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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): Mathieu Carriere
*
* Copyright (C) 2018 INRIA (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/>.
*/
#include <gudhi/Persistence_weighted_gaussian.h>
#include <iostream>
#include <vector>
#include <utility>
using PD = std::vector<std::pair<double,double> >;
using PWG = Gudhi::Persistence_representations::Persistence_weighted_gaussian;
int main(int argc, char** argv) {
std::vector<std::pair<double, double> > persistence1;
std::vector<std::pair<double, double> > persistence2;
persistence1.push_back(std::make_pair(1, 2));
persistence1.push_back(std::make_pair(6, 8));
persistence1.push_back(std::make_pair(0, 4));
persistence1.push_back(std::make_pair(3, 8));
persistence2.push_back(std::make_pair(2, 9));
persistence2.push_back(std::make_pair(1, 6));
persistence2.push_back(std::make_pair(3, 5));
persistence2.push_back(std::make_pair(6, 10));
PWG PWG1(persistence1);
PWG PWG2(persistence2);
double sigma = 1;
double tau = 1;
int m = 1000;
// Linear PWG
std::cout << PWG1.compute_scalar_product (PWG2, sigma, PWG::arctan_weight, m) << std::endl;
std::cout << PWG1.compute_scalar_product (PWG2, sigma, PWG::arctan_weight, -1) << std::endl;
std::cout << PWG1.distance (PWG2, sigma, PWG::arctan_weight, m) << std::endl;
std::cout << PWG1.distance (PWG2, sigma, PWG::arctan_weight, -1) << std::endl;
// Gaussian PWG
std::cout << std::exp( -PWG1.distance (PWG2, sigma, PWG::arctan_weight, m, 2) ) / (2*tau*tau) << std::endl;
std::cout << std::exp( -PWG1.distance (PWG2, sigma, PWG::arctan_weight, -1, 2) ) / (2*tau*tau) << std::endl;
// PSS
PD pd1 = persistence1; int numpts = persistence1.size(); for(int i = 0; i < numpts; i++) pd1.emplace_back(persistence1[i].second,persistence1[i].first);
PD pd2 = persistence2; numpts = persistence2.size(); for(int i = 0; i < numpts; i++) pd2.emplace_back(persistence2[i].second,persistence2[i].first);
PWG pwg1(pd1);
PWG pwg2(pd2);
std::cout << pwg1.compute_scalar_product (pwg2, 2*std::sqrt(sigma), PWG::pss_weight, m) / (16*pi*sigma) << std::endl;
std::cout << pwg1.compute_scalar_product (pwg2, 2*std::sqrt(sigma), PWG::pss_weight, -1) / (16*pi*sigma) << std::endl;
std::cout << pwg1.distance (pwg2, 2*std::sqrt(sigma), PWG::pss_weight, m) / (16*pi*sigma) << std::endl;
std::cout << pwg1.distance (pwg2, 2*std::sqrt(sigma), PWG::pss_weight, -1) / (16*pi*sigma) << std::endl;
return 0;
}
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