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+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#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
+#include <cmath> // for std::abs
+
+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_