diff options
author | skachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2015-07-04 09:49:32 +0000 |
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committer | skachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb> | 2015-07-04 09:49:32 +0000 |
commit | d4c823dce7436f561c8cd545f5a4f80d2d301ca1 (patch) | |
tree | 759a6ac3d8c731b86ca99bea73c500298fc7fe79 /src/Witness_complex/example/witness_complex_epsilon.cpp | |
parent | c88e3b93de22be92cc7027f4c14ea4294f8c366f (diff) |
Added files for testing on didgeridoo
git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/witness@676 636b058d-ea47-450e-bf9e-a15bfbe3eedb
Former-commit-id: 6d8aeda398803d49ee9218b99939095098ceb92e
Diffstat (limited to 'src/Witness_complex/example/witness_complex_epsilon.cpp')
-rw-r--r-- | src/Witness_complex/example/witness_complex_epsilon.cpp | 566 |
1 files changed, 566 insertions, 0 deletions
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); + } + +} |