diff options
9 files changed, 2582 insertions, 213 deletions
diff --git a/src/Witness_complex/example/CMakeLists.txt b/src/Witness_complex/example/CMakeLists.txt index 77f95c79..23919b4a 100644 --- a/src/Witness_complex/example/CMakeLists.txt +++ b/src/Witness_complex/example/CMakeLists.txt @@ -87,8 +87,19 @@ if(CGAL_FOUND) target_link_libraries(witness_complex_sphere ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) add_test(witness_complex_sphere ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_sphere ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) add_executable ( relaxed_witness_complex_sphere relaxed_witness_complex_sphere.cpp ) - target_link_libraries(relaxed_witness_complex_sphere ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) - add_test(relaxed_witness_complex_sphere ${CMAKE_CURRENT_BINARY_DIR}/relaxed_witness_complex_sphere ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) + add_test(witness_complex_sphere ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_sphere ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) + add_executable ( witness_complex_protected_delaunay witness_complex_protected_delaunay.cpp ) + target_link_libraries(witness_complex_protected_delaunay ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) + add_test(witness_complex_protected_delaunay ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_protected_delaunay ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) + add_executable ( witness_complex_cubic_systems witness_complex_cubic_systems.cpp ) + target_link_libraries(witness_complex_cubic_systems ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) + add_test(witness_complex_cubic_systems ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_cubic_systems ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) + add_executable ( witness_complex_cube witness_complex_cube.cpp ) + target_link_libraries(witness_complex_cube ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) + add_test(witness_complex_cube ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_cube ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) + add_executable ( witness_complex_epsilon witness_complex_epsilon.cpp ) + target_link_libraries(witness_complex_epsilon ${Boost_SYSTEM_LIBRARY} ${CGAL_LIBRARY}) + add_test(witness_complex_epsilon ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_epsilon ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100) else() message(WARNING "Eigen3 not found. Version 3.1.0 is required for Alpha shapes feature.") endif() diff --git a/src/Witness_complex/example/Torus_distance.h b/src/Witness_complex/example/Torus_distance.h new file mode 100644 index 00000000..5ae127df --- /dev/null +++ b/src/Witness_complex/example/Torus_distance.h @@ -0,0 +1,209 @@ +#ifndef GUDHI_TORUS_DISTANCE_H_ +#define GUDHI_TORUS_DISTANCE_H_ + +#include <math.h> + +#include <CGAL/Search_traits.h> +#include <CGAL/Search_traits_adapter.h> +#include <CGAL/Epick_d.h> + +typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; +typedef K::Point_d Point_d; +typedef K::FT FT; +typedef CGAL::Search_traits< + FT, Point_d, + typename K::Cartesian_const_iterator_d, + typename K::Construct_cartesian_const_iterator_d> Traits_base; + +/** + * \brief Class of distance in a flat torus in dimension D + * + */ +class Torus_distance { + +public: + typedef K::FT FT; + typedef K::Point_d Point_d; + typedef Point_d Query_item; + typedef typename CGAL::Dynamic_dimension_tag D; + + double box_length = 2; + + FT transformed_distance(Query_item q, Point_d p) const + { + FT distance = FT(0); + FT coord = FT(0); + //std::cout << "Hello skitty!\n"; + typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); + typename K::Cartesian_const_iterator_d qit = construct_it(q), + qe = construct_it(q,1), pit = construct_it(p); + for(; qit != qe; qit++, pit++) + { + coord = sqrt(((*qit)-(*pit))*((*qit)-(*pit))); + if (coord*coord <= (box_length-coord)*(box_length-coord)) + distance += coord*coord; + else + distance += (box_length-coord)*(box_length-coord); + } + return distance; + } + + FT min_distance_to_rectangle(const Query_item& q, + const CGAL::Kd_tree_rectangle<FT,D>& r) const { + FT distance = FT(0); + FT dist1, dist2; + typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); + typename K::Cartesian_const_iterator_d qit = construct_it(q), + qe = construct_it(q,1); + for(unsigned int i = 0;qit != qe; i++, qit++) + { + if((*qit) < r.min_coord(i)) + { + dist1 = (r.min_coord(i)-(*qit)); + dist2 = (box_length - r.max_coord(i)+(*qit)); + if (dist1 < dist2) + distance += dist1*dist1; + else + distance += dist2*dist2; + } + else if ((*qit) > r.max_coord(i)) + { + dist1 = (box_length - (*qit)+r.min_coord(i)); + dist2 = ((*qit) - r.max_coord(i)); + if (dist1 < dist2) + distance += dist1*dist1; + else + distance += dist2*dist2; + } + } + return distance; + } + + FT min_distance_to_rectangle(const Query_item& q, + const CGAL::Kd_tree_rectangle<FT,D>& r, + std::vector<FT>& dists) const { + FT distance = FT(0); + FT dist1, dist2; + typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); + typename K::Cartesian_const_iterator_d qit = construct_it(q), + qe = construct_it(q,1); + //std::cout << r.max_coord(0) << std::endl; + for(unsigned int i = 0;qit != qe; i++, qit++) + { + if((*qit) < r.min_coord(i)) + { + dist1 = (r.min_coord(i)-(*qit)); + dist2 = (box_length - r.max_coord(i)+(*qit)); + if (dist1 < dist2) + { + dists[i] = dist1; + distance += dist1*dist1; + } + else + { + dists[i] = dist2; + distance += dist2*dist2; + //std::cout << "Good stuff1\n"; + } + } + else if ((*qit) > r.max_coord(i)) + { + dist1 = (box_length - (*qit)+r.min_coord(i)); + dist2 = ((*qit) - r.max_coord(i)); + if (dist1 < dist2) + { + dists[i] = dist1; + distance += dist1*dist1; + //std::cout << "Good stuff2\n"; + } + else + { + dists[i] = dist2; + distance += dist2*dist2; + } + } + }; + return distance; + } + + FT max_distance_to_rectangle(const Query_item& q, + const CGAL::Kd_tree_rectangle<FT,D>& r) const { + FT distance=FT(0); + typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); + typename K::Cartesian_const_iterator_d qit = construct_it(q), + qe = construct_it(q,1); + for(unsigned int i = 0;qit != qe; i++, qit++) + { + if (box_length <= (r.min_coord(i)+r.max_coord(i))) + if ((r.max_coord(i)+r.min_coord(i)-box_length)/FT(2.0) <= (*qit) && + (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) + distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); + else + distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); + else + if ((box_length-r.max_coord(i)-r.min_coord(i))/FT(2.0) <= (*qit) || + (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) + distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); + else + distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); + } + return distance; + } + + + FT max_distance_to_rectangle(const Query_item& q, + const CGAL::Kd_tree_rectangle<FT,D>& r, + std::vector<FT>& dists) const { + FT distance=FT(0); + typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); + typename K::Cartesian_const_iterator_d qit = construct_it(q), + qe = construct_it(q,1); + for(unsigned int i = 0;qit != qe; i++, qit++) + { + if (box_length <= (r.min_coord(i)+r.max_coord(i))) + if ((r.max_coord(i)+r.min_coord(i)-box_length)/FT(2.0) <= (*qit) && + (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) + { + dists[i] = r.max_coord(i)-(*qit); + distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); + } + else + { + dists[i] = sqrt(((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i))); + distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); + } + else + if ((box_length-r.max_coord(i)-r.min_coord(i))/FT(2.0) <= (*qit) || + (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) + { + dists[i] = sqrt((r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit))); + distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); + + } + else + { + dists[i] = (*qit)-r.min_coord(i); + distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); + } + } + return distance; + } + + inline FT new_distance(FT dist, FT old_off, FT new_off, + int ) const { + + FT new_dist = dist + (new_off*new_off - old_off*old_off); + return new_dist; + } + + inline FT transformed_distance(FT d) const { + return d*d; + } + + inline FT inverse_of_transformed_distance(FT d) const { + return sqrt(d); + } + +}; + +#endif diff --git a/src/Witness_complex/example/witness_complex_cube.cpp b/src/Witness_complex/example/witness_complex_cube.cpp new file mode 100644 index 00000000..7545f156 --- /dev/null +++ b/src/Witness_complex/example/witness_complex_cube.cpp @@ -0,0 +1,541 @@ +/* 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(s): Siargey Kachanovich + * + * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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/>. + */ + +#include <iostream> +#include <fstream> +#include <ctime> +#include <utility> +#include <algorithm> +#include <set> +#include <iterator> +#include <chrono> + +#include <sys/types.h> +#include <sys/stat.h> +//#include <stdlib.h> + +//#include "gudhi/graph_simplicial_complex.h" +#include "gudhi/Witness_complex.h" +#include "gudhi/reader_utils.h" +#include "Torus_distance.h" + +#include <CGAL/Cartesian_d.h> +#include <CGAL/Search_traits.h> +#include <CGAL/Search_traits_adapter.h> +#include <CGAL/property_map.h> +#include <CGAL/Epick_d.h> +#include <CGAL/Orthogonal_k_neighbor_search.h> +#include <CGAL/Kd_tree.h> +#include <CGAL/Euclidean_distance.h> +#include <CGAL/Kernel_d/Sphere_d.h> + +#include <CGAL/Kernel_d/Vector_d.h> +#include <CGAL/point_generators_d.h> +#include <CGAL/constructions_d.h> +#include <CGAL/Fuzzy_sphere.h> +#include <CGAL/Random.h> +#include <CGAL/Delaunay_triangulation.h> + + +#include <boost/tuple/tuple.hpp> +#include <boost/iterator/zip_iterator.hpp> +#include <boost/iterator/counting_iterator.hpp> +#include <boost/range/iterator_range.hpp> + +using namespace Gudhi; +//using namespace boost::filesystem; + +typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; +typedef K::Point_d Point_d; +//typedef CGAL::Cartesian_d<double> K; +//typedef CGAL::Point_d<K> Point_d; +typedef K::FT FT; +typedef CGAL::Search_traits< + FT, Point_d, + typename K::Cartesian_const_iterator_d, + typename K::Construct_cartesian_const_iterator_d> Traits_base; +typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; + + +typedef std::vector< Vertex_handle > typeVectorVertex; + +//typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; +//typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; + +typedef CGAL::Search_traits_adapter< + std::ptrdiff_t, Point_d*, Traits_base> STraits; +//typedef K TreeTraits; +//typedef CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance > Euclidean_adapter; +//typedef CGAL::Kd_tree<STraits> Kd_tree; +typedef CGAL::Orthogonal_k_neighbor_search<STraits, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>> K_neighbor_search; +typedef K_neighbor_search::Tree Tree; +typedef K_neighbor_search::Distance Distance; +typedef K_neighbor_search::iterator KNS_iterator; +typedef K_neighbor_search::iterator KNS_range; +typedef boost::container::flat_map<int, int> Point_etiquette_map; +typedef