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+/* 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);
+ }
+
+}