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Diffstat (limited to 'include/gudhi/Neighbors_finder.h')
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diff --git a/include/gudhi/Neighbors_finder.h b/include/gudhi/Neighbors_finder.h new file mode 100644 index 00000000..bdc47578 --- /dev/null +++ b/include/gudhi/Neighbors_finder.h @@ -0,0 +1,192 @@ +/* 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> + +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::abs(p.x()-c.x())<=size && 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_ |