CGAL::Kd_tree<STraits> Tree2; + +typedef CGAL::Fuzzy_sphere<STraits> Fuzzy_sphere; + +typedef std::vector<Point_d> Point_Vector; + +//typedef K::Equal_d Equal_d; +//typedef CGAL::Random_points_in_cube_d<CGAL::Point_d<CGAL::Cartesian_d<FT> > > Random_cube_iterator; +typedef CGAL::Random_points_in_cube_d<Point_d> Random_cube_iterator; +typedef CGAL::Random_points_in_ball_d<Point_d> Random_point_iterator; + +typedef CGAL::Delaunay_triangulation<K> Delaunay_triangulation; +typedef Delaunay_triangulation::Facet Facet; +typedef CGAL::Sphere_d<K> Sphere_d; + +bool toric=false; + + +/** + * \brief Customized version of read_points + * which takes into account a possible nbP first line + * + */ +inline void +read_points_cust ( std::string file_name , Point_Vector & points) +{ + std::ifstream in_file (file_name.c_str(),std::ios::in); + if(!in_file.is_open()) + { + std::cerr << "Unable to open file " << file_name << std::endl; + return; + } + std::string line; + double x; + while( getline ( in_file , line ) ) + { + std::vector< double > point; + std::istringstream iss( line ); + while(iss >> x) { point.push_back(x); } + Point_d p(point.begin(), point.end()); + if (point.size() != 1) + points.push_back(p); + } + in_file.close(); +} + +void generate_points_grid(Point_Vector& W, int width, int D) +{ + int nb_points = 1; + for (int i = 0; i < D; ++i) + nb_points *= width; + for (int i = 0; i < nb_points; ++i) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(0.01*(cell_i%width)); + cell_i /= width; + } + W.push_back(point); + } +} + +void generate_points_random_box(Point_Vector& W, int nbP, int dim) +{ + /* + Random_cube_iterator rp(dim, 1); + for (int i = 0; i < nbP; i++) + { + std::vector<double> point; + for (auto it = rp->cartesian_begin(); it != rp->cartesian_end(); ++it) + point.push_back(*it); + W.push_back(Point_d(point)); + rp++; + } + */ + Random_cube_iterator rp(dim, 1.0); + for (int i = 0; i < nbP; i++) + { + W.push_back(*rp++); + } +} + + +void write_wl( std::string file_name, std::vector< std::vector <int> > & WL) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : WL) + { + for (auto l: w) + ofs << l << " "; + ofs << "\n"; + } + ofs.close(); +} + + +void write_points( std::string file_name, std::vector< Point_d > & points) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : points) + { + for (auto it = w.cartesian_begin(); it != w.cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + } + ofs.close(); +} + +void write_edges(std::string file_name, Witness_complex<>& witness_complex, Point_Vector& landmarks) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto u: witness_complex.complex_vertex_range()) + for (auto v: witness_complex.complex_vertex_range()) + { + typeVectorVertex edge = {u,v}; + if (u < v && witness_complex.find(edge) != witness_complex.null_simplex()) + { + for (auto it = landmarks[u].cartesian_begin(); it != landmarks[u].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + for (auto it = landmarks[v].cartesian_begin(); it != landmarks[v].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n\n\n"; + } + } + ofs.close(); +} + + +void insert_delaunay_landmark_with_copies(Point_Vector& W, int chosen_landmark, std::vector<int>& landmarks_ind, Delaunay_triangulation& delaunay, int& landmark_count) +{ + delaunay.insert(W[chosen_landmark]); + landmarks_ind.push_back(chosen_landmark); + landmark_count++; +} + +bool is_violating_protection(Point_d& p, Delaunay_triangulation& t, int D, FT delta) +{ + Euclidean_distance ed; + Delaunay_triangulation::Vertex_handle v; + Delaunay_triangulation::Face f(t.current_dimension()); + Delaunay_triangulation::Facet ft; + Delaunay_triangulation::Full_cell_handle c; + Delaunay_triangulation::Locate_type lt; + c = t.locate(p, lt, f, ft, v); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + { + std::vector<Point_d> vertices; + for (auto v_it = fc_it->vertices_begin(); v_it != fc_it->vertices_end(); ++v_it) + vertices.push_back((*v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, p); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 >= r*r && dist2 <= (r+delta)*(r+delta)) + return true; + } + return false; +} + +bool triangulation_is_protected(Delaunay_triangulation& t, FT delta) +{ + Euclidean_distance ed; + int D = t.current_dimension(); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + for (auto v_it = t.vertices_begin(); v_it != t.vertices_end(); ++v_it) + { + //check if vertex belongs to the face + bool belongs = false; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + if (v_it == *fc_v_it) + { + belongs = true; + break; + } + if (!belongs) + { + std::vector<Point_d> vertices; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + vertices.push_back((*fc_v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, v_it->point()); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 <= (r+delta)*(r+delta)) + return false; + } + } + return true; +} + +void fill_landmarks(Point_Vector& W, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + for (int j = 0; j < landmarks_ind.size(); ++j) + landmarks.push_back(W[landmarks_ind[j]][l]); +} + +void landmark_choice_by_delaunay(Point_Vector& W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind, FT delta) +{ + int D = W[0].size(); + Delaunay_triangulation t(D); + CGAL::Random rand; + int chosen_landmark; + int landmark_count = 0; + for (int i = 0; i <= D+1; ++i) + { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + insert_delaunay_landmark_with_copies(W, chosen_landmark, landmarks_ind, t, landmark_count); + } + while (landmark_count < nbL) + { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + // If no conflicts then insert in every copy of T^3 + if (!is_violating_protection(W[chosen_landmark], t, D, delta)) + insert_delaunay_landmark_with_copies(W, chosen_landmark, landmarks_ind, t, landmark_count); + } +} + + +void landmark_choice_protected_delaunay(Point_Vector& W, int nbP, Point_Vector& landmarks, std::vector<int>& landmarks_ind, FT delta) +{ + int D = W[0].size(); + Torus_distance td; + Euclidean_distance ed; + Delaunay_triangulation t(D); + CGAL::Random rand; + int landmark_count = 0; + std::list<int> index_list; + // shuffle the list of indexes (via a vector) + { + std::vector<int> temp_vector; + for (int i = 0; i < nbP; ++i) + temp_vector.push_back(i); + unsigned seed = std::chrono::system_clock::now().time_since_epoch().count(); + std::shuffle(temp_vector.begin(), temp_vector.end(), std::default_random_engine(seed)); + for (std::vector<int>::iterator it = temp_vector.begin(); it != temp_vector.end(); ++it) + index_list.push_front(*it); + } + // add the first D+1 vertices to form one non-empty cell + for (int i = 0; i <= D+1; ++i) + { + insert_delaunay_landmark_with_copies(W, index_list.front(), landmarks_ind, t, landmark_count); + index_list.pop_front(); + } + // add other vertices if they don't violate protection + std::list<int>::iterator list_it = index_list.begin(); + while (list_it != index_list.end()) + if (!is_violating_protection(W[*list_it], t, D, delta)) + { + // If no conflicts then insert in every copy of T^3 + insert_delaunay_landmark_with_copies(W, *list_it, landmarks_ind, t, landmark_count); + index_list.erase(list_it); + list_it = index_list.begin(); + } + else + list_it++; + fill_landmark_copies(W, landmarks, landmarks_ind); +} + + +int landmark_perturbation(Point_Vector &W, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + //******************** Preface: origin point + int D = W[0].size(); + std::vector<FT> orig_vector; + for (int i=0; i<D; i++) + orig_vector.push_back(0); + Point_d origin(orig_vector); + + //******************** Constructing a WL matrix + int nbP = W.size(); + Euclidean_distance ed; + FT lambda = ed.transformed_distance(landmarks[0],landmarks[1]); + std::vector<Point_d> landmarks_ext; + int nb_cells = 1; + for (int i = 0; i < D; ++i) + nb_cells *= 3; + for (int i = 0; i < nb_cells; ++i) + for (int k = 0; k < nbL; ++k) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1.0)); + cell_i /= 3; + } + landmarks_ext.push_back(point); + } + write_points("landmarks/initial_landmarks",landmarks_ext); + STraits traits(&(landmarks_ext[0])); + std::vector< std::vector <int> > WL(nbP); + + //********************** Neighbor search in a Kd tree + Tree L(boost::counting_iterator<std::ptrdiff_t>(0), + boost::counting_iterator<std::ptrdiff_t>(nb_cells*nbL), + typename Tree::Splitter(), + traits); + std::cout << "Enter (D+1) nearest landmarks\n"; + for (int i = 0; i < nbP; i++) + { + Point_d& w = W[i]; + ////Search D+1 nearest neighbours from the tree of landmarks L + K_neighbor_search search(L, w, D+1, FT(0), true, + CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>(&(landmarks_ext[0])) ); + for(K_neighbor_search::iterator it = search.begin(); it != search.end(); ++it) + { + if (std::find(WL[i].begin(), WL[i].end(), (it->first)%nbL) == WL[i].end()) + WL[i].push_back((it->first)%nbL); + } + if (i == landmarks_ind[WL[i][0]]) + { + FT dist = ed.transformed_distance(W[i], landmarks[WL[i][1]]); + if (dist < lambda) + lambda = dist; + } + } + std::string out_file = "wl_result"; + write_wl(out_file,WL); + + //******************** Constructng a witness complex + std::cout << "Entered witness complex construction\n"; + Witness_complex<> witnessComplex; + witnessComplex.setNbL(nbL); + witnessComplex.witness_complex(WL); + + //******************** Making a set of bad link landmarks + std::cout << "Entered bad links\n"; + std::set< int > perturbL; + int count_badlinks = 0; + //std::cout << "Bad links around "; + std::vector< int > count_bad(D); + std::vector< int > count_good(D); + for (auto u: witnessComplex.complex_vertex_range()) + { + if (!witnessComplex.has_good_link(u, count_bad, count_good)) + { + count_badlinks++; + Point_d& l = landmarks[u]; + Fuzzy_sphere fs(l, sqrt(lambda)*3, 0, traits); + std::vector<int> curr_perturb; + L.search(std::insert_iterator<std::vector<int>>(curr_perturb,curr_perturb.begin()),fs); + for (int i: curr_perturb) + perturbL.insert(i%nbL); + } + } + for (unsigned int i = 0; i != count_good.size(); i++) + if (count_good[i] != 0) + std::cout << "count_good[" << i << "] = " << count_good[i] << std::endl; + for (unsigned int i = 0; i != count_bad.size(); i++) + if (count_bad[i] != 0) + std::cout << "count_bad[" << i << "] = " << count_bad[i] << std::endl; + std::cout << "\nBad links total: " << count_badlinks << " Points to perturb: " << perturbL.size() << std::endl; + + //*********************** Perturb bad link landmarks + for (auto u: perturbL) + { + Random_point_iterator rp(D,sqrt(lambda)/8); + std::vector<FT> point; + for (int i = 0; i < D; i++) + { + while (K().squared_distance_d_object()(*rp,origin) < lambda/256) + rp++; + FT coord = landmarks[u][i] + (*rp)[i]; + if (coord > 1) + point.push_back(coord-1); + else if (coord < -1) + point.push_back(coord+1); + else + point.push_back(coord); + } + landmarks[u] = Point_d(point); + } + std::cout << "lambda=" << lambda << std::endl; + char buffer[100]; + int i = sprintf(buffer,"stree_result.txt"); + + if (i >= 0) + { + std::string out_file = (std::string)buffer; + std::ofstream ofs (out_file, std::ofstream::out); + witnessComplex.st_to_file(ofs); + ofs.close(); + } + write_edges("landmarks/edges", witnessComplex, landmarks); + return count_badlinks; +} + + +int main (int argc, char * const argv[]) +{ + if (argc != 5) + { + std::cerr << "Usage: " << argv[0] + << " nbP nbL dim delta\n"; + return 0; + } + int nbP = atoi(argv[1]); + int nbL = atoi(argv[2]); + int dim = atoi(argv[3]); + FT delta = atof(argv[4]); + + std::cout << "Let the carnage begin!