C++ Point_set::begin_or_selection_begin方法代码示例

  void advancing_front (const Point_set& points, Scene_polyhedron_item* new_item, double size,
                        double radius_ratio_bound = 5., double beta = 0.52)
  {

    // TODO: build DT with indices
    
    Polyhedron& P = * const_cast<Polyhedron*>(new_item->polyhedron());
    Radius filter (size);

    typedef CGAL::Advancing_front_surface_reconstruction_vertex_base_3<Kernel> LVb;
    typedef CGAL::Advancing_front_surface_reconstruction_cell_base_3<Kernel> LCb;

    typedef CGAL::Triangulation_data_structure_3<LVb,LCb> Tds;
    typedef CGAL::Delaunay_triangulation_3<Kernel,Tds> Triangulation_3;

    typedef CGAL::Advancing_front_surface_reconstruction<Triangulation_3, Radius> Reconstruction;

    Triangulation_3 dt( boost::make_transform_iterator(points.begin_or_selection_begin(), Point_set_make_pair_point_index(points)),
                        boost::make_transform_iterator(points.end(), Point_set_make_pair_point_index(points)) );

    Reconstruction R(dt, filter);
    R.run(radius_ratio_bound, beta);
    CGAL::AFSR::construct_polyhedron(P, R);
						  
  }

  void compute_normals (Point_set& points, unsigned int neighbors)
  {
    CGAL::jet_estimate_normals<Concurrency_tag>(points.begin_or_selection_begin(), points.end(),
                                                points.point_map(),
                                                points.normal_map(),
                                                2 * neighbors);

    points.set_first_selected (CGAL::mst_orient_normals (points.begin(), points.end(),
                                                         points.point_map(),
                                                         points.normal_map(),
                                                         2 * neighbors));
    points.delete_selection();
  }

bool poisson_reconstruct(FaceGraph* graph,
                         Point_set& points,
                         typename Traits::FT sm_angle, // Min triangle angle (degrees).
                         typename Traits::FT sm_radius, // Max triangle size w.r.t. point set average spacing.
                         typename Traits::FT sm_distance, // Approximation error w.r.t. point set average spacing.
                         const QString& solver_name, // solver name
                         bool use_two_passes,
                         bool do_not_fill_holes)
{
  // Poisson implicit function
  typedef CGAL::Poisson_reconstruction_function<Traits> Poisson_reconstruction_function;

  // Surface mesher
  typedef CGAL::Surface_mesh_default_triangulation_3 STr;
  typedef CGAL::Surface_mesh_complex_2_in_triangulation_3<STr> C2t3;
  typedef CGAL::Implicit_surface_3<Traits, Poisson_reconstruction_function> Surface_3;

  // AABB tree
  typedef CGAL::AABB_face_graph_triangle_primitive<FaceGraph> Primitive;
  typedef CGAL::AABB_traits<Traits, Primitive> AABB_traits;
  typedef CGAL::AABB_tree<AABB_traits> AABB_tree;
    CGAL::Timer task_timer; task_timer.start();

    //***************************************
    // Checks requirements
    //***************************************

    if (points.size() == 0)
    {
      std::cerr << "Error: empty point set" << std::endl;
     return false;
    }

    bool points_have_normals = points.has_normal_map();
    if ( ! points_have_normals )
    {
      std::cerr << "Input point set not supported: this reconstruction method requires oriented normals" << std::endl;
     return false;
    }

    CGAL::Timer reconstruction_timer; reconstruction_timer.start();

    //***************************************
    // Computes implicit function
    //***************************************

 
    std::cerr << "Computes Poisson implicit function "
              << "using " << solver_name.toLatin1().data() << " solver...\n";
              
    
    // Creates implicit function from the point set.
    // Note: this method requires an iterator over points
    // + property maps to access each point's position and normal.
    Poisson_reconstruction_function function(points.begin_or_selection_begin(), points.end(),
                                             points.point_map(), points.normal_map());

    bool ok = false;    
    #ifdef CGAL_EIGEN3_ENABLED
    if(solver_name=="Eigen - built-in simplicial LDLt")
    {
      CGAL::Eigen_solver_traits<Eigen::SimplicialCholesky<CGAL::Eigen_sparse_matrix<double>::EigenType> > solver;
      ok = function.compute_implicit_function(solver, use_two_passes);
    }
    if(solver_name=="Eigen - built-in CG")
    {
      CGAL::Eigen_solver_traits<Eigen::ConjugateGradient<CGAL::Eigen_sparse_matrix<double>::EigenType> > solver;
      solver.solver().setTolerance(1e-6);
      solver.solver().setMaxIterations(1000);
      ok = function.compute_implicit_function(solver, use_two_passes);
    }
    #endif

