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-/*    This file is part of the Gudhi Library. The Gudhi library
- *    (Geometric Understanding in Higher Dimensions) is a generic C++
- *    library for computational topology.
- *
- *    Author:       Francois Godi
- *
- *    Copyright (C) 2015 Inria
- *
- *    This program is free software: you can redistribute it and/or modify
- *    it under the terms of the GNU General Public License as published by
- *    the Free Software Foundation, either version 3 of the License, or
- *    (at your option) any later version.
- *
- *    This program is distributed in the hope that it will be useful,
- *    but WITHOUT ANY WARRANTY; without even the implied warranty of
- *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
- *    GNU General Public License for more details.
- *
- *    You should have received a copy of the GNU General Public License
- *    along with this program.  If not, see <http://www.gnu.org/licenses/>.
- */
-
-#ifndef NEIGHBORS_FINDER_H_
-#define NEIGHBORS_FINDER_H_
-
-// Inclusion order is important for CGAL patch
-#include <CGAL/Kd_tree.h>
-#include <CGAL/Search_traits.h>
-
-#include <gudhi/Persistence_graph.h>
-#include <gudhi/Internal_point.h>
-
-#include <unordered_set>
-#include <vector>
-#include <algorithm>  // for std::max
-
-namespace Gudhi {
-
-namespace persistence_diagram {
-
-/** \internal \brief Variant of CGAL::Fuzzy_iso_box to ensure that the box ic closed. It isn't clear how necessary that is.
- */
-struct Square_query {
-  typedef CGAL::Dimension_tag<2> D;
-  typedef Internal_point Point_d;
-  typedef double FT;
-  bool contains(Point_d p) const {
-    return std::max(std::abs(p.x()-c.x()), std::abs(p.y()-c.y())) <= size;
-  }
-  bool inner_range_intersects(CGAL::Kd_tree_rectangle<FT, D> const&r) const {
-    return
-      r.max_coord(0) >= c.x() - size &&
-      r.min_coord(0) <= c.x() + size &&
-      r.max_coord(1) >= c.y() - size &&
-      r.min_coord(1) <= c.y() + size;
-  }
-  bool outer_range_contains(CGAL::Kd_tree_rectangle<FT, D> const&r) const {
-    return
-      r.min_coord(0) >= c.x() - size &&
-      r.max_coord(0) <= c.x() + size &&
-      r.min_coord(1) >= c.y() - size &&
-      r.max_coord(1) <= c.y() + size;
-  }
-  Point_d c;
-  FT size;
-};
-
-/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U
- * (which can be a projection).
- *
- * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically
- * removed.
- *
- * \ingroup bottleneck_distance
- */
-class Neighbors_finder {
-  typedef CGAL::Dimension_tag<2> D;
-  typedef CGAL::Search_traits<double, Internal_point, const double*, Construct_coord_iterator, D> Traits;
-  typedef CGAL::Kd_tree<Traits> Kd_tree;
-
- public:
-  /** \internal \brief Constructor taking the near distance definition as parameter. */
-  Neighbors_finder(const Persistence_graph& g, double r);
-  /** \internal \brief A point added will be possibly pulled. */
-  void add(int v_point_index);
-  /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if
-   * there isn't such a point. */
-  int pull_near(int u_point_index);
-  /** \internal \brief Returns and remove all the V points near to the U point given as parameter. */
-  std::vector<int> pull_all_near(int u_point_index);
-
- private:
-  const Persistence_graph& g;
-  const double r;
-  Kd_tree kd_t;
-  std::unordered_set<int> projections_f;
-};
-
-/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U
- * (which can be a projection) in a layered graph layer given as parmeter.
- *
- * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically
- * removed.
- *
- * \ingroup bottleneck_distance
- */
-class Layered_neighbors_finder {
- public:
-  /** \internal \brief Constructor taking the near distance definition as parameter. */
-  Layered_neighbors_finder(const Persistence_graph& g, double r);
-  /** \internal \brief A point added will be possibly pulled. */
-  void add(int v_point_index, int vlayer);
-  /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if
-   * there isn't such a point. */
-  int pull_near(int u_point_index, int vlayer);
-  /** \internal \brief Returns the number of layers. */
-  int vlayers_number() const;
-
- private:
-  const Persistence_graph& g;
-  const double r;
-  std::vector<std::unique_ptr<Neighbors_finder>> neighbors_finder;
-};
-
-inline Neighbors_finder::Neighbors_finder(const Persistence_graph& g, double r) :
-    g(g), r(r), kd_t(), projections_f() { }
-
-inline void Neighbors_finder::add(int v_point_index) {
-  if (g.on_the_v_diagonal(v_point_index))
-    projections_f.emplace(v_point_index);
-  else
-    kd_t.insert(g.get_v_point(v_point_index));
-}
-
-inline int Neighbors_finder::pull_near(int u_point_index) {
-  int tmp;
-  int c = g.corresponding_point_in_v(u_point_index);
-  if (g.on_the_u_diagonal(u_point_index) && !projections_f.empty()) {
-    // Any pair of projection is at distance 0
-    tmp = *projections_f.cbegin();
-    projections_f.erase(tmp);
-  } else if (projections_f.count(c) && (g.distance(u_point_index, c) <= r)) {
-    // Is the query point near to its projection ?
-    tmp = c;
-    projections_f.erase(tmp);
-  } else {
-    // Is the query point near to a V point in the plane ?
-    Internal_point u_point = g.get_u_point(u_point_index);
-    auto neighbor = kd_t.search_any_point(Square_query{u_point, r});
-    if (!neighbor)
-      return null_point_index();
-    tmp = neighbor->point_index;
-    auto point = g.get_v_point(tmp);
-    int idx = point.point_index;
-    kd_t.remove(point, [idx](Internal_point const&p){return p.point_index == idx;});
-  }
-  return tmp;
-}
-
-inline std::vector<int> Neighbors_finder::pull_all_near(int u_point_index) {
-  std::vector<int> all_pull;
-  int last_pull = pull_near(u_point_index);
-  while (last_pull != null_point_index()) {
-    all_pull.emplace_back(last_pull);
-    last_pull = pull_near(u_point_index);
-  }
-  return all_pull;
-}
-
-inline Layered_neighbors_finder::Layered_neighbors_finder(const Persistence_graph& g, double r) :
-    g(g), r(r), neighbors_finder() { }
-
-inline void Layered_neighbors_finder::add(int v_point_index, int vlayer) {
-  for (int l = neighbors_finder.size(); l <= vlayer; l++)
-    neighbors_finder.emplace_back(std::unique_ptr<Neighbors_finder>(new Neighbors_finder(g, r)));
-  neighbors_finder.at(vlayer)->add(v_point_index);
-}
-
-inline int Layered_neighbors_finder::pull_near(int u_point_index, int vlayer) {
-  if (static_cast<int> (neighbors_finder.size()) <= vlayer)
-    return null_point_index();
-  return neighbors_finder.at(vlayer)->pull_near(u_point_index);
-}
-
-inline int Layered_neighbors_finder::vlayers_number() const {
-  return static_cast<int> (neighbors_finder.size());
-}
-
-}  // namespace persistence_diagram
-
-}  // namespace Gudhi
-
-#endif  // NEIGHBORS_FINDER_H_