\n"; + Point_Vector point_vector; + generate_points_random_box(point_vector, nbP, dim); + Point_Vector L; + std::vector<int> chosen_landmarks; + bool ok=false; + while (!ok) + { + ok = true; + L = {}; + chosen_landmarks = {}; + //landmark_choice_by_delaunay(point_vector, nbP, nbL, L, chosen_landmarks, delta); + landmark_choice_protected_delaunay(point_vector, nbP, L, chosen_landmarks, delta); + nbL = chosen_landmarks.size(); + std::cout << "Number of landmarks is " << nbL << std::endl; + //int width = (int)pow(nbL, 1.0/dim); landmark_choice_bcc(point_vector, nbP, width, L, chosen_landmarks); + for (auto i: chosen_landmarks) + { + ok = ok && (std::count(chosen_landmarks.begin(),chosen_landmarks.end(),i) == 1); + if (!ok) break; + } + + } + int bl = nbL, curr_min = bl; + write_points("landmarks/initial_pointset",point_vector); + //write_points("landmarks/initial_landmarks",L); + //for (int i = 0; i < 1; i++) + for (int i = 0; bl > 0; i++) + { + std::cout << "========== Start iteration " << i << "== curr_min(" << curr_min << ")========\n"; + bl=landmark_perturbation(point_vector, nbL, L, chosen_landmarks); + if (bl < curr_min) + curr_min=bl; + write_points("landmarks/landmarks0",L); + } + +} diff --git a/src/Witness_complex/example/witness_complex_cubic_systems.cpp b/src/Witness_complex/example/witness_complex_cubic_systems.cpp new file mode 100644 index 00000000..2f4ee1cb --- /dev/null +++ b/src/Witness_complex/example/witness_complex_cubic_systems.cpp @@ -0,0 +1,547 @@ +/* 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(s): Siargey Kachanovich + * + * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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/>. + */ + +#include <iostream> +#include <fstream> +#include <ctime> +#include <utility> +#include <algorithm> +#include <set> +#include <iterator> + +#include <sys/types.h> +#include <sys/stat.h> +#include <unistd.h> + +//#include "gudhi/graph_simplicial_complex.h" +#include "gudhi/Witness_complex.h" +#include "gudhi/reader_utils.h" +#include "Torus_distance.h" + +#include <CGAL/Cartesian_d.h> +#include <CGAL/Search_traits.h> +#include <CGAL/Search_traits_adapter.h> +#include <CGAL/property_map.h> +#include <CGAL/Epick_d.h> +#include <CGAL/Orthogonal_k_neighbor_search.h> +#include <CGAL/Kd_tree.h> +#include <CGAL/Euclidean_distance.h> +#include <CGAL/Kernel_d/Sphere_d.h> + +#include <CGAL/Kernel_d/Vector_d.h> +#include <CGAL/point_generators_d.h> +#include <CGAL/constructions_d.h> +#include <CGAL/Fuzzy_sphere.h> +#include <CGAL/Random.h> +#include <CGAL/Delaunay_triangulation.h> + + +#include <boost/tuple/tuple.hpp> +#include <boost/iterator/zip_iterator.hpp> +#include <boost/iterator/counting_iterator.hpp> +#include <boost/range/iterator_range.hpp> + +using namespace Gudhi; +//using namespace boost::filesystem; + +typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; +typedef K::Point_d Point_d; +//typedef CGAL::Cartesian_d<double> K; +//typedef CGAL::Point_d<K> Point_d; +typedef K::FT FT; +typedef CGAL::Search_traits< + FT, Point_d, + typename K::Cartesian_const_iterator_d, + typename K::Construct_cartesian_const_iterator_d> Traits_base; +typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; + + +typedef std::vector< Vertex_handle > typeVectorVertex; + +//typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; +//typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; + +typedef CGAL::Search_traits_adapter< + std::ptrdiff_t, Point_d*, Traits_base> STraits; +//typedef K TreeTraits; +//typedef CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance > Euclidean_adapter; +//typedef CGAL::Kd_tree<STraits> Kd_tree; +typedef CGAL::Orthogonal_k_neighbor_search<STraits, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>> K_neighbor_search; +typedef K_neighbor_search::Tree Tree; +typedef K_neighbor_search::Distance Distance; +typedef K_neighbor_search::iterator KNS_iterator; +typedef K_neighbor_search::iterator KNS_range; +typedef boost::container::flat_map<int, int> Point_etiquette_map; +typedef CGAL::Kd_tree<STraits> Tree2; + +typedef CGAL::Fuzzy_sphere<STraits> Fuzzy_sphere; + +typedef std::vector<Point_d> Point_Vector; + +//typedef K::Equal_d Equal_d; +//typedef CGAL::Random_points_in_cube_d<CGAL::Point_d<CGAL::Cartesian_d<FT> > > Random_cube_iterator; +typedef CGAL::Random_points_in_cube_d<Point_d> Random_cube_iterator; +typedef CGAL::Random_points_in_ball_d<Point_d> Random_point_iterator; + +typedef CGAL::Delaunay_triangulation<K> Delaunay_triangulation; +typedef Delaunay_triangulation::Facet Facet; +typedef CGAL::Sphere_d<K> Sphere_d; + +bool toric=false; + + +/** + * \brief Customized version of read_points + * which takes into account a possible nbP first line + * + */ +inline void +read_points_cust ( std::string file_name , Point_Vector & points) +{ + std::ifstream in_file (file_name.c_str(),std::ios::in); + if(!in_file.is_open()) + { + std::cerr << "Unable to open file " << file_name << std::endl; + return; + } + std::string line; + double x; + while( getline ( in_file , line ) ) + { + std::vector< double > point; + std::istringstream iss( line ); + while(iss >> x) { point.push_back(x); } + Point_d p(point.begin(), point.end()); + if (point.size() != 1) + points.push_back(p); + } + in_file.close(); +} + +void generate_points_random_box(Point_Vector& W, int nbP, int dim) +{ + /* + Random_cube_iterator rp(dim, 1); + for (int i = 0; i < nbP; i++) + { + std::vector<double> point; + for (auto it = rp->cartesian_begin(); it != rp->cartesian_end(); ++it) + point.push_back(*it); + W.push_back(Point_d(point)); + rp++; + } + */ + Random_cube_iterator rp(dim, 1.0); + for (int i = 0; i < nbP; i++) + { + W.push_back(*rp++); + } +} + + +void write_wl( std::string file_name, std::vector< std::vector <int> > & WL) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : WL) + { + for (auto l: w) + ofs << l << " "; + ofs << "\n"; + } + ofs.close(); +} + + +void write_points( std::string file_name, std::vector< Point_d > & points) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : points) + { + for (auto it = w.cartesian_begin(); it != w.cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + } + ofs.close(); +} + +void write_edges(std::string file_name, Witness_complex<>& witness_complex, Point_Vector& landmarks) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto u: witness_complex.complex_vertex_range()) + for (auto v: witness_complex.complex_vertex_range()) + { + typeVectorVertex edge = {u,v}; + if (u < v && witness_complex.find(edge) != witness_complex.null_simplex()) + { + for (auto it = landmarks[u].cartesian_begin(); it != landmarks[u].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + for (auto it = landmarks[v].cartesian_begin(); it != landmarks[v].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n\n\n"; + } + } + ofs.close(); +} + + +/** Function that chooses landmarks from W and place it in the kd-tree L. + * Note: nbL hould be removed if the code moves to Witness_complex + */ +void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + std::cout << "Enter landmark choice to kd tree\n"; + int chosen_landmark; + Point_d* p; + CGAL::Random rand; + for (int i = 0; i < nbL; i++) + { + // while (!res.second) + // { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + //rand++; + //std::cout << "Chose " << chosen_landmark << std::endl; + p = &W[chosen_landmark]; + //L_i.emplace(chosen_landmark,i); + // } + landmarks.push_back(*p); + landmarks_ind.push_back(chosen_landmark); + //std::cout << "Added landmark " << chosen_landmark << std::endl; + } + } + +void aux_fill_grid(Point_Vector& W, int& width, Point_Vector& landmarks, std::vector<int>& landmarks_ind, std::vector<bool> & curr_pattern) +{ + int D = W[0].size(); + int nb_points = 1; + for (int i = 0; i < D; ++i) + nb_points *= width; + for (int i = 0; i < nb_points; ++i) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + if (curr_pattern[l]) + point.push_back(-1.0+(2.0/width)*(cell_i%width)+(1.0/width)); + else + point.push_back(-1.0+(2.0/width)*(cell_i%width)); + cell_i /= width; + } + landmarks.push_back(Point_d(point)); + landmarks_ind.push_back(0);//landmarks_ind.push_back(W.size()); + //std::cout << "Added point " << W.size() << std::endl;; + //W.push_back(Point_d(point)); + } +} + +void aux_put_halves(Point_Vector& W, int& width, Point_Vector& landmarks, std::vector<int>& landmarks_ind, std::vector<bool>& curr_pattern, std::vector<bool>::iterator curr_pattern_it, std::vector<bool>::iterator bool_it, std::vector<bool>::iterator bool_end) +{ + if (curr_pattern_it != curr_pattern.end()) + { + if (bool_it != bool_end) + { + *curr_pattern_it = false; + aux_put_halves(W, width, landmarks, landmarks_ind, curr_pattern, curr_pattern_it+1, bool_it, bool_end); + *curr_pattern_it = true; + aux_put_halves(W, width, landmarks, landmarks_ind, curr_pattern, curr_pattern_it+1, bool_it+1, bool_end); + } + } + else + if (*bool_it) + { + std::cout << "Filling the pattern "; + for (bool b: curr_pattern) + if (b) std::cout << '1'; + else std::cout << '0'; + std::cout << "\n"; + aux_fill_grid(W, width, landmarks, landmarks_ind, curr_pattern); + } +} + +void landmark_choice_cs(Point_Vector& W, int width, Point_Vector& landmarks, std::vector<int>& landmarks_ind, std::vector<bool>& face_centers) +{ + std::cout << "Enter landmark choice to kd tree\n"; + //int chosen_landmark; + CGAL::Random rand; + //To speed things up check the last true in the code and put it as the finishing condition + unsigned last_true = face_centers.size()-1; + while (!face_centers[last_true] && last_true != 0) + last_true--; + //Recursive procedure to understand where we put +1/2 in centers' coordinates + std::vector<bool> curr_pattern(W[0].size(), false); + aux_put_halves(W, width, landmarks, landmarks_ind, curr_pattern, curr_pattern.begin(), face_centers.begin(), face_centers.begin()+(last_true+1)); + std::cout << "The number of landmarks is: " << landmarks.size() << std::endl; + + } + +int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + //******************** Preface: origin point + int D = W[0].size(); + std::vector<FT> orig_vector; + for (int i=0; i<D; i++) + orig_vector.push_back(0); + Point_d origin(orig_vector); + + //******************** Constructing a WL matrix + int nbP = W.size(); + int nbL = landmarks.size(); + Euclidean_distance ed; + FT lambda = ed.transformed_distance(landmarks[0],landmarks[1]); + std::vector<Point_d> landmarks_ext; + int nb_cells = 1; + for (int i = 0; i < D; ++i) + nb_cells *= 3; + for (int i = 0; i < nb_cells; ++i) + for (int k = 0; k < nbL; ++k) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1.0)); + cell_i /= 3; + } + landmarks_ext.push_back(point); + } + write_points("landmarks/initial_landmarks",landmarks_ext); + STraits traits(&(landmarks_ext[0])); + std::vector< std::vector <int> > WL(nbP); + + //********************** Neighbor search in a Kd tree + Tree L(boost::counting_iterator<std::ptrdiff_t>(0), + boost::counting_iterator<std::ptrdiff_t>(nb_cells*nbL), + typename Tree::Splitter(), + traits); + std::cout << "Enter (D+1) nearest landmarks\n"; + for (int i = 0; i < nbP; i++) + { + Point_d& w = W[i]; + ////Search D+1 nearest neighbours from the tree of landmarks L + K_neighbor_search search(L, w, D+1, FT(0), true, + CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>(&(landmarks_ext[0])) ); + for(K_neighbor_search::iterator it = search.begin(); it != search.end(); ++it) + { + if (std::find(WL[i].begin(), WL[i].end(), (it->first)%nbL) == WL[i].end()) + WL[i].push_back((it->first)%nbL); + } + if (i == landmarks_ind[WL[i][0]]) + { + FT dist = ed.transformed_distance(W[i], landmarks[WL[i][1]]); + if (dist < lambda) + lambda = dist; + } + } + std::string out_file = "wl_result"; + write_wl(out_file,WL); + + //******************** Constructng a witness complex + std::cout << "Entered witness complex construction\n"; + Witness_complex<> witnessComplex; + witnessComplex.setNbL(nbL); + witnessComplex.witness_complex(WL); + + //******************** Making a set of bad link landmarks + std::cout << "Entered bad links\n"; + std::set< int > perturbL; + int count_badlinks = 0; + //std::cout << "Bad links around "; + std::vector< int > count_bad(D); + std::vector< int > count_good(D); + for (auto u: witnessComplex.complex_vertex_range()) + { + if (!witnessComplex.has_good_link(u, count_bad, count_good, D)) + { + count_badlinks++; + Point_d& l = landmarks[u]; + Fuzzy_sphere fs(l, sqrt(lambda)*3, 0, traits); + std::vector<int> curr_perturb; + L.search(std::insert_iterator<std::vector<int>>(curr_perturb,curr_perturb.begin()),fs); + for (int i: curr_perturb) + perturbL.insert(i%nbL); + } + } + for (unsigned int i = 0; i != count_good.size(); i++) + if (count_good[i] != 0) + std::cout << "count_good[" << i << "] = " << count_good[i] << std::endl; + for (unsigned int i = 0; i != count_bad.size(); i++) + if (count_bad[i] != 0) + std::cout << "count_bad[" << i << "] = " << count_bad[i] << std::endl; + std::cout << "\nBad links total: " << count_badlinks << " Points to perturb: " << perturbL.size() << std::endl; + + //*********************** Perturb bad link landmarks + for (auto u: perturbL) + { + Random_point_iterator rp(D,sqrt(lambda)/8); + std::vector<FT> point; + for (int i = 0; i < D; i++) + { + while (K().squared_distance_d_object()(*rp,origin) < lambda/256) + rp++; + FT coord = landmarks[u][i] + (*rp)[i]; + if (coord > 1) + point.push_back(coord-1); + else if (coord < -1) + point.push_back(coord+1); + else + point.push_back(coord); + } + landmarks[u] = Point_d(point); + } + std::cout << "lambda=" << lambda << std::endl; + char buffer[100]; + int i = sprintf(buffer,"stree_result.txt"); + + if (i >= 0) + { + std::string out_file = (std::string)buffer; + std::ofstream ofs (out_file, std::ofstream::out); + witnessComplex.st_to_file(ofs); + ofs.close(); + } + write_edges("landmarks/edges", witnessComplex, landmarks); + return count_badlinks; +} + +void exaustive_search(Point_Vector& W, int width) +{ + int D = W[0].size()+1; + int nb_points = pow(2,D); + std::vector<bool> face_centers(D, false); + int bl = 0; //Bad links + std::vector<std::vector<bool>> good_patterns; + for (int i = 0; i < nb_points; ++i) + { + int cell_i = i; + for (int l = 0; l < D; ++l) + { + if (cell_i%2 == 0) + face_centers[l] = false; + else + face_centers[l] = true; + cell_i /= 2; + } + std::cout << "**Current pattern "; + for (bool b: face_centers) + if (b) std::cout << '1'; + else std::cout << '0'; + std::cout << "\n"; + Point_Vector landmarks; + std::vector<int> landmarks_ind; + Point_Vector W_copy(W); + landmark_choice_cs(W_copy, width, landmarks, landmarks_ind, face_centers); + if (landmarks.size() != 0) + { + bl = landmark_perturbation(W_copy, landmarks, landmarks_ind); + if ((1.0*bl)/landmarks.size() < 0.5) + good_patterns.push_back(face_centers); + } + } + std::cout << "The following patterns worked: "; + for (std::vector<bool> pattern : good_patterns) + { + std::cout << "["; + for (bool b: pattern) + if (b) std::cout << '1'; + else std::cout << '0'; + std::cout << "] "; + } + std::cout << "\n"; +} + +int main (int argc, char * const argv[]) +{ + unsigned nbP = atoi(argv[1]); + unsigned width = atoi(argv[2]); + unsigned dim = atoi(argv[3]); + std::string code = (std::string) argv[4]; + bool e_option = false; + int c; + if (argc != 5) + { + std::cerr << "Usage: " << argv[0] + << "witness_complex_cubic_systems nbP width dim code || witness_complex_systems -e nbP width dim\n" + << "where nbP stands for the number of witnesses, width for the width of the grid, dim for dimension " + << "and code is a sequence of (dim+1) symbols 0 and 1 representing if we take the centers of k-dimensional faces of the cubic system depending if it is 0 or 1." + << "-e stands for the 'exaustive' option"; + return 0; + } + while ((c = getopt (argc, argv, "e::")) != -1) + switch(c) + { + case 'e' : + e_option = true; + nbP = atoi(argv[2]); + width = atoi(argv[3]); + dim = atoi(argv[4]); + break; + default : + nbP = atoi(argv[1]); + width = atoi(argv[2]); + dim = atoi(argv[3]); + code = (std::string) argv[4]; + } + Point_Vector point_vector; + generate_points_random_box(point_vector, nbP, dim); + + // Exaustive search + if (e_option) + { + std::cout << "Start exaustive search!\n"; + exaustive_search(point_vector, width); + return 0; + } + // Search with a specific cubic system + std::vector<bool> face_centers; + if (code.size() != dim+1) + { + std::cerr << "The code should contain (dim+1) symbols"; + return 1; + } + for (char c: code) + if (c == '0') + face_centers.push_back(false); + else + face_centers.push_back(true); + std::cout << "Let the carnage begin!\n"; + Point_Vector L; + std::vector<int> chosen_landmarks; + + landmark_choice_cs(point_vector, width, L, chosen_landmarks, face_centers); + + int nbL = width; //!!!!!!!!!!!!! + int bl = nbL, curr_min = bl; + write_points("landmarks/initial_pointset",point_vector); + //write_points("landmarks/initial_landmarks",L); + //for (int i = 0; i < 1; i++) + for (int i = 0; bl > 0; i++) + { + std::cout << "========== Start iteration " << i << "== curr_min(" << curr_min << ")========\n"; + bl=landmark_perturbation(point_vector, L, chosen_landmarks); + if (bl < curr_min) + curr_min=bl; + write_points("landmarks/landmarks0",L); + } + +} diff --git a/src/Witness_complex/example/witness_complex_epsilon.cpp b/src/Witness_complex/example/witness_complex_epsilon.cpp new file mode 100644 index 00000000..d091bdb7 --- /dev/null +++ b/src/Witness_complex/example/witness_complex_epsilon.cpp @@ -0,0 +1,566 @@ +/* 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(s): Siargey Kachanovich + * + * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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/>. + */ + +#include <iostream> +#include <fstream> +#include <ctime> +#include <utility> +#include <algorithm> +#include <set> +#include <iterator> +#include <chrono> + +#include <sys/types.h> +#include <sys/stat.h> +//#include <stdlib.h> + +//#include "gudhi/graph_simplicial_complex.h" +#include "gudhi/Witness_complex.h" +#include "gudhi/reader_utils.h" +#include "Torus_distance.h" + +#include <CGAL/Cartesian_d.h> +#include <CGAL/Search_traits.h> +#include <CGAL/Search_traits_adapter.h> +#include <CGAL/property_map.h> +#include <CGAL/Epick_d.h> +#include <CGAL/Orthogonal_k_neighbor_search.h> +#include <CGAL/Kd_tree.h> +#include <CGAL/Euclidean_distance.h> +#include <CGAL/Kernel_d/Sphere_d.h> + +#include <CGAL/Kernel_d/Vector_d.h> +#include <CGAL/point_generators_d.h> +#include <CGAL/constructions_d.h> +#include <CGAL/Fuzzy_sphere.h> +#include <CGAL/Random.h> +#include <CGAL/Delaunay_triangulation.h> + + +#include <boost/tuple/tuple.hpp> +#include <boost/iterator/zip_iterator.hpp> +#include <boost/iterator/counting_iterator.hpp> +#include <boost/range/iterator_range.hpp> + +using namespace Gudhi; +//using namespace boost::filesystem; + +typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; +typedef K::Point_d Point_d; +//typedef CGAL::Cartesian_d<double> K; +//typedef CGAL::Point_d<K> Point_d; +typedef K::FT FT; +typedef CGAL::Search_traits< + FT, Point_d, + typename K::Cartesian_const_iterator_d, + typename K::Construct_cartesian_const_iterator_d> Traits_base; +typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; + + +typedef std::vector< Vertex_handle > typeVectorVertex; + +//typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; +//typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; + +typedef CGAL::Search_traits_adapter< + std::ptrdiff_t, Point_d*, Traits_base> STraits; +//typedef K TreeTraits; +//typedef CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance > Euclidean_adapter; +//typedef CGAL::Kd_tree<STraits> Kd_tree; +typedef CGAL::Orthogonal_k_neighbor_search<STraits, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>> K_neighbor_search; +typedef K_neighbor_search::Tree Tree; +typedef K_neighbor_search::Distance Distance; +typedef K_neighbor_search::iterator KNS_iterator; +typedef K_neighbor_search::iterator KNS_range; +typedef boost::container::flat_map<int, int> Point_etiquette_map; +typedef CGAL::Kd_tree<STraits> Tree2; + +typedef CGAL::Fuzzy_sphere<STraits> Fuzzy_sphere; + +typedef std::vector<Point_d> Point_Vector; + +//typedef K::Equal_d Equal_d; +//typedef CGAL::Random_points_in_cube_d<CGAL::Point_d<CGAL::Cartesian_d<FT> > > Random_cube_iterator; +typedef CGAL::Random_points_in_cube_d<Point_d> Random_cube_iterator; +typedef CGAL::Random_points_in_ball_d<Point_d> Random_point_iterator; + +typedef CGAL::Delaunay_triangulation<K> Delaunay_triangulation; +typedef Delaunay_triangulation::Facet Facet; +typedef CGAL::Sphere_d<K> Sphere_d; + +bool toric=false; + + +/** + * \brief Customized version of read_points + * which takes into account a possible nbP first line + * + */ +inline void +read_points_cust ( std::string file_name , Point_Vector & points) +{ + std::ifstream in_file (file_name.c_str(),std::ios::in); + if(!in_file.is_open()) + { + std::cerr << "Unable to open file " << file_name << std::endl; + return; + } + std::string line; + double x; + while( getline ( in_file , line ) ) + { + std::vector< double > point; + std::istringstream iss( line ); + while(iss >> x) { point.push_back(x); } + Point_d p(point.begin(), point.end()); + if (point.size() != 1) + points.push_back(p); + } + in_file.close(); +} + +void generate_points_grid(Point_Vector& W, int width, int D) +{ + int nb_points = 1; + for (int i = 0; i < D; ++i) + nb_points *= width; + for (int i = 0; i < nb_points; ++i) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(0.01*(cell_i%width)); + cell_i /= width; + } + W.push_back(point); + } +} + +void generate_points_random_box(Point_Vector& W, int nbP, int dim) +{ + /* + Random_cube_iterator rp(dim, 1); + for (int i = 0; i < nbP; i++) + { + std::vector<double> point; + for (auto it = rp->cartesian_begin(); it != rp->cartesian_end(); ++it) + point.push_back(*it); + W.push_back(Point_d(point)); + rp++; + } + */ + Random_cube_iterator rp(dim, 1.0); + for (int i = 0; i < nbP; i++) + { + W.push_back(*rp++); + } +} + + +void write_wl( std::string file_name, std::vector< std::vector <int> > & WL) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : WL) + { + for (auto l: w) + ofs << l << " "; + ofs << "\n"; + } + ofs.close(); +} + + +void write_points( std::string file_name, std::vector< Point_d > & points) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : points) + { + for (auto it = w.cartesian_begin(); it != w.cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + } + ofs.close(); +} + +void write_edges(std::string file_name, Witness_complex<>& witness_complex, Point_Vector& landmarks) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto u: witness_complex.complex_vertex_range()) + for (auto v: witness_complex.complex_vertex_range()) + { + typeVectorVertex edge = {u,v}; + if (u < v && witness_complex.find(edge) != witness_complex.null_simplex()) + { + for (auto it = landmarks[u].cartesian_begin(); it != landmarks[u].