/* 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 . */ #include #include #include #include #include #include //#include //#include "gudhi/graph_simplicial_complex.h" #include "gudhi/Witness_complex.h" #include "gudhi/reader_utils.h" #include "generators.h" #include "output.h" //#include //#include #include #include #include #include #include #include #include #include #include #include using namespace Gudhi; //using namespace boost::filesystem; typedef std::vector< Vertex_handle > typeVectorVertex; //typedef std::pair typeSimplex; //typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool; typedef CGAL::Epick_d K; typedef K::FT FT; typedef K::Point_d Point_d; typedef CGAL::Search_traits< FT, Point_d, typename K::Cartesian_const_iterator_d, typename K::Construct_cartesian_const_iterator_d> Traits_base; typedef CGAL::Search_traits_adapter< std::ptrdiff_t, Point_d*, Traits_base> STraits; //typedef K TreeTraits; typedef CGAL::Orthogonal_k_neighbor_search 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 Point_etiquette_map; typedef std::vector Point_Vector; /** 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_to_tree(Point_Vector &W, int nbP, Point_etiquette_map &L_i, int nbL, std::vector< std::vector > &WL) { std::cout << "Enter landmark choice to kd tree\n"; std::vector landmarks; int chosen_landmark; //std::pair res = std::make_pair(L_i.begin(),false); Point_d* p; srand(24660); for (int i = 0; i < nbL; i++) { // while (!res.second) // { chosen_landmark = rand()%nbP; p = &W[chosen_landmark]; //L_i.emplace(chosen_landmark,i); // } landmarks.push_back(*p); //std::cout << "Added landmark " << chosen_landmark << std::endl; } Tree L(boost::counting_iterator(0), boost::counting_iterator(nbL), typename Tree::Splitter(), STraits((Point_d*)&(landmarks[0]))); /*} void d_nearest_landmarks(Point_Vector &W, Tree &L, Point_etiquette_map &L_i, std::vector< std::vector > &WL) {*/ std::cout << "Enter (D+1) nearest landmarks\n"; std::cout << "Size of the tree is " << L.size() << std::endl; //int nbP = W.size(); int D = W[0].size(); for (int i = 0; i < nbP; i++) { //std::cout << "Entered witness number " << i << std::endl; Point_d& w = W[i]; //std::cout << "Safely constructed a point\n"; //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>((Point_d*)&(landmarks[0])) ); //std::cout << "Safely found nearest landmarks\n"; for(K_neighbor_search::iterator it = search.begin(); it != search.end(); ++it) { //std::cout << "Entered KNN_it with point at distance " << it->second << "\n"; //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); //std::cout << i << " " << it->first << ": " << it->second << std::endl; } } } int main (int argc, char * const argv[]) { if (argc != 3) { std::cerr << "Usage: " << argv[0] << " path_to_point_file nbL \n"; return 0; } /* boost::filesystem::path p; for (; argc > 2; --argc, ++argv) p /= argv[1]; */ std::string file_name = argv[1]; int nbL = atoi(argv[2]); clock_t start, end; //Construct the Simplex Tree Witness_complex<> witnessComplex; std::cout << "Let the carnage begin!\n"; Point_Vector point_vector; read_points_cust(file_name, point_vector); //std::cout << "Successfully read the points\n"; witnessComplex.setNbL(nbL); // witnessComplex.witness_complex_from_points(point_vector); int nbP = point_vector.size(); std::vector > WL(nbP); //std::set L; Tree L; Point_etiquette_map L_i; start = clock(); //witnessComplex.landmark_choice_by_furthest_points(point_vector, point_vector.size(), WL); landmark_choice_to_tree(point_vector, nbP, L_i, nbL, WL); //d_nearest_landmarks(point_vector, L, L_i, WL); end = clock(); std::cout << "Landmark choice took " << (double)(end-start)/CLOCKS_PER_SEC << " s. \n"; // Write the WL matrix in a file mkdir("output", S_IRWXU); const size_t last_slash_idx = file_name.find_last_of("/"); if (std::string::npos != last_slash_idx) { file_name.erase(0, last_slash_idx + 1); } std::string out_file = "output/"+file_name+"_"+argv[2]+".wl"; write_wl(out_file,WL); start = clock(); witnessComplex.witness_complex(WL); // end = clock(); std::cout << "Howdy world! The process took " << (double)(end-start)/CLOCKS_PER_SEC << " s. \n"; /* char buffer[100]; int i = sprintf(buffer,"%s_%s_result.txt",argv[1],argv[2]); 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(); } */ out_file = "output/"+file_name+"_"+argv[2]+".stree"; std::ofstream ofs (out_file, std::ofstream::out); witnessComplex.st_to_file(ofs); ofs.close(); out_file = "output/"+file_name+"_"+argv[2]+".badlinks"; std::ofstream ofs2(out_file, std::ofstream::out); //witnessComplex.write_bad_links(ofs2); ofs2.close(); }