/* 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();
}