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + for (auto it = landmarks[v].cartesian_begin(); it != landmarks[v].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n\n\n"; + } + } + ofs.close(); +} + + +/** Function that chooses landmarks from W and place it in the kd-tree L. + * Note: nbL hould be removed if the code moves to Witness_complex + */ +void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + std::cout << "Enter landmark choice to kd tree\n"; + int chosen_landmark; + Point_d* p; + CGAL::Random rand; + for (int i = 0; i < nbL; i++) + { + // while (!res.second) + // { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + //rand++; + //std::cout << "Chose " << chosen_landmark << std::endl; + p = &W[chosen_landmark]; + //L_i.emplace(chosen_landmark,i); + // } + landmarks.push_back(*p); + landmarks_ind.push_back(chosen_landmark); + //std::cout << "Added landmark " << chosen_landmark << std::endl; + } + } + +void insert_delaunay_landmark_with_copies(Point_Vector& W, int chosen_landmark, std::vector<int>& landmarks_ind, Delaunay_triangulation& delaunay, int& landmark_count) +{ + delaunay.insert(W[chosen_landmark]); + landmarks_ind.push_back(chosen_landmark); + landmark_count++; +} + +bool is_violating_protection(Point_d& p, Delaunay_triangulation& t, int D, FT delta) +{ + Euclidean_distance ed; + Delaunay_triangulation::Vertex_handle v; + Delaunay_triangulation::Face f(t.current_dimension()); + Delaunay_triangulation::Facet ft; + Delaunay_triangulation::Full_cell_handle c; + Delaunay_triangulation::Locate_type lt; + c = t.locate(p, lt, f, ft, v); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + { + std::vector<Point_d> vertices; + for (auto v_it = fc_it->vertices_begin(); v_it != fc_it->vertices_end(); ++v_it) + vertices.push_back((*v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, p); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 >= r*r && dist2 <= (r+delta)*(r+delta)) + return true; + } + return false; +} + +bool triangulation_is_protected(Delaunay_triangulation& t, FT delta) +{ + Euclidean_distance ed; + int D = t.current_dimension(); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + for (auto v_it = t.vertices_begin(); v_it != t.vertices_end(); ++v_it) + { + //check if vertex belongs to the face + bool belongs = false; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + if (v_it == *fc_v_it) + { + belongs = true; + break; + } + if (!belongs) + { + std::vector<Point_d> vertices; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + vertices.push_back((*fc_v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, v_it->point()); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 <= (r+delta)*(r+delta)) + return false; + } + } + return true; +} + +FT sampling_radius(Delaunay_triangulation& t) +{ + int D = t.current_dimension(); + FT epsilon2 = 4.0; + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + { + Point_Vector vertices; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + vertices.push_back((*fc_v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + FT r2 = Euclidean_distance().transformed_distance(cs.center(), *(vertices.begin())); + if (epsilon2 > r2) + epsilon2 = r2; + } + return sqrt(epsilon2); +} + +FT point_sampling_radius_by_delaunay(Point_Vector& points) +{ + Delaunay_triangulation t(points[0].size()); + t.insert(points.begin(), points.end()); + return sampling_radius(t); +} + +void landmark_choice_protected_delaunay(Point_Vector& W, int nbP, Point_Vector& landmarks, std::vector<int>& landmarks_ind, FT delta) +{ + int D = W[0].size(); + Torus_distance td; + Euclidean_distance ed; + Delaunay_triangulation t(D); + CGAL::Random rand; + int landmark_count = 0; + std::list<int> index_list; + // shuffle the list of indexes (via a vector) + { + std::vector<int> temp_vector; + for (int i = 0; i < nbP; ++i) + temp_vector.push_back(i); + unsigned seed = std::chrono::system_clock::now().time_since_epoch().count(); + std::shuffle(temp_vector.begin(), temp_vector.end(), std::default_random_engine(seed)); + for (std::vector<int>::iterator it = temp_vector.begin(); it != temp_vector.end(); ++it) + index_list.push_front(*it); + } + // add the first D+1 vertices to form one non-empty cell + for (int i = 0; i <= D+1; ++i) + { + insert_delaunay_landmark_with_copies(W, index_list.front(), landmarks_ind, t, landmark_count); + index_list.pop_front(); + } + // add other vertices if they don't violate protection + std::list<int>::iterator list_it = index_list.begin(); + while (list_it != index_list.end()) + if (!is_violating_protection(W[*list_it], t, D, delta)) + { + // If no conflicts then insert in every copy of T^3 + insert_delaunay_landmark_with_copies(W, *list_it, landmarks_ind, t, landmark_count); + index_list.erase(list_it); + list_it = index_list.begin(); + } + else + list_it++; + for (std::vector<int>::iterator it = landmarks_ind.begin(); it != landmarks_ind.end(); ++it) + landmarks.push_back(W[*it]); +} + + +int landmark_perturbation(Point_Vector &W, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + //******************** Preface: origin point + int D = W[0].size(); + std::vector<FT> orig_vector; + for (int i=0; i<D; i++) + orig_vector.push_back(0); + Point_d origin(orig_vector); + + //******************** Constructing a WL matrix + int nbP = W.size(); + Euclidean_distance ed; + FT lambda = ed.transformed_distance(landmarks[0],landmarks[1]); + std::vector<Point_d> landmarks_ext; + int nb_cells = 1; + for (int i = 0; i < D; ++i) + nb_cells *= 3; + for (int i = 0; i < nb_cells; ++i) + for (int k = 0; k < nbL; ++k) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1.0)); + cell_i /= 3; + } + landmarks_ext.push_back(point); + } + write_points("landmarks/initial_landmarks",landmarks_ext); + STraits traits(&(landmarks_ext[0])); + std::vector< std::vector <int> > WL(nbP); + + //********************** Neighbor search in a Kd tree + Tree L(boost::counting_iterator<std::ptrdiff_t>(0), + boost::counting_iterator<std::ptrdiff_t>(nb_cells*nbL), + typename Tree::Splitter(), + traits); + std::cout << "Enter (D+1) nearest landmarks\n"; + for (int i = 0; i < nbP; i++) + { + Point_d& w = W[i]; + ////Search D+1 nearest neighbours from the tree of landmarks L + K_neighbor_search search(L, w, D+1, FT(0), true, + CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>(&(landmarks_ext[0])) ); + for(K_neighbor_search::iterator it = search.begin(); it != search.end(); ++it) + { + if (std::find(WL[i].begin(), WL[i].end(), (it->first)%nbL) == WL[i].end()) + WL[i].push_back((it->first)%nbL); + } + if (i == landmarks_ind[WL[i][0]]) + { + FT dist = ed.transformed_distance(W[i], landmarks[WL[i][1]]); + if (dist < lambda) + lambda = dist; + } + } + std::string out_file = "wl_result"; + write_wl(out_file,WL); + + //******************** Constructng a witness complex + std::cout << "Entered witness complex construction\n"; + Witness_complex<> witnessComplex; + witnessComplex.setNbL(nbL); + witnessComplex.witness_complex(WL); + + //******************** Making a set of bad link landmarks + std::cout << "Entered bad links\n"; + std::set< int > perturbL; + int count_badlinks = 0; + //std::cout << "Bad links around "; + std::vector< int > count_bad(D); + std::vector< int > count_good(D); + for (auto u: witnessComplex.complex_vertex_range()) + { + if (!witnessComplex.has_good_link(u, count_bad, count_good)) + { + count_badlinks++; + Point_d& l = landmarks[u]; + Fuzzy_sphere fs(l, sqrt(lambda)*3, 0, traits); + std::vector<int> curr_perturb; + L.search(std::insert_iterator<std::vector<int>>(curr_perturb,curr_perturb.begin()),fs); + for (int i: curr_perturb) + perturbL.insert(i%nbL); + } + } + for (unsigned int i = 0; i != count_good.size(); i++) + if (count_good[i] != 0) + std::cout << "count_good[" << i << "] = " << count_good[i] << std::endl; + for (unsigned int i = 0; i != count_bad.size(); i++) + if (count_bad[i] != 0) + std::cout << "count_bad[" << i << "] = " << count_bad[i] << std::endl; + std::cout << "\nBad links total: " << count_badlinks << " Points to perturb: " << perturbL.size() << std::endl; + + //*********************** Perturb bad link landmarks + for (auto u: perturbL) + { + Random_point_iterator rp(D,sqrt(lambda)/8); + std::vector<FT> point; + for (int i = 0; i < D; i++) + { + while (K().squared_distance_d_object()(*rp,origin) < lambda/256) + rp++; + FT coord = landmarks[u][i] + (*rp)[i]; + if (coord > 1) + point.push_back(coord-1); + else if (coord < -1) + point.push_back(coord+1); + else + point.push_back(coord); + } + landmarks[u] = Point_d(point); + } + std::cout << "lambda=" << lambda << std::endl; + char buffer[100]; + int i = sprintf(buffer,"stree_result.txt"); + + if (i >= 0) + { + std::string out_file = (std::string)buffer; + std::ofstream ofs (out_file, std::ofstream::out); + witnessComplex.st_to_file(ofs); + ofs.close(); + } + write_edges("landmarks/edges", witnessComplex, landmarks); + return count_badlinks; +} + + +int main (int argc, char * const argv[]) +{ + if (argc != 5) + { + std::cerr << "Usage: " << argv[0] + << " nbP nbL dim delta\n"; + return 0; + } + int nbP = atoi(argv[1]); + int nbL = atoi(argv[2]); + int dim = atoi(argv[3]); + FT delta = atof(argv[4]); + + std::cout << "Let the carnage begin!