    // Computes the Poisson indicator function f()
    // at each vertex of the triangulation.
    if ( ! ok )
    {
      std::cerr << "Error: cannot compute implicit function" << std::endl;
     return false;
    }

    // Prints status
    std::cerr << "Total implicit function (triangulation+refinement+solver): " << task_timer.time() << " seconds\n";
    task_timer.reset();

    //***************************************
    // Surface mesh generation
    //***************************************

    std::cerr << "Surface meshing...\n";

    // Computes average spacing
    Kernel::FT average_spacing = CGAL::compute_average_spacing<Concurrency_tag>(points.all_or_selection_if_not_empty(),
                                                                                6 /* knn = 1 ring */,
                                                                                points.parameters());

    // Gets one point inside the implicit surface
    Kernel::Point_3 inner_point = function.get_inner_point();
    Kernel::FT inner_point_value = function(inner_point);
    if(inner_point_value >= 0.0)
//.........这里部分代码省略.........

  void scale_space (const Point_set& points, ItemsInserter items,
		    unsigned int scale, bool generate_smooth = false,
                    bool separate_shells = false, bool force_manifold = true,
                    unsigned int samples = 300, unsigned int iterations = 4)
  {
    ScaleSpace reconstruct (scale, samples);
    reconstruct.reconstruct_surface(points.points().begin(), points.points().end(),
                                    iterations,
                                    separate_shells, force_manifold);

    for( unsigned int sh = 0; sh < reconstruct.number_of_shells(); ++sh )
      {
        Scene_polygon_soup_item* new_item
          = new Scene_polygon_soup_item ();
        new_item->setColor(Qt::lightGray);
        new_item->setRenderingMode(FlatPlusEdges);
        new_item->init_polygon_soup(points.size(), reconstruct.number_of_triangles ());

        Scene_polygon_soup_item* smooth_item = NULL;
        if (generate_smooth)
          {
            smooth_item = new Scene_polygon_soup_item ();
            smooth_item->setColor(Qt::lightGray);
            smooth_item->setRenderingMode(FlatPlusEdges);
            smooth_item->init_polygon_soup(points.size(), reconstruct.number_of_triangles ());
          }

        std::map<unsigned int, unsigned int> map_i2i;
        unsigned int current_index = 0;
    
        for (ScaleSpace::Triple_iterator it = reconstruct.shell_begin (sh);
             it != reconstruct.shell_end (sh); ++ it)
          {
            for (unsigned int ind = 0; ind < 3; ++ ind)
              {
                if (map_i2i.find ((*it)[ind]) == map_i2i.end ())
                  {
                    map_i2i.insert (std::make_pair ((*it)[ind], current_index ++));
                    Point p = points.point(*(points.begin_or_selection_begin() + (*it)[ind]));
                    new_item->new_vertex (p.x (), p.y (), p.z ());
                    
                    if (generate_smooth)
                      {
                        p = *(reconstruct.points_begin() + (*it)[ind]);
                        smooth_item->new_vertex (p.x (), p.y (), p.z ());
                      }
                  }
              }
            new_item->new_triangle( map_i2i[(*it)[0]],
                                    map_i2i[(*it)[1]],
                                    map_i2i[(*it)[2]] );
            if (generate_smooth)
              smooth_item->new_triangle( map_i2i[(*it)[0]],
                                         map_i2i[(*it)[1]],
                                         map_i2i[(*it)[2]] );
              
          }

        *(items ++) = new_item;
        if (generate_smooth)
          *(items ++) = smooth_item;
      }

    if (force_manifold)
      {
        std::ptrdiff_t num = std::distance( reconstruct.garbage_begin(  ),
                                            reconstruct.garbage_end(  ) );

        Scene_polygon_soup_item* new_item
          = new Scene_polygon_soup_item ();
        new_item->setColor(Qt::blue);
        new_item->setRenderingMode(FlatPlusEdges);
        new_item->init_polygon_soup(points.size(), num);

        Scene_polygon_soup_item* smooth_item = NULL;
        if (generate_smooth)
          {
            smooth_item = new Scene_polygon_soup_item ();
            smooth_item->setColor(Qt::blue);
            smooth_item->setRenderingMode(FlatPlusEdges);
            smooth_item->init_polygon_soup(points.size(), num);
          }

        std::map<unsigned int, unsigned int> map_i2i;

        unsigned int current_index = 0;
        for (ScaleSpace::Triple_iterator it=reconstruct.garbage_begin(),
               end=reconstruct.garbage_end();it!=end;++it)
          {
            for (unsigned int ind = 0; ind < 3; ++ ind)
              {
                if (map_i2i.find ((*it)[ind]) == map_i2i.end ())
                  {
                    map_i2i.insert (std::make_pair ((*it)[ind], current_index ++));
                    Point p = points.point(*(points.begin_or_selection_begin() + (*it)[ind]));
                    new_item->new_vertex (p.x (), p.y (), p.z ());
                    
                    if (generate_smooth)
                      {
                        p = *(reconstruct.points_begin() + (*it)[ind]);
//.........这里部分代码省略.........

