C++ hypergraph::VertexSet类代码示例

  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);
  }

void starsInEdge(StarSet& stars, HyperGraph::Edge* e, EdgeStarMap& esmap, HyperGraph::VertexSet& gauge){
  for (size_t i=0; i<e->vertices().size(); i++){
    OptimizableGraph::Vertex* v=(OptimizableGraph::Vertex*)e->vertices()[i];
    if (gauge.find(v)==gauge.end())
      starsInVertex(stars, v, esmap);
  }
}

void OptimizableGraph::push(HyperGraph::VertexSet& vset) {
  for (HyperGraph::VertexSet::iterator it = vset.begin(); it != vset.end();
      it++) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
    v->push();
  }
}

void HyperDijkstra::shortestPaths(HyperGraph::Vertex* v, HyperDijkstra::CostFunction* cost, double maxDistance,
                                  double comparisonConditioner, bool directed, double maxEdgeCost)
{
    HyperGraph::VertexSet vset;
    vset.insert(v);
    shortestPaths(vset, cost, maxDistance, comparisonConditioner, directed, maxEdgeCost);
}

  void OptimizableGraph::setFixed(HyperGraph::VertexSet& vset, bool fixed)
{
  for (HyperGraph::VertexSet::iterator it=vset.begin(); it!=vset.end(); ++it) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
    v->setFixed(fixed);
  }
}

void OptimizableGraph::discardTop(HyperGraph::VertexSet& vset)
{
  for (HyperGraph::VertexSet::iterator it=vset.begin(); it!=vset.end(); ++it) {
    OptimizableGraph::Vertex* v = static_cast<OptimizableGraph::Vertex*>(*it);
    v->discardTop();
  }
}

bool saveGnuplot(const std::string& gnudump, const OptimizableGraph& optimizer)
{
  HyperGraph::VertexSet vset;
  for (HyperGraph::VertexIDMap::const_iterator it=optimizer.vertices().begin(); it!=optimizer.vertices().end(); it++){
    vset.insert(it->second);
  }
  return saveGnuplot(gnudump, vset, optimizer.edges());
}

  void SparseOptimizer::push(HyperGraph::VertexSet& vlist)
  {
    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 SparseOptimizer::pop(HyperGraph::VertexSet& vlist)
  {
    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 << "FATAL POP SET" << endl;
    }
  }

  void HyperDijkstra::shortestPaths(HyperGraph::VertexSet& vset, HyperDijkstra::CostFunction* cost, 
      double maxDistance, double comparisonConditioner, bool directed, double maxEdgeCost)
  {
    reset();
    std::priority_queue< AdjacencyMapEntry > frontier;
    for (HyperGraph::VertexSet::iterator vit=vset.begin(); vit!=vset.end(); ++vit){
      HyperGraph::Vertex* v=*vit;
      AdjacencyMap::iterator it=_adjacencyMap.find(v);
      assert(it!=_adjacencyMap.end());
      it->second._distance=0.;
      it->second._parent=0;
      frontier.push(it->second);
    }

    while(! frontier.empty()){
      AdjacencyMapEntry entry=frontier.top();
      frontier.pop();
      HyperGraph::Vertex* u=entry.child();
      AdjacencyMap::iterator ut=_adjacencyMap.find(u);
      assert(ut!=_adjacencyMap.end());
      double uDistance=ut->second.distance();

      std::pair< HyperGraph::VertexSet::iterator, bool> insertResult=_visited.insert(u); (void) insertResult;
      HyperGraph::EdgeSet::iterator et=u->edges().begin();
      while (et != u->edges().end()){
        HyperGraph::Edge* edge=*et;
        ++et;

        if (directed && edge->vertex(0) != u)
          continue;

        for (size_t i = 0; i < edge->vertices().size(); ++i) {
          HyperGraph::Vertex* z = edge->vertex(i);
          if (z == u)
            continue;

          double edgeDistance=(*cost)(edge, u, z);
          if (edgeDistance==std::numeric_limits< double >::max() || edgeDistance > maxEdgeCost)
            continue;
          double zDistance=uDistance+edgeDistance;
          //cerr << z->id() << " " << zDistance << endl;

          AdjacencyMap::iterator ot=_adjacencyMap.find(z);
          assert(ot!=_adjacencyMap.end());

          if (zDistance+comparisonConditioner<ot->second.distance() && zDistance<maxDistance){
            ot->second._distance=zDistance;
            ot->second._parent=u;
            ot->second._edge=edge;
            frontier.push(ot->second);
          }
        }
      }
    }
  }

  bool SparseOptimizer::initializeOptimization(int level)
  {
    HyperGraph::VertexSet vset;

    for (VertexIDMap::iterator
         it  = vertices().begin();
         it != vertices().end();
         it++)
       vset.insert(it->second);

    return initializeOptimization(vset,level);
  }

  void SparseOptimizer::computeInitialGuess(EstimatePropagatorCost& costFunction)
  {
    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;
    }
  }

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());
  }
 
}

void HyperDijkstra::connectedSubset(HyperGraph::VertexSet& connected, HyperGraph::VertexSet& visited,
                                    HyperGraph::VertexSet& startingSet,
                                    HyperGraph* g, HyperGraph::Vertex* v,
                                    HyperDijkstra::CostFunction* cost, double distance,
                                    double comparisonConditioner, double maxEdgeCost)
{
    typedef std::queue<HyperGraph::Vertex*> VertexDeque;
    visited.clear();
    connected.clear();
    VertexDeque frontier;
    HyperDijkstra dv(g);
    connected.insert(v);
    frontier.push(v);
    while (! frontier.empty()) {
        HyperGraph::Vertex* v0=frontier.front();
        frontier.pop();
        dv.shortestPaths(v0, cost, distance, comparisonConditioner, false, maxEdgeCost);
        for (HyperGraph::VertexSet::iterator it=dv.visited().begin(); it!=dv.visited().end(); ++it) {
            visited.insert(*it);
            if (startingSet.find(*it)==startingSet.end())
                continue;
            std::pair<HyperGraph::VertexSet::iterator, bool> insertOutcome=connected.insert(*it);
            if (insertOutcome.second) { // the node was not in the connectedSet;
                frontier.push(dynamic_cast<HyperGraph::Vertex*>(*it));
            }
        }
    }
}

  bool SparseOptimizer::initializeOptimization
     (HyperGraph::VertexSet& vset, int level)
  {

    // Recorre todos los vertices introducidos en el optimizador.
    // Para cada vertice 'V' obtiene los edges de los que forma parte.
    // Para cada uno de esos edges, se mira si todos sus vertices estan en el
    // optimizador. Si lo estan, el edge se aniade a _activeEdges.
    // Si el vertice 'V' tiene algun edge con todos los demas vertices en el
    // optimizador, se aniade 'V' a _activeVertices

    // Al final se asignan unos indices internos para los vertices:
    // -1: vertices fijos
    // 0..n: vertices no fijos y NO marginalizables
    // n+1..m: vertices no fijos y marginalizables
    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)
          {
            auxEdgeSet.insert(reinterpret_cast<OptimizableGraph::Edge*>(*it));
            levelEdges++;
          }
        }
      }
      if (levelEdges)   _activeVertices.push_back(v);
    }

    _activeEdges.reserve(auxEdgeSet.size());
    for (set<Edge*>::iterator
         it = auxEdgeSet.begin();
         it != auxEdgeSet.end();
         ++it)
       _activeEdges.push_back(*it);

    sortVectorContainers();
    return buildIndexMapping(_activeVertices);
  }