\n"; + Point_Vector point_vector; + generate_points_random_box(point_vector, nbP, dim); + FT epsilon = point_sampling_radius_by_delaunay(point_vector); + std::cout << "Initial epsilon = " << epsilon << std::endl; + Point_Vector L; + std::vector<int> chosen_landmarks; + bool ok=false; + while (!ok) + { + ok = true; + L = {}; + chosen_landmarks = {}; + //landmark_choice_by_delaunay(point_vector, nbP, nbL, L, chosen_landmarks, delta); + landmark_choice_protected_delaunay(point_vector, nbP, L, chosen_landmarks, delta); + nbL = chosen_landmarks.size(); + std::cout << "Number of landmarks is " << nbL << std::endl; + //int width = (int)pow(nbL, 1.0/dim); landmark_choice_bcc(point_vector, nbP, width, L, chosen_landmarks); + for (auto i: chosen_landmarks) + { + ok = ok && (std::count(chosen_landmarks.begin(),chosen_landmarks.end(),i) == 1); + if (!ok) break; + } + + } + FT epsilon2 = point_sampling_radius_by_delaunay(L); + std::cout << "Final epsilon = " << epsilon2 << ". Ratio = " << epsilon/epsilon2 << std::endl; + int bl = nbL, curr_min = bl; + write_points("landmarks/initial_pointset",point_vector); + //write_points("landmarks/initial_landmarks",L); + //for (int i = 0; i < 1; i++) + for (int i = 0; bl > 0; i++) + { + std::cout << "========== Start iteration " << i << "== curr_min(" << curr_min << ")========\n"; + bl=landmark_perturbation(point_vector, nbL, L, chosen_landmarks); + if (bl < curr_min) + curr_min=bl; + write_points("landmarks/landmarks0",L); + } + +} diff --git a/src/Witness_complex/example/witness_complex_flat_torus.cpp b/src/Witness_complex/example/witness_complex_flat_torus.cpp index 42bf5e7e..06bf5a9f 100644 --- a/src/Witness_complex/example/witness_complex_flat_torus.cpp +++ b/src/Witness_complex/example/witness_complex_flat_torus.cpp @@ -63,8 +63,10 @@ using namespace Gudhi; //using namespace boost::filesystem; typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; -typedef K::FT FT; typedef K::Point_d Point_d; +//typedef CGAL::Cartesian_d<double> K; +//typedef CGAL::Point_d<K> Point_d; +typedef K::FT FT; typedef CGAL::Search_traits< FT, Point_d, typename K::Cartesian_const_iterator_d, @@ -72,7 +74,7 @@ typedef CGAL::Search_traits< typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; /** - * \brief Class of distance in a flat torus in dimaension D + * \brief Class of distance in a flat torus in dimension D * */ //class Torus_distance : public Euclidean_distance { @@ -288,10 +290,11 @@ typedef CGAL::Fuzzy_sphere<STraits> Fuzzy_sphere; typedef std::vector<Point_d> Point_Vector; //typedef K::Equal_d Equal_d; +//typedef CGAL::Random_points_in_cube_d<CGAL::Point_d<CGAL::Cartesian_d<FT> > > Random_cube_iterator; typedef CGAL::Random_points_in_cube_d<Point_d> Random_cube_iterator; typedef CGAL::Random_points_in_ball_d<Point_d> Random_point_iterator; -bool toric=true; +bool toric=false; /** * \brief Customized version of read_points @@ -341,9 +344,20 @@ void generate_points_grid(Point_Vector& W, int width, int D) void generate_points_random_box(Point_Vector& W, int nbP, int dim) { + /* Random_cube_iterator rp(dim, 1); for (int i = 0; i < nbP; i++) { + std::vector<double> point; + for (auto it = rp->cartesian_begin(); it != rp->cartesian_end(); ++it) + point.push_back(*it); + W.push_back(Point_d(point)); + rp++; + } + */ + Random_cube_iterator rp(dim, 1.0); + for (int i = 0; i < nbP; i++) + { W.push_back(*rp++); } } @@ -494,9 +508,7 @@ void write_edges(std::string file_name, Witness_complex<>& witness_complex, Poin void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) { std::cout << "Enter landmark choice to kd tree\n"; - //std::vector<Point_d> landmarks; int chosen_landmark; - //std::pair<Point_etiquette_map::iterator,bool> res = std::make_pair(L_i.begin(),false); Point_d* p; CGAL::Random rand; for (int i = 0; i < nbL; i++) @@ -516,6 +528,33 @@ void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, } } +/** \brief Choose landmarks on a body-central cubic system + */ +void landmark_choice_bcc(Point_Vector &W, int nbP, int width, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + int D = W[0].size(); + int nb_points = 1; + for (int i = 0; i < D; ++i) + nb_points *= width; + for (int i = 0; i < nb_points; ++i) + { + std::vector<double> point; + std::vector<double> cpoint; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(-1.0+(2.0/width)*(cell_i%width)); + cpoint.push_back(-1.0+(2.0/width)*(cell_i%width)+(1.0/width)); + cell_i /= width; + } + landmarks.push_back(point); + landmarks.push_back(cpoint); + landmarks_ind.push_back(2*i); + landmarks_ind.push_back(2*i+1); + } + std::cout << "The number of landmarks is: " << landmarks.size() << std::endl; +} + int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector<int>& landmarks_ind) { @@ -548,7 +587,7 @@ int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector< int cell_i = i; for (int l = 0; l < D; ++l) { - point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1)); + point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1.0)); cell_i /= 3; } landmarks_ext.push_back(point); @@ -587,7 +626,8 @@ int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector< //Point_etiquette_map::iterator itm = L_i.find(it->first); //assert(itm != L_i.end()); //std::cout << "Entered KNN_it with point at distance " << it->second << "\n"; - WL[i].push_back((it->first)%nbL); + if (std::find(WL[i].begin(), WL[i].end(), (it->first)%nbL) == WL[i].end()) + WL[i].push_back((it->first)%nbL); //std::cout << "ITFIRST " << it->first << std::endl; //std::cout << i << " " << it->first << ": " << it->second << std::endl; } @@ -609,6 +649,12 @@ int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector< Witness_complex<> witnessComplex; witnessComplex.setNbL(nbL); witnessComplex.witness_complex(WL); + /* + if (witnessComplex.is_witness_complex(WL)) + std::cout << "!!YES. IT IS A WITNESS COMPLEX!!\n"; + else + std::cout << "??NO. IT IS NOT A WITNESS COMPLEX??\n"; + */ //******************** Making a set of bad link landmarks std::cout << "Entered bad links\n"; std::set< int > perturbL; @@ -730,9 +776,9 @@ int main (int argc, char * const argv[]) std::cout << "Let the carnage begin!\n"; Point_Vector point_vector; //read_points_cust(file_name, point_vector); - //generate_points_random_box(point_vector, nbP, dim); - generate_points_grid(point_vector, (int)pow(nbP, 1.0/dim), dim); - nbP = (int)(pow((int)pow(nbP, 1.0/dim), dim)); + generate_points_random_box(point_vector, nbP, dim); + //generate_points_grid(point_vector, (int)pow(nbP, 1.0/dim), dim); + //nbP = (int)(pow((int)pow(nbP, 1.0/dim), dim)); /* for (auto &p: point_vector) { @@ -757,17 +803,20 @@ int main (int argc, char * const argv[]) L = {}; chosen_landmarks = {}; landmark_choice(point_vector, nbP, nbL, L, chosen_landmarks); + + //int width = (int)pow(nbL, 1.0/dim); landmark_choice_bcc(point_vector, nbP, width, L, chosen_landmarks); for (auto i: chosen_landmarks) { ok = ok && (std::count(chosen_landmarks.begin(),chosen_landmarks.end(),i) == 1); if (!ok) break; } + } int bl = nbL, curr_min = bl; write_points("landmarks/initial_pointset",point_vector); //write_points("landmarks/initial_landmarks",L); - - for (int i = 0; bl > 0; i++) + for (int i = 0; i < 1; i++) + //for (int i = 0; bl > 0; i++) { std::cout << "========== Start iteration " << i << "== curr_min(" << curr_min << ")========\n"; bl=landmark_perturbation(point_vector, L, chosen_landmarks); diff --git a/src/Witness_complex/example/witness_complex_perturbations.cpp b/src/Witness_complex/example/witness_complex_perturbations.cpp index 88a7510a..b3b84b1f 100644 --- a/src/Witness_complex/example/witness_complex_perturbations.cpp +++ b/src/Witness_complex/example/witness_complex_perturbations.cpp @@ -416,7 +416,7 @@ int main (int argc, char * const argv[]) { file_name.erase(0, last_slash_idx + 1); } - //write_points("landmarks/initial_pointset",point_vector); + write_points("landmarks/initial_pointset",point_vector); write_points("landmarks/initial_landmarks",L); //for (int i = 0; bl != 0; i++) for (int i = 0; i < 1; i++) diff --git a/src/Witness_complex/example/witness_complex_protected_delaunay.cpp b/src/Witness_complex/example/witness_complex_protected_delaunay.cpp new file mode 100644 index 00000000..2f795a5f --- /dev/null +++ b/src/Witness_complex/example/witness_complex_protected_delaunay.cpp @@ -0,0 +1,594 @@ +/* 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(s): Siargey Kachanovich + * + * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) + * + * 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/>. + */ + +#include <iostream> +#include <fstream> +#include <ctime> +#include <utility> +#include <algorithm> +#include <set> +#include <iterator> +#include <chrono> + +#include <sys/types.h> +#include <sys/stat.h> +//#include <stdlib.h> + +//#include "gudhi/graph_simplicial_complex.h" +#include "gudhi/Witness_complex.h" +#include "gudhi/reader_utils.h" +#include "Torus_distance.h" + +#include <CGAL/Cartesian_d.h> +#include <CGAL/Search_traits.h> +#include <CGAL/Search_traits_adapter.h> +#include <CGAL/property_map.h> +#include <CGAL/Epick_d.h> +#include <CGAL/Orthogonal_k_neighbor_search.h> +#include <CGAL/Kd_tree.h> +#include <CGAL/Euclidean_distance.h> +#include <CGAL/Kernel_d/Sphere_d.h> + +#include <CGAL/Kernel_d/Vector_d.h> +#include <CGAL/point_generators_d.h> +#include <CGAL/constructions_d.h> +#include <CGAL/Fuzzy_sphere.h> +#include <CGAL/Random.h> +#include <CGAL/Delaunay_triangulation.h> + + +#include <boost/tuple/tuple.hpp> +#include <boost/iterator/zip_iterator.hpp> +#include <boost/iterator/counting_iterator.hpp> +#include <boost/range/iterator_range.hpp> + +using namespace Gudhi; +//using namespace boost::filesystem; + +typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K; +typedef K::Point_d Point_d; +//typedef CGAL::Cartesian_d<double> K; +//typedef CGAL::Point_d<K> Point_d; +typedef K::FT FT; +typedef CGAL::Search_traits< + FT, Point_d, + typename K::Cartesian_const_iterator_d, + typename K::Construct_cartesian_const_iterator_d> Traits_base; +typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; + + +typedef std::vector< Vertex_handle > typeVectorVertex; + +//typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; +//typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; + +typedef CGAL::Search_traits_adapter< + std::ptrdiff_t, Point_d*, Traits_base> STraits; +//typedef K TreeTraits; +//typedef CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance > Euclidean_adapter; +//typedef CGAL::Kd_tree<STraits> Kd_tree; +typedef CGAL::Orthogonal_k_neighbor_search<STraits, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>> K_neighbor_search; +typedef K_neighbor_search::Tree Tree; +typedef K_neighbor_search::Distance Distance; +typedef K_neighbor_search::iterator KNS_iterator; +typedef K_neighbor_search::iterator KNS_range; +typedef boost::container::flat_map<int, int> Point_etiquette_map; +typedef CGAL::Kd_tree<STraits> Tree2; + +typedef CGAL::Fuzzy_sphere<STraits> Fuzzy_sphere; + +typedef std::vector<Point_d> Point_Vector; + +//typedef K::Equal_d Equal_d; +//typedef CGAL::Random_points_in_cube_d<CGAL::Point_d<CGAL::Cartesian_d<FT> > > Random_cube_iterator; +typedef CGAL::Random_points_in_cube_d<Point_d> Random_cube_iterator; +typedef CGAL::Random_points_in_ball_d<Point_d> Random_point_iterator; + +typedef CGAL::Delaunay_triangulation<K> Delaunay_triangulation; +typedef Delaunay_triangulation::Facet Facet; +typedef CGAL::Sphere_d<K> Sphere_d; + +bool toric=false; + + +/** + * \brief Customized version of read_points + * which takes into account a possible nbP first line + * + */ +inline void +read_points_cust ( std::string file_name , Point_Vector & points) +{ + std::ifstream in_file (file_name.c_str(),std::ios::in); + if(!in_file.is_open()) + { + std::cerr << "Unable to open file " << file_name << std::endl; + return; + } + std::string line; + double x; + while( getline ( in_file , line ) ) + { + std::vector< double > point; + std::istringstream iss( line ); + while(iss >> x) { point.push_back(x); } + Point_d p(point.begin(), point.end()); + if (point.size() != 1) + points.push_back(p); + } + in_file.close(); +} + +void generate_points_grid(Point_Vector& W, int width, int D) +{ + int nb_points = 1; + for (int i = 0; i < D; ++i) + nb_points *= width; + for (int i = 0; i < nb_points; ++i) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(0.01*(cell_i%width)); + cell_i /= width; + } + W.push_back(point); + } +} + +void generate_points_random_box(Point_Vector& W, int nbP, int dim) +{ + /* + Random_cube_iterator rp(dim, 1); + for (int i = 0; i < nbP; i++) + { + std::vector<double> point; + for (auto it = rp->cartesian_begin(); it != rp->cartesian_end(); ++it) + point.push_back(*it); + W.push_back(Point_d(point)); + rp++; + } + */ + Random_cube_iterator rp(dim, 1.0); + for (int i = 0; i < nbP; i++) + { + W.push_back(*rp++); + } +} + + +void write_wl( std::string file_name, std::vector< std::vector <int> > & WL) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : WL) + { + for (auto l: w) + ofs << l << " "; + ofs << "\n"; + } + ofs.close(); +} + + +void write_points( std::string file_name, std::vector< Point_d > & points) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto w : points) + { + for (auto it = w.cartesian_begin(); it != w.cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + } + ofs.close(); +} + +void write_edges(std::string file_name, Witness_complex<>& witness_complex, Point_Vector& landmarks) +{ + std::ofstream ofs (file_name, std::ofstream::out); + for (auto u: witness_complex.complex_vertex_range()) + for (auto v: witness_complex.complex_vertex_range()) + { + typeVectorVertex edge = {u,v}; + if (u < v && witness_complex.find(edge) != witness_complex.null_simplex()) + { + for (auto it = landmarks[u].cartesian_begin(); it != landmarks[u].