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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/Witness_complex.h>
#include <gudhi/Construct_closest_landmark_table.h>
#include <gudhi/pick_n_random_points.h>
#include <gudhi/reader_utils.h>
#include <iostream>
#include <fstream>
#include <ctime>
#include <utility>
#include <string>
#include <vector>
#include "generators.h"
/** 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 != 2) {
std::cerr << "Usage: " << argv[0]
<< " number_of_landmarks \n";
return 0;
}
int number_of_landmarks = atoi(argv[1]);
clock_t start, end;
// Construct the Simplex Tree
Gudhi::Simplex_tree<> simplex_tree;
std::vector< std::pair<int, double> > l_time;
// Read the point file
for (int nbP = 500; nbP < 10000; nbP += 500) {
Point_Vector point_vector, landmarks;
generate_points_sphere(point_vector, nbP, 4);
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;
Gudhi::subsampling::pick_n_random_points(point_vector, 100, std::back_inserter(landmarks));
Gudhi::witness_complex::construct_closest_landmark_table(point_vector, landmarks, knn);
// Compute witness complex
Gudhi::witness_complex::witness_complex(knn, number_of_landmarks, point_vector[0].size(), simplex_tree);
end = clock();
double time = static_cast<double>(end - start) / CLOCKS_PER_SEC;
std::cout << "Witness complex for " << number_of_landmarks << " landmarks took "
<< time << " s. \n";
std::cout << "Number of simplices is: " << simplex_tree.num_simplices() << "\n";
l_time.push_back(std::make_pair(nbP, time));
}
write_data(l_time, "w_time.dat");
}
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