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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): Pawel Dlotko
*
* Copyright (C) 2016 Inria
*
* Modification(s):
* - YYYY/MM Author: Description of the modification
*/
#include <gudhi/Persistence_intervals.h>
#include <iostream>
#include <utility>
#include <vector>
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<double, double> min_max_ = p.get_x_range();
std::cout << "Birth-death range : " << min_max_.first << " " << min_max_.second << std::endl;
std::vector<double> 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<std::pair<double, double> > 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<size_t> 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<size_t> 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<double> 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<double> 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<std::pair<double, size_t> > 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;
}
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