyperGraphActionLibrary::instance()->actionByName("writeGnuplot");
  if (! saveGnuplot ){
    cerr << __PRETTY_FUNCTION__ << ": no action \"writeGnuplot\" registered" << endl;
    return false;
  }
  WriteGnuplotAction::Parameters params;

  int maxDim = -1;
  int minDim = numeric_limits<int>::max();
  for (HyperGraph::VertexSet::const_iterator it = vertices.begin(); it != vertices.end(); ++it){
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
    int vdim = v->dimension();
    maxDim = (std::max)(vdim, maxDim);
    minDim = (std::min)(vdim, minDim);
  }

  string extension = getFileExtension(gnudump);
  if (extension.size() == 0)
    extension = "dat";
  string baseFilename = getPureFilename(gnudump);

  // check for odometry edges
  bool hasOdomEdge = false;
  bool hasLandmarkEdge = false;
  for (HyperGraph::EdgeSet::const_iterator it = edges.begin(); it != edges.end(); ++it) {
    OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
    if (e->vertices().size() == 2) {
      if (edgeAllVertsSameDim(e, maxDim))
        hasOdomEdge = true;
      else
        hasLandmarkEdge = true;
    }
    if (hasOdomEdge && hasLandmarkEdge)
      break;
  }

  bool fileStatus = true;
  if (hasOdomEdge) {
    string odomFilename = baseFilename + "_odom_edges." + extension;
    cerr << "# saving " << odomFilename << " ... ";
    ofstream fout(odomFilename.c_str());
    if (! fout) {
      cerr << "Unable to open file" << endl;
      return false;
    }
    params.os = &fout;

    // writing odometry edges
    for (HyperGraph::EdgeSet::const_iterator it = edges.begin(); it != edges.end(); ++it) {
      OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
      if (e->vertices().size() != 2 || ! edgeAllVertsSameDim(e, maxDim))
        continue;
      (*saveGnuplot)(e, &params);
    }
    cerr << "done." << endl;
  }

  if (hasLandmarkEdge) {
    string filename = baseFilename + "_landmarks_edges." + extension;
    cerr << "# saving " << filename << " ... ";
    ofstream fout(filename.c_str());
    if (! fout) {
      cerr << "Unable to open file" << endl;
      return false;
    }
    params.os = &fout;

    // writing landmark edges
    for (HyperGraph::EdgeSet::const_iterator it = edges.begin(); it != edges.end(); ++it) {
      OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
      if (e->vertices().size() != 2 || edgeAllVertsSameDim(e, maxDim))
        continue;
      (*saveGnuplot)(e, &params);
    }
    cerr << "done." << endl;
  }

  if (1) {
    string filename = baseFilename + "_edges." + extension;
    cerr << "# saving " << filename << " ... ";
    ofstream fout(filename.c_str());
    if (! fout) {
      cerr << "Unable to open file" << endl;
      return false;
    }
    params.os = &fout;

    // writing all edges
    for (HyperGraph::EdgeSet::const_iterator it = edges.begin(); it != edges.end(); ++it) {
      OptimizableGraph::Edge* e = static_cast<OptimizableGraph::Edge*>(*it);
      (*saveGnuplot)(e, &params);
    }
    cerr << "done." << endl;
  }

  if (1) {
    string filename = baseFilename + "_vertices." + extension;
    cerr << "# saving " << filename << " ... ";
    ofstream fout(filename.c_str());
    if (! fout) {
      cerr << "Unable to open file" << endl;
      return false;
    }
    params.os = &fout;

    for (HyperGraph::VertexSet::const_iterator it = vertices.begin(); it != vertices.end(); ++it){
      OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
      (*saveGnuplot)(v, &params);
    }
    cerr << "done." << endl;
  }

  return fileStatus;
}