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n"; + for (auto it = landmarks[v].cartesian_begin(); it != landmarks[v].cartesian_end(); ++it) + ofs << *it << " "; + ofs << "\n\n\n"; + } + } + ofs.close(); +} + + +/** Function that chooses landmarks from W and place it in the kd-tree L. + * Note: nbL hould be removed if the code moves to Witness_complex + */ +void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + std::cout << "Enter landmark choice to kd tree\n"; + int chosen_landmark; + Point_d* p; + CGAL::Random rand; + for (int i = 0; i < nbL; i++) + { + // while (!res.second) + // { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + //rand++; + //std::cout << "Chose " << chosen_landmark << std::endl; + p = &W[chosen_landmark]; + //L_i.emplace(chosen_landmark,i); + // } + landmarks.push_back(*p); + landmarks_ind.push_back(chosen_landmark); + //std::cout << "Added landmark " << chosen_landmark << std::endl; + } + } + +void insert_delaunay_landmark_with_copies(Point_Vector& W, int chosen_landmark, std::vector<int>& landmarks_ind, Delaunay_triangulation& delaunay, int& landmark_count) +{ + int D = W[0].size(); + int nb_cells = pow(3, D); + for (int i = 0; i < nb_cells; ++i) + { + std::vector<FT> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(W[chosen_landmark][l] + 2.0*(cell_i%3-1)); + cell_i /= 3; + } + delaunay.insert(point); + } + landmarks_ind.push_back(chosen_landmark); + landmark_count++; +} + +bool is_violating_protection(Point_d& p, Delaunay_triangulation& t, int D, FT delta) +{ + Euclidean_distance ed; + Delaunay_triangulation::Vertex_handle v; + Delaunay_triangulation::Face f(t.current_dimension()); + Delaunay_triangulation::Facet ft; + Delaunay_triangulation::Full_cell_handle c; + Delaunay_triangulation::Locate_type lt; + c = t.locate(p, lt, f, ft, v); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + { + std::vector<Point_d> vertices; + for (auto v_it = fc_it->vertices_begin(); v_it != fc_it->vertices_end(); ++v_it) + vertices.push_back((*v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, p); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 >= r*r && dist2 <= (r+delta)*(r+delta)) + return true; + } + return false; +} + +bool triangulation_is_protected(Delaunay_triangulation& t, FT delta) +{ + Euclidean_distance ed; + int D = t.current_dimension(); + for (auto fc_it = t.full_cells_begin(); fc_it != t.full_cells_end(); ++fc_it) + if (!t.is_infinite(fc_it)) + for (auto v_it = t.vertices_begin(); v_it != t.vertices_end(); ++v_it) + { + //check if vertex belongs to the face + bool belongs = false; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + if (v_it == *fc_v_it) + { + belongs = true; + break; + } + if (!belongs) + { + std::vector<Point_d> vertices; + for (auto fc_v_it = fc_it->vertices_begin(); fc_v_it != fc_it->vertices_end(); ++fc_v_it) + vertices.push_back((*fc_v_it)->point()); + Sphere_d cs(D, vertices.begin(), vertices.end()); + Point_d center_cs = cs.center(); + FT r = sqrt(ed.transformed_distance(center_cs, fc_it->vertex(1)->point())); + FT dist2 = ed.transformed_distance(center_cs, v_it->point()); + //if the new point is inside the protection ball of a non conflicting simplex + if (dist2 <= (r+delta)*(r+delta)) + return false; + } + } + return true; +} + +void fill_landmark_copies(Point_Vector& W, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + int D = W[0].size(); + int nb_cells = pow(3, D); + int nbL = landmarks_ind.size(); + // Fill landmarks + for (int i = 0; i < nb_cells-1; ++i) + for (int j = 0; j < nbL; ++j) + { + int cell_i = i; + Point_d point; + for (int l = 0; l < D; ++l) + { + point.push_back(W[landmarks_ind[j]][l] + 2.0*(cell_i-1)); + cell_i /= 3; + } + landmarks.push_back(point); + } +} + +void landmark_choice_by_delaunay(Point_Vector& W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind, FT delta) +{ + int D = W[0].size(); + Delaunay_triangulation t(D); + CGAL::Random rand; + int chosen_landmark; + int landmark_count = 0; + for (int i = 0; i <= D+1; ++i) + { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + insert_delaunay_landmark_with_copies(W, chosen_landmark, landmarks_ind, t, landmark_count); + } + while (landmark_count < nbL) + { + do chosen_landmark = rand.get_int(0,nbP); + while (std::count(landmarks_ind.begin(),landmarks_ind.end(),chosen_landmark)!=0); + // If no conflicts then insert in every copy of T^3 + if (!is_violating_protection(W[chosen_landmark], t, D, delta)) + insert_delaunay_landmark_with_copies(W, chosen_landmark, landmarks_ind, t, landmark_count); + } + fill_landmark_copies(W, landmarks, landmarks_ind); +} + + +void landmark_choice_protected_delaunay(Point_Vector& W, int nbP, Point_Vector& landmarks, std::vector<int>& landmarks_ind, FT delta) +{ + int D = W[0].size(); + Torus_distance td; + Euclidean_distance ed; + Delaunay_triangulation t(D); + CGAL::Random rand; + int landmark_count = 0; + std::list<int> index_list; + // shuffle the list of indexes (via a vector) + { + std::vector<int> temp_vector; + for (int i = 0; i < nbP; ++i) + temp_vector.push_back(i); + unsigned seed = std::chrono::system_clock::now().time_since_epoch().count(); + std::shuffle(temp_vector.begin(), temp_vector.end(), std::default_random_engine(seed)); + for (std::vector<int>::iterator it = temp_vector.begin(); it != temp_vector.end(); ++it) + index_list.push_front(*it); + } + // add the first D+1 vertices to form one non-empty cell + for (int i = 0; i <= D+1; ++i) + { + insert_delaunay_landmark_with_copies(W, index_list.front(), landmarks_ind, t, landmark_count); + index_list.pop_front(); + } + // add other vertices if they don't violate protection + std::list<int>::iterator list_it = index_list.begin(); + while (list_it != index_list.end()) + if (!is_violating_protection(W[*list_it], t, D, delta)) + { + // If no conflicts then insert in every copy of T^3 + insert_delaunay_landmark_with_copies(W, *list_it, landmarks_ind, t, landmark_count); + index_list.erase(list_it); + list_it = index_list.begin(); + } + else + list_it++; + fill_landmark_copies(W, landmarks, landmarks_ind); +} + + +int landmark_perturbation(Point_Vector &W, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + //******************** Preface: origin point + int D = W[0].size(); + std::vector<FT> orig_vector; + for (int i=0; i<D; i++) + orig_vector.push_back(0); + Point_d origin(orig_vector); + + //******************** Constructing a WL matrix + int nbP = W.size(); + Euclidean_distance ed; + FT lambda = ed.transformed_distance(landmarks[0],landmarks[1]); + std::vector<Point_d> landmarks_ext; + int nb_cells = 1; + for (int i = 0; i < D; ++i) + nb_cells *= 3; + for (int i = 0; i < nb_cells; ++i) + for (int k = 0; k < nbL; ++k) + { + std::vector<double> point; + int cell_i = i; + for (int l = 0; l < D; ++l) + { + point.push_back(landmarks[k][l] + 2.0*((cell_i%3)-1.0)); + cell_i /= 3; + } + landmarks_ext.push_back(point); + } + write_points("landmarks/initial_landmarks",landmarks_ext); + STraits traits(&(landmarks_ext[0])); + std::vector< std::vector <int> > WL(nbP); + + //********************** Neighbor search in a Kd tree + Tree L(boost::counting_iterator<std::ptrdiff_t>(0), + boost::counting_iterator<std::ptrdiff_t>(nb_cells*nbL), + typename Tree::Splitter(), + traits); + std::cout << "Enter (D+1) nearest landmarks\n"; + for (int i = 0; i < nbP; i++) + { + Point_d& w = W[i]; + ////Search D+1 nearest neighbours from the tree of landmarks L + K_neighbor_search search(L, w, D+1, FT(0), true, + CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>(&(landmarks_ext[0])) ); + for(K_neighbor_search::iterator it = search.begin(); it != search.end(); ++it) + { + if (std::find(WL[i].begin(), WL[i].end(), (it->first)%nbL) == WL[i].end()) + WL[i].push_back((it->first)%nbL); + } + if (i == landmarks_ind[WL[i][0]]) + { + FT dist = ed.transformed_distance(W[i], landmarks[WL[i][1]]); + if (dist < lambda) + lambda = dist; + } + } + std::string out_file = "wl_result"; + write_wl(out_file,WL); + + //******************** Constructng a witness complex + std::cout << "Entered witness complex construction\n"; + Witness_complex<> witnessComplex; + witnessComplex.setNbL(nbL); + witnessComplex.witness_complex(WL); + + //******************** Making a set of bad link landmarks + std::cout << "Entered bad links\n"; + std::set< int > perturbL; + int count_badlinks = 0; + //std::cout << "Bad links around "; + std::vector< int > count_bad(D); + std::vector< int > count_good(D); + for (auto u: witnessComplex.complex_vertex_range()) + { + if (!witnessComplex.has_good_link(u, count_bad, count_good)) + { + count_badlinks++; + Point_d& l = landmarks[u]; + Fuzzy_sphere fs(l, sqrt(lambda)*3, 0, traits); + std::vector<int> curr_perturb; + L.search(std::insert_iterator<std::vector<int>>(curr_perturb,curr_perturb.begin()),fs); + for (int i: curr_perturb) + perturbL.insert(i%nbL); + } + } + for (unsigned int i = 0; i != count_good.size(); i++) + if (count_good[i] != 0) + std::cout << "count_good[" << i << "] = " << count_good[i] << std::endl; + for (unsigned int i = 0; i != count_bad.size(); i++) + if (count_bad[i] != 0) + std::cout << "count_bad[" << i << "] = " << count_bad[i] << std::endl; + std::cout << "\nBad links total: " << count_badlinks << " Points to perturb: " << perturbL.size() << std::endl; + + //*********************** Perturb bad link landmarks + for (auto u: perturbL) + { + Random_point_iterator rp(D,sqrt(lambda)/8); + std::vector<FT> point; + for (int i = 0; i < D; i++) + { + while (K().squared_distance_d_object()(*rp,origin) < lambda/256) + rp++; + FT coord = landmarks[u][i] + (*rp)[i]; + if (coord > 1) + point.push_back(coord-1); + else if (coord < -1) + point.push_back(coord+1); + else + point.push_back(coord); + } + landmarks[u] = Point_d(point); + } + std::cout << "lambda=" << lambda << std::endl; + char buffer[100]; + int i = sprintf(buffer,"stree_result.txt"); + + if (i >= 0) + { + std::string out_file = (std::string)buffer; + std::ofstream ofs (out_file, std::ofstream::out); + witnessComplex.st_to_file(ofs); + ofs.close(); + } + write_edges("landmarks/edges", witnessComplex, landmarks); + return count_badlinks; +} + + +int main (int argc, char * const argv[]) +{ + if (argc != 5) + { + std::cerr << "Usage: " << argv[0] + << " nbP nbL dim delta\n"; + return 0; + } + int nbP = atoi(argv[1]); + int nbL = atoi(argv[2]); + int dim = atoi(argv[3]); + FT delta = atof(argv[4]); + + std::cout << "Let the carnage begin!