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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/>.
*/
#define BOOST_PARAMETER_MAX_ARITY 12
#include <sys/types.h>
#include <sys/stat.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/Strange_witness_complex.h>
#include <gudhi/Landmark_choice_by_random_point.h>
#include <gudhi/reader_utils.h>
#include "output.h"
#include <iostream>
#include <fstream>
#include <ctime>
#include <utility>
#include <string>
#include <vector>
#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_incremental_neighbor_search.h>
#include <CGAL/Kd_tree.h>
#include <CGAL/Euclidean_distance.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 <boost/tuple/tuple.hpp>
#include <boost/iterator/zip_iterator.hpp>
#include <boost/iterator/counting_iterator.hpp>
#include <boost/range/iterator_range.hpp>
#include "generators.h"
using namespace Gudhi;
using namespace Gudhi::witness_complex;
typedef std::vector< Vertex_handle > typeVectorVertex;
typedef Strange_witness_complex< Simplex_tree<> > WitnessComplex;
typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> 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::Euclidean_distance<Traits_base> Euclidean_distance;
typedef CGAL::Search_traits_adapter<
std::ptrdiff_t, Point_d*, Traits_base> STraits;
typedef CGAL::Orthogonal_incremental_neighbor_search<STraits, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>> Neighbor_search;
typedef Neighbor_search::Tree Tree;
typedef Neighbor_search::Distance Distance;
typedef Neighbor_search::iterator KNS_iterator;
typedef 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;
/** 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";
//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++)
{
// while (!res.second)
// {
do chosen_landmark = rand.get_int(0,nbP);
while (std::find(landmarks_ind.begin(), landmarks_ind.end(), chosen_landmark) != landmarks_ind.end());
//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 landmarks_to_witness_complex(Point_Vector &W, int nbL)
{
//********************Preface: origin point
unsigned D = W[0].size();
std::vector<FT> orig_vector;
for (unsigned i = 0; i < D; i++)
orig_vector.push_back(0);
Point_d origin(orig_vector);
//Distance dist;
//dist.transformed_distance(0,1);
//******************** Constructing a WL matrix
int nbP = W.size();
Point_Vector landmarks;
std::vector<int> landmarks_ind;
landmark_choice(W, nbP, nbL, landmarks, landmarks_ind);
STraits traits(&(landmarks[0]));
Euclidean_distance ed;
std::vector< std::vector <int> > WL(nbP);
std::vector< std::vector< typename std::vector<int>::iterator > > ope_limits(nbP);
Tree L(boost::counting_iterator<std::ptrdiff_t>(0),
boost::counting_iterator<std::ptrdiff_t>(nbL),
typename Tree::Splitter(),
traits);
std::cout << "Enter (D+1) nearest landmarks\n";
//std::cout << "Size of the tree is " << L.size() << std::endl;
for (int i = 0; i < nbP; i++) {
//std::cout << "Entered witness number " << i << std::endl;
Point_d& w = W[i];
std::queue< typename std::vector<int>::iterator > ope_queue; // queue of points at (1+epsilon) distance to current landmark
Neighbor_search search(L, w, FT(0), true, CGAL::Distance_adapter<std::ptrdiff_t,Point_d*,Euclidean_distance>(&(landmarks[0])));
Neighbor_search::iterator search_it = search.begin();
//Incremental search and filling WL
while (WL[i].size() < D)
WL[i].push_back((search_it++)->first);
}
write_wl("WL.txt", WL); //!
//******************** Constructng a witness complex
std::cout << "Entered witness complex construction\n";
Simplex_tree<> simplex_tree;
WitnessComplex(WL, simplex_tree, nbL, W[0].size()-1);
//std::cout << simplex_tree << "\n"; //!
write_witness_mesh(W, landmarks_ind, simplex_tree, false, true);
}
/** Write a gnuplot readable file.
* Data range is a random access range of pairs (arg, value)
*/
template < typename Data_range >
void write_data(Data_range & data, std::string filename) {
std::ofstream ofs(filename, std::ofstream::out);
for (auto entry : data)
ofs << entry.first << ", " << entry.second << "\n";
ofs.close();
}
int main(int argc, char * const argv[]) {
if (argc != 4) {
std::cerr << "Usage: " << argv[0]
<< " nbP nbL dim\n";
return 0;
}
int nbP = atoi(argv[1]);
int nbL = atoi(argv[2]);
int dim = atoi(argv[3]);
clock_t start, end;
// Construct the Simplex Tree
Simplex_tree<> simplex_tree;
std::vector< std::pair<int, double> > l_time;
// Read the point file
Point_Vector point_vector;
generate_points_sphere(point_vector, nbP, dim);
std::cout << "Successfully generated " << point_vector.size() << " points.\n";
std::cout << "Ambient dimension is " << point_vector[0].size() << ".\n";
// Choose landmarks
start = clock();
std::vector<std::vector< int > > knn;
landmarks_to_witness_complex(point_vector, nbL);
end = clock();
double time = static_cast<double>(end - start) / CLOCKS_PER_SEC;
std::cout << "Witness complex for " << nbL << " landmarks took "
<< time << " s. \n";
l_time.push_back(std::make_pair(nbP, time));
//write_data(l_time, "w_time.dat");
}
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