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-rw-r--r--src/cython/cython/kernels.pyx128
-rw-r--r--src/cython/cython/vectors.pyx68
-rw-r--r--src/cython/include/Kernels_interface.h130
-rw-r--r--src/cython/include/Vectors_interface.h59
4 files changed, 0 insertions, 385 deletions
diff --git a/src/cython/cython/kernels.pyx b/src/cython/cython/kernels.pyx
deleted file mode 100644
index cb8fc0fd..00000000
--- a/src/cython/cython/kernels.pyx
+++ /dev/null
@@ -1,128 +0,0 @@
-from cython cimport numeric
-from libcpp.vector cimport vector
-from libcpp.utility cimport pair
-import os
-
-"""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 <http://www.gnu.org/licenses/>.
-"""
-
-__author__ = "Mathieu Carriere"
-__copyright__ = "Copyright (C) 2018 INRIA"
-__license__ = "GPL v3"
-
-cdef extern from "Kernels_interface.h" namespace "Gudhi::persistence_diagram":
- double sw (vector[pair[double, double]], vector[pair[double, double]], double, int)
- vector[vector[double]] sw_matrix (vector[vector[pair[double, double]]], vector[vector[pair[double, double]]], double, int)
- double pss (vector[pair[double, double]], vector[pair[double, double]], double, int)
- vector[vector[double]] pss_matrix (vector[vector[pair[double, double]]], vector[vector[pair[double, double]]], double, int)
- double pwg (vector[pair[double, double]], vector[pair[double, double]], int, string, double, double, double)
- vector[vector[double]] pwg_matrix (vector[vector[pair[double, double]]], vector[vector[pair[double, double]]], int, string, double, double, double)
-
-def sliced_wasserstein(diagram_1, diagram_2, sigma = 1, N = 100):
- """
-
- :param diagram_1: The first diagram.
- :type diagram_1: vector[pair[double, double]]
- :param diagram_2: The second diagram.
- :type diagram_2: vector[pair[double, double]]
- :param sigma: bandwidth of Gaussian
- :param N: number of directions
-
- :returns: the sliced wasserstein kernel.
- """
- return sw(diagram_1, diagram_2, sigma, N)
-
-def sliced_wasserstein_matrix(diagrams_1, diagrams_2, sigma = 1, N = 100):
- """
-
- :param diagram_1: The first set of diagrams.
- :type diagram_1: vector[vector[pair[double, double]]]
- :param diagram_2: The second set of diagrams.
- :type diagram_2: vector[vector[pair[double, double]]]
- :param sigma: bandwidth of Gaussian
- :param N: number of directions
-
- :returns: the sliced wasserstein kernel matrix.
- """
- return sw_matrix(diagrams_1, diagrams_2, sigma, N)
-
-def persistence_weighted_gaussian(diagram_1, diagram_2, N = 100, weight = "arctan", sigma = 1.0, C = 1.0, p = 1.0):
- """
-
- :param diagram_1: The first diagram.
- :type diagram_1: vector[pair[double, double]]
- :param diagram_2: The second diagram.
- :type diagram_2: vector[pair[double, double]]
- :param N: number of Fourier features
- :param weight: weight to use for the diagram points
- :param sigma: bandwidth of Gaussian
- :param C: cost of arctan persistence weight
- :param p: power of arctan persistence weight
-
- :returns: the persistence weighted gaussian kernel.
- """
- return pwg(diagram_1, diagram_2, N, weight, sigma, C, p)
-
-def persistence_weighted_gaussian_matrix(diagrams_1, diagrams_2, N = 100, weight = "arctan", sigma = 1.0, C = 1.0, p = 1.0):
- """
-
- :param diagram_1: The first set of diagrams.
- :type diagram_1: vector[vector[pair[double, double]]]
- :param diagram_2: The second set of diagrams.
- :type diagram_2: vector[vector[pair[double, double]]]
- :param N: number of Fourier features
- :param weight: weight to use for the diagram points
- :param sigma: bandwidth of Gaussian
- :param C: cost of arctan persistence weight
- :param p: power of arctan persistence weight
-
- :returns: the persistence weighted gaussian kernel matrix.
- """
- return pwg_matrix(diagrams_1, diagrams_2, N, weight, sigma, C, p)
-
-def persistence_scale_space(diagram_1, diagram_2, sigma = 1, N = 100):
- """
-
- :param diagram_1: The first diagram.
- :type diagram_1: vector[pair[double, double]]
- :param diagram_2: The second diagram.
- :type diagram_2: vector[pair[double, double]]
- :param sigma: bandwidth of Gaussian
- :param N: number of Fourier features
-
- :returns: the persistence scale space kernel.
