/* 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): Pawel Dlotko
*
* Copyright (C) 2016 Inria
*
* 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
using Persistence_intervals = Gudhi::Persistence_representations::Persistence_intervals;
int main(int argc, char** argv) {
if (argc != 2) {
std::cout << "To run this program, please provide the name of a file with persistence diagram \n";
return 1;
}
Persistence_intervals p(argv[1]);
std::pair min_max_ = p.get_x_range();
std::cout << "Birth-death range : " << min_max_.first << " " << min_max_.second << std::endl;
std::vector dominant_ten_intervals_length = p.length_of_dominant_intervals(10);
std::cout << "Length of ten dominant intervals : " << std::endl;
for (size_t i = 0; i != dominant_ten_intervals_length.size(); ++i) {
std::cout << dominant_ten_intervals_length[i] << std::endl;
}
std::vector > ten_dominant_intervals = p.dominant_intervals(10);
std::cout << "Here are the dominant intervals : " << std::endl;
for (size_t i = 0; i != ten_dominant_intervals.size(); ++i) {
std::cout << "( " << ten_dominant_intervals[i].first << "," << ten_dominant_intervals[i].second << std::endl;
}
std::vector histogram = p.histogram_of_lengths(10);
std::cout << "Here is the histogram of barcode's length : " << std::endl;
for (size_t i = 0; i != histogram.size(); ++i) {
std::cout << histogram[i] << " ";
}
std::cout << std::endl;
std::vector cumulative_histogram = p.cumulative_histogram_of_lengths(10);
std::cout << "Cumulative histogram : " << std::endl;
for (size_t i = 0; i != cumulative_histogram.size(); ++i) {
std::cout << cumulative_histogram[i] << " ";
}
std::cout << std::endl;
std::vector char_funct_diag = p.characteristic_function_of_diagram(min_max_.first, min_max_.second);
std::cout << "Characteristic function of diagram : " << std::endl;
for (size_t i = 0; i != char_funct_diag.size(); ++i) {
std::cout << char_funct_diag[i] << " ";
}
std::cout << std::endl;
std::vector cumul_char_funct_diag =
p.cumulative_characteristic_function_of_diagram(min_max_.first, min_max_.second);
std::cout << "Cumulative characteristic function of diagram : " << std::endl;
for (size_t i = 0; i != cumul_char_funct_diag.size(); ++i) {
std::cout << cumul_char_funct_diag[i] << " ";
}
std::cout << std::endl;
std::cout << "Persistence Betti numbers \n";
std::vector > pbns = p.compute_persistent_betti_numbers();
for (size_t i = 0; i != pbns.size(); ++i) {
std::cout << pbns[i].first << " " << pbns[i].second << std::endl;
}
return 0;
}