/* 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
*
* 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 .
*/
#ifndef INCLUDE_KERNELS_INTERFACE_H_
#define INCLUDE_KERNELS_INTERFACE_H_
#include
#include
#include
#include
#include
#include // for std::pair
namespace Gudhi {
namespace persistence_diagram {
// *******************
// Kernel evaluations.
// *******************
double sw(const std::vector>& diag1, const std::vector>& diag2, double sigma, int N) {
Gudhi::Persistence_representations::Sliced_Wasserstein sw1(diag1, sigma, N);
Gudhi::Persistence_representations::Sliced_Wasserstein sw2(diag2, sigma, N);
return sw1.compute_scalar_product(sw2);
}
double pwg(const std::vector>& diag1, const std::vector>& diag2, double sigma, int N, double C, double p) {
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg1(diag1, sigma, N, Gudhi::Persistence_representations::arctan_weight(C,p));
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(diag2, sigma, N, Gudhi::Persistence_representations::arctan_weight(C,p));
return pwg1.compute_scalar_product(pwg2);
}
double pss(const std::vector>& diag1, const std::vector>& diag2, double sigma, int N) {
std::vector> pd1 = diag1; int numpts = diag1.size(); for(int i = 0; i < numpts; i++) pd1.emplace_back(diag1[i].second,diag1[i].first);
std::vector> pd2 = diag2; numpts = diag2.size(); for(int i = 0; i < numpts; i++) pd2.emplace_back(diag2[i].second,diag2[i].first);
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg1(pd1, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::pss_weight);
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(pd2, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::pss_weight);
return pwg1.compute_scalar_product (pwg2) / (16*Gudhi::Persistence_representations::pi*sigma);
}
double pss_sym(const std::vector>& diag1, const std::vector>& diag2, double sigma, int N) {
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg1(diag1, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::pss_weight);
Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(diag2, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::pss_weight);
return pwg1.compute_scalar_product (pwg2) / (16*Gudhi::Persistence_representations::pi*sigma);
}
// ****************
// Kernel matrices.
// ****************
std::vector > sw_matrix(const std::vector > >& s1, const std::vector > >& s2, double sigma, int N){
std::vector > matrix;
std::vector ss1;
int num_diag_1 = s1.size(); for(int i = 0; i < num_diag_1; i++){Gudhi::Persistence_representations::Sliced_Wasserstein sw1(s1[i], sigma, N); ss1.push_back(sw1);}
std::vector ss2;
int num_diag_2 = s2.size(); for(int i = 0; i < num_diag_2; i++){Gudhi::Persistence_representations::Sliced_Wasserstein sw2(s2[i], sigma, N); ss2.push_back(sw2);}
for(int i = 0; i < num_diag_1; i++){
std::cout << 100.0*i/num_diag_1 << " %" << std::endl;
std::vector ps; for(int j = 0; j < num_diag_2; j++) ps.push_back(ss1[i].compute_scalar_product(ss2[j])); matrix.push_back(ps);
}
return matrix;
}
std::vector > pwg_matrix(const std::vector > >& s1, const std::vector > >& s2, double sigma, int N, double C, double p){
std::vector > matrix; int num_diag_1 = s1.size(); int num_diag_2 = s2.size();
for(int i = 0; i < num_diag_1; i++){
std::cout << 100.0*i/num_diag_1 << " %" << std::endl;
std::vector ps; for(int j = 0; j < num_diag_2; j++) ps.push_back(pwg(s1[i], s2[j], sigma, N, C, p)); matrix.push_back(ps);
}
return matrix;
}
std::vector > pss_matrix(const std::vector > >& s1, const std::vector > >& s2, double sigma, int N){
std::vector > > ss1, ss2; std::vector > matrix; int num_diag_1 = s1.size(); int num_diag_2 = s2.size();
for(int i = 0; i < num_diag_1; i++){
std::vector> pd1 = s1[i]; int numpts = s1[i].size();
for(int j = 0; j < numpts; j++) pd1.emplace_back(s1[i][j].second,s1[i][j].first);
ss1.push_back(pd1);
}
for(int i = 0; i < num_diag_2; i++){
std::vector> pd2 = s2[i]; int numpts = s2[i].size();
for(int j = 0; j < numpts; j++) pd2.emplace_back(s2[i][j].second,s2[i][j].first);
ss2.push_back(pd2);
}
for(int i = 0; i < num_diag_1; i++){
std::cout << 100.0*i/num_diag_1 << " %" << std::endl;
std::vector ps; for(int j = 0; j < num_diag_2; j++) ps.push_back(pss_sym(ss1[i], ss2[j], sigma, N)); matrix.push_back(ps);
}
return matrix;
}
} // namespace persistence_diagram
} // namespace Gudhi
#endif // INCLUDE_KERNELS_INTERFACE_H_