\n"; + Point_Vector point_vector; + generate_points_random_box(point_vector, nbP, dim); + Point_Vector L; + std::vector<int> chosen_landmarks; + bool ok=false; + while (!ok) + { + ok = true; + L = {}; + chosen_landmarks = {}; + //landmark_choice_by_delaunay(point_vector, nbP, nbL, L, chosen_landmarks, delta); + landmark_choice_protected_delaunay(point_vector, nbP, L, chosen_landmarks, delta); + nbL = chosen_landmarks.size(); + std::cout << "Number of landmarks is " << nbL << std::endl; + //int width = (int)pow(nbL, 1.0/dim); landmark_choice_bcc(point_vector, nbP, width, L, chosen_landmarks); + for (auto i: chosen_landmarks) + { + ok = ok && (std::count(chosen_landmarks.begin(),chosen_landmarks.end(),i) == 1); + if (!ok) break; + } + + } + int bl = nbL, curr_min = bl; + write_points("landmarks/initial_pointset",point_vector); + //write_points("landmarks/initial_landmarks",L); + //for (int i = 0; i < 1; i++) + for (int i = 0; bl > 0; i++) + { + std::cout << "========== Start iteration " << i << "== curr_min(" << curr_min << ")========\n"; + bl=landmark_perturbation(point_vector, nbL, L, chosen_landmarks); + if (bl < curr_min) + curr_min=bl; + write_points("landmarks/landmarks0",L); + } + +} diff --git a/src/Witness_complex/example/witness_complex_sphere.cpp b/src/Witness_complex/example/witness_complex_sphere.cpp index d08c763f..74aae875 100644 --- a/src/Witness_complex/example/witness_complex_sphere.cpp +++ b/src/Witness_complex/example/witness_complex_sphere.cpp @@ -71,199 +71,6 @@ typedef CGAL::Search_traits< typename K::Construct_cartesian_const_iterator_d> Traits_base; typedef CGAL::Euclidean_distance<Traits_base> Euclidean_distance; -/** - * \brief Class of distance in a flat torus in dimaension D - * - */ -//class Torus_distance : public Euclidean_distance { - class Torus_distance { - -public: - typedef K::FT FT; - typedef K::Point_d Point_d; - typedef Point_d Query_item; - typedef typename CGAL::Dynamic_dimension_tag D; - - double box_length = 2; - - FT transformed_distance(Query_item q, Point_d p) const - { - FT distance = FT(0); - FT coord = FT(0); - //std::cout << "Hello skitty!\n"; - typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); - typename K::Cartesian_const_iterator_d qit = construct_it(q), - qe = construct_it(q,1), pit = construct_it(p); - for(; qit != qe; qit++, pit++) - { - coord = sqrt(((*qit)-(*pit))*((*qit)-(*pit))); - if (coord*coord <= (box_length-coord)*(box_length-coord)) - distance += coord*coord; - else - distance += (box_length-coord)*(box_length-coord); - } - return distance; - } - - FT min_distance_to_rectangle(const Query_item& q, - const CGAL::Kd_tree_rectangle<FT,D>& r) const { - FT distance = FT(0); - FT dist1, dist2; - typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); - typename K::Cartesian_const_iterator_d qit = construct_it(q), - qe = construct_it(q,1); - for(unsigned int i = 0;qit != qe; i++, qit++) - { - if((*qit) < r.min_coord(i)) - { - dist1 = (r.min_coord(i)-(*qit)); - dist2 = (box_length - r.max_coord(i)+(*qit)); - if (dist1 < dist2) - distance += dist1*dist1; - else - distance += dist2*dist2; - } - else if ((*qit) > r.max_coord(i)) - { - dist1 = (box_length - (*qit)+r.min_coord(i)); - dist2 = ((*qit) - r.max_coord(i)); - if (dist1 < dist2) - distance += dist1*dist1; - else - distance += dist2*dist2; - } - } - return distance; - } - - FT min_distance_to_rectangle(const Query_item& q, - const CGAL::Kd_tree_rectangle<FT,D>& r, - std::vector<FT>& dists) const { - FT distance = FT(0); - FT dist1, dist2; - typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); - typename K::Cartesian_const_iterator_d qit = construct_it(q), - qe = construct_it(q,1); - //std::cout << r.max_coord(0) << std::endl; - for(unsigned int i = 0;qit != qe; i++, qit++) - { - if((*qit) < r.min_coord(i)) - { - dist1 = (r.min_coord(i)-(*qit)); - dist2 = (box_length - r.max_coord(i)+(*qit)); - if (dist1 < dist2) - { - dists[i] = dist1; - distance += dist1*dist1; - } - else - { - dists[i] = dist2; - distance += dist2*dist2; - //std::cout << "Good stuff1\n"; - } - } - else if ((*qit) > r.max_coord(i)) - { - dist1 = (box_length - (*qit)+r.min_coord(i)); - dist2 = ((*qit) - r.max_coord(i)); - if (dist1 < dist2) - { - dists[i] = dist1; - distance += dist1*dist1; - //std::cout << "Good stuff2\n"; - } - else - { - dists[i] = dist2; - distance += dist2*dist2; - } - } - }; - return distance; - } - - FT max_distance_to_rectangle(const Query_item& q, - const CGAL::Kd_tree_rectangle<FT,D>& r) const { - FT distance=FT(0); - typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); - typename K::Cartesian_const_iterator_d qit = construct_it(q), - qe = construct_it(q,1); - for(unsigned int i = 0;qit != qe; i++, qit++) - { - if (box_length <= (r.min_coord(i)+r.max_coord(i))) - if ((r.max_coord(i)+r.min_coord(i)-box_length)/FT(2.0) <= (*qit) && - (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) - distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); - else - distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); - else - if ((box_length-r.max_coord(i)-r.min_coord(i))/FT(2.0) <= (*qit) || - (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) - distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); - else - distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); - } - return distance; - } - - - FT max_distance_to_rectangle(const Query_item& q, - const CGAL::Kd_tree_rectangle<FT,D>& r, - std::vector<FT>& dists) const { - FT distance=FT(0); - typename K::Construct_cartesian_const_iterator_d construct_it=Traits_base().construct_cartesian_const_iterator_d_object(); - typename K::Cartesian_const_iterator_d qit = construct_it(q), - qe = construct_it(q,1); - for(unsigned int i = 0;qit != qe; i++, qit++) - { - if (box_length <= (r.min_coord(i)+r.max_coord(i))) - if ((r.max_coord(i)+r.min_coord(i)-box_length)/FT(2.0) <= (*qit) && - (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) - { - dists[i] = r.max_coord(i)-(*qit); - distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); - } - else - { - dists[i] = sqrt(((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i))); - distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); - } - else - if ((box_length-r.max_coord(i)-r.min_coord(i))/FT(2.0) <= (*qit) || - (*qit) <= (r.min_coord(i)+r.max_coord(i))/FT(2.0)) - { - dists[i] = sqrt((r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit))); - distance += (r.max_coord(i)-(*qit))*(r.max_coord(i)-(*qit)); - - } - else - { - dists[i] = (*qit)-r.min_coord(i); - distance += ((*qit)-r.min_coord(i))*((*qit)-r.min_coord(i)); - } - } - return distance; - } - - inline FT new_distance(FT dist, FT old_off, FT new_off, - int /* cutting_dimension */) const { - - FT new_dist = dist + (new_off*new_off - old_off*old_off); - return new_dist; - } - - inline FT transformed_distance(FT d) const { - return d*d; - } - - inline FT inverse_of_transformed_distance(FT d) const { - return sqrt(d); - } - -}; - - typedef std::vector< Vertex_handle > typeVectorVertex; //typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex; @@ -502,6 +309,49 @@ void landmark_choice(Point_Vector &W, int nbP, int nbL, Point_Vector& landmarks, } } +/** \brief A test with 600cell, the generalisation of icosaedre in 4d + */ +void landmark_choice_600cell(Point_Vector&W, int nbP, int nbL, Point_Vector& landmarks, std::vector<int>& landmarks_ind) +{ + assert(W[0].size() == 4); //4-dimensionality required + FT phi = (1+sqrt(5))/2; + FT phi_1 = FT(1)/phi; + std::vector<FT> p; + // 16 vertices + for (FT a = -0.5; a < 1; a += 1) + for (FT b = -0.5; b < 1; b += 1) + for (FT c = -0.5; c < 1; c += 1) + for (FT d = -0.5; d < 1; d += 1) + landmarks.push_back(Point_d(std::vector<FT>({a,b,c,d}))); + // 8 vertices + for (FT a = -0.5; a < 1; a += 1) + { + landmarks.push_back(Point_d(std::vector<FT>({a,0,0,0}))); + landmarks.push_back(Point_d(std::vector<FT>({0,a,0,0}))); + landmarks.push_back(Point_d(std::vector<FT>({0,0,a,0}))); + landmarks.push_back(Point_d(std::vector<FT>({0,0,0,a}))); + } + // 96 vertices + for (FT a = -phi/2; a < phi; a += phi) + for (FT b = -0.5; b < 1; b += 1) + for (FT c = -phi_1/2; c < phi_1; c += phi_1) + { + landmarks.push_back(Point_d(std::vector<FT>({a,b,c,0}))); + landmarks.push_back(Point_d(std::vector<FT>({b,a,0,c}))); + landmarks.push_back(Point_d(std::vector<FT>({c,0,a,b}))); + landmarks.push_back(Point_d(std::vector<FT>({0,c,b,a}))); + landmarks.push_back(Point_d(std::vector<FT>({a,c,0,b}))); + landmarks.push_back(Point_d(std::vector<FT>({a,0,b,c}))); + landmarks.push_back(Point_d(std::vector<FT>({c,b,0,a}))); + landmarks.push_back(Point_d(std::vector<FT>({0,b,a,c}))); + landmarks.push_back(Point_d(std::vector<FT>({b,0,c,a}))); + landmarks.push_back(Point_d(std::vector<FT>({0,a,c,b}))); + landmarks.push_back(Point_d(std::vector<FT>({b,c,a,0}))); + landmarks.push_back(Point_d(std::vector<FT>({c,a,b,0}))); + } + for (int i = 0; i < 120; ++i) + landmarks_ind.push_back(i); +} int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector<int>& landmarks_ind) { @@ -516,10 +366,7 @@ int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector< //******************** Constructing a WL matrix int nbP = W.size(); int nbL = landmarks.size(); - //Point_Vector landmarks_ = landmarks; - Torus_distance ed; - //Equal_d ed; - //Point_d p1(std::vector<FT>({0.8,0.8})), p2(std::vector<FT>({0.1,0.1})); + Euclidean_distance ed; FT lambda = ed.transformed_distance(landmarks[0],landmarks[1]); //std::cout << "Lambda=" << lambda << std::endl; //FT lambda = 0.1;//Euclidean_distance(); @@ -578,10 +425,12 @@ int landmark_perturbation(Point_Vector &W, Point_Vector& landmarks, std::vector< Witness_complex<> witnessComplex; witnessComplex.setNbL(nbL); witnessComplex.witness_complex(WL); + /* if (witnessComplex.is_witness_complex(WL)) std::cout << "!!YES. IT IS A WITNESS COMPLEX!!\n"; else - std::cout << "??NO. IT IS NOT A WITNESS COMPLEX??\n"; + std::cout << "??NO. IT IS NOT A WITNESS COMPLEX??\n"; + */ //******************** Making a set of bad link landmarks std::cout << "Entered bad links\n"; std::set< int > perturbL; @@ -715,11 +564,14 @@ int main (int argc, char * const argv[]) L = {}; chosen_landmarks = {}; landmark_choice(point_vector, nbP, nbL, L, chosen_landmarks); + //landmark_choice_600cell(point_vector, nbP, nbL, L, chosen_landmarks); + /* for (auto i: chosen_landmarks) { ok = ok && (std::count(chosen_landmarks.begin(),chosen_landmarks.end(),i) == 1); if (!ok) break; } + */ } int bl = nbL, curr_min = bl; write_points("landmarks/initial_pointset",point_vector); |