  unsigned int scale_of_noise (const Point_set& points, double& size)
  {
    Tree tree(points.begin_or_selection_begin(), points.end(),
              Tree::Splitter(), Search_traits (points.point_map()));
    Distance tr_dist (points.point_map());
    
    double ratio_kept = (points.size() < 1000)
      ? 1. : 1000. / (points.size());
    
    std::vector<Point> subset;
    for (Point_set::const_iterator it = points.begin(); it != points.end(); ++ it)
      if (rand() / (double)RAND_MAX < ratio_kept)
    	subset.push_back (points.point(*it));
    
    std::vector<unsigned int> scales;
    generate_scales (std::back_inserter (scales));

    std::vector<unsigned int> chosen;
    
    for (std::size_t i = 0; i < subset.size (); ++ i)
      {
    	Neighbor_search search(tree, subset[i],scales.back(), 0, true, tr_dist);
	double current = 0.;
    	unsigned int nb = 0;
    	std::size_t index = 0;
	double minimum = (std::numeric_limits<double>::max)();
	unsigned int c = 0;
	
    	for (Search_iterator search_iterator = search.begin();
    	     search_iterator != search.end (); ++ search_iterator, ++ nb)
    	  {
	    current += search_iterator->second;

    	    if (nb + 1 == scales[index])
    	      {
		double score = std::sqrt (current / scales[index])
		  / std::pow (scales[index], 0.375); // NB ^ (5/12)

		if (score < minimum)
		  {
		    minimum = score;
		    c = scales[index];
		  }

    		++ index;
    		if (index == scales.size ())
    		  break;
    	      }
    	  }
	chosen.push_back (c);
      }

    std::sort (chosen.begin (), chosen.end());

    unsigned int noise_scale = chosen[chosen.size() / 2];
    size = 0.;
    for (std::size_t i = 0; i < subset.size (); ++ i)
      {
    	Neighbor_search search(tree, subset[i], noise_scale, 0, true, tr_dist);
	size += std::sqrt ((-- search.end())->second);
      }
    size /= subset.size();

    
    return noise_scale;
  }

  unsigned int scale_of_anisotropy (const Point_set& points, double& size)
  {
    Tree tree(points.begin_or_selection_begin(), points.end(),
              Tree::Splitter(), Search_traits (points.point_map()));
    
    double ratio_kept = (points.size() < 1000)
      ? 1. : 1000. / (points.size());
    
    std::vector<Point> subset;
    for (Point_set::const_iterator it = points.begin(); it != points.end(); ++ it)
      if (rand() / (double)RAND_MAX < ratio_kept)
    	subset.push_back (points.point(*it));
    
    std::vector<unsigned int> scales;
    generate_scales (std::back_inserter (scales));

    std::vector<unsigned int> chosen;
    Distance tr_dist (points.point_map());
    
    for (std::size_t i = 0; i < subset.size (); ++ i)
      {
    	Neighbor_search search(tree, subset[i],scales.back(), 0, true, tr_dist);
	double current = 0.;
    	unsigned int nb = 0;
    	std::size_t index = 0;
	double maximum = 0.;
	unsigned int c = 0;
	
    	for (Search_iterator search_iterator = search.begin();
    	     search_iterator != search.end (); ++ search_iterator, ++ nb)
    	  {
	    current += search_iterator->second;

    	    if (nb + 1 == scales[index])
    	      {
		double score = std::sqrt (current / scales[index])
		  / std::pow (scales[index], 0.75); // NB ^ (3/4)

		if (score > maximum)
		  {
		    maximum = score;
		    c = scales[index];
		  }

    		++ index;
    		if (index == scales.size ())
    		  break;
    	      }
    	  }
	chosen.push_back (c);
      }

    double mean = 0.;
    for (std::size_t i = 0; i < chosen.size(); ++ i)
      mean += chosen[i];
    mean /= chosen.size();
    unsigned int aniso_scale = static_cast<unsigned int>(mean);

    size = 0.;
    for (std::size_t i = 0; i < subset.size (); ++ i)
      {
    	Neighbor_search search(tree, subset[i], aniso_scale, 0, true, tr_dist);
	size += std::sqrt ((-- search.end())->second);
      }
    size /= subset.size();
    
    return aniso_scale;
  }