/* 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 // 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::Persistence_weighted_gaussian::arctan_weight(C,p)); Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(diag2, sigma, N, Gudhi::Persistence_representations::Persistence_weighted_gaussian::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::Persistence_weighted_gaussian::pss_weight); Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(pd2, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::Persistence_weighted_gaussian::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::Persistence_weighted_gaussian::pss_weight); Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(diag2, 2*std::sqrt(sigma), N, Gudhi::Persistence_representations::Persistence_weighted_gaussian::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_