- """
- return pss(diagram_1, diagram_2, sigma, N)
-
-def persistence_scale_space_matrix(diagrams_1, diagrams_2, sigma = 1, N = 100):
- """
-
- :param diagram_1: The first set of diagrams.
- :type diagram_1: vector[vector[pair[double, double]]]
- :param diagram_2: The second set of diagrams.
- :type diagram_2: vector[vector[pair[double, double]]]
- :param sigma: bandwidth of Gaussian
- :param N: number of Fourier features
-
- :returns: the persistence scale space kernel matrix.
- """
- return pss_matrix(diagrams_1, diagrams_2, sigma, N)
diff --git a/src/cython/cython/vectors.pyx b/src/cython/cython/vectors.pyx
deleted file mode 100644
index af53f739..00000000
--- a/src/cython/cython/vectors.pyx
+++ /dev/null
@@ -1,68 +0,0 @@
-from cython cimport numeric
-from libcpp.vector cimport vector
-from libcpp.utility cimport pair
-import os
-
-"""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 <http://www.gnu.org/licenses/>.
-"""
-
-__author__ = "Mathieu Carriere"
-__copyright__ = "Copyright (C) 2018 INRIA"
-__license__ = "GPL v3"
-
-cdef extern from "Vectors_interface.h" namespace "Gudhi::persistence_diagram":
- vector[vector[double]] compute_ls (vector[pair[double, double]], int, double, double, int)
- vector[vector[double]] compute_pim (vector[pair[double, double]], double, double, int, double, double, int, string, double, double, double)
-
-def landscape(diagram, nb_ls = 10, min_x = 0.0, max_x = 1.0, res_x = 100):
- """
-
- :param diagram: The diagram
- :type diagram: vector[pair[double, double]]
- :param nb_ls: Number of landscapes
- :param min_x: Minimum abscissa
- :param max_x: Maximum abscissa
- :param res_x: Number of samples
-
- :returns: the landscape
- """
- return compute_ls(diagram, nb_ls, min_x, max_x, res_x)
-
-def persistence_image(diagram, min_x = 0.0, max_x = 1.0, res_x = 10, min_y = 0.0, max_y = 1.0, res_y = 10, weight = "linear", sigma = 1.0, C = 1.0, p = 1.0):
- """
-
- :param diagram: The diagram
- :type diagram: vector[vector[pair[double, double]]]
- :param min_x: Minimum abscissa
- :param max_x: Maximum abscissa
- :param res_x: Number of abscissa pixels
- :param min_x: Minimum ordinate
- :param max_x: Maximum ordinate
- :param res_x: Number of ordinate pixels
- :param weight: Weight to use for the diagram points
- :param sigma: bandwidth of Gaussian
- :param C: cost of arctan persistence weight
- :param p: power of arctan persistence weight
-
- :returns: the persistence image
- """
- return compute_pim(diagram, min_x, max_x, res_x, min_y, max_y, res_y, weight, sigma, C, p)
diff --git a/src/cython/include/Kernels_interface.h b/src/cython/include/Kernels_interface.h
deleted file mode 100644
index a07d7820..00000000
--- a/src/cython/include/Kernels_interface.h
+++ /dev/null
@@ -1,130 +0,0 @@
-/* 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 <http://www.gnu.org/licenses/>.
- */
-
-#ifndef INCLUDE_KERNELS_INTERFACE_H_
-#define INCLUDE_KERNELS_INTERFACE_H_
-
-#include <gudhi/common_persistence_representations.h>
-#include <gudhi/Sliced_Wasserstein.h>
-#include <gudhi/Persistence_weighted_gaussian.h>
-#include <gudhi/Weight_functions.h>
-
-#include <iostream>
-#include <vector>
-#include <utility> // for std::pair
-
-namespace Gudhi {
-
-namespace persistence_diagram {
-
-
- // *******************
- // Kernel evaluations.
- // *******************
-
- double sw(const std::vector<std::pair<double, double>>& diag1, const std::vector<std::pair<double, double>>& 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<std::pair<double, double>>& diag1, const std::vector<std::pair<double, double>>& diag2, int N, std::string weight, double sigma, double C, double p) {
- Gudhi::Persistence_representations::Weight weight_fn;
- if(weight.compare("linear") == 0) weight_fn = Gudhi::Persistence_representations::linear_weight;
- if(weight.compare("arctan") == 0) weight_fn = Gudhi::Persistence_representations::arctan_weight(C,p);
- if(weight.compare("const") == 0) weight_fn = Gudhi::Persistence_representations::const_weight;
- Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg1(diag1, sigma, N, weight_fn);
- Gudhi::Persistence_representations::Persistence_weighted_gaussian pwg2(diag2, sigma, N, weight_fn);
- return pwg1.compute_scalar_product(pwg2);
- }
-
- double pss(const std::vector<std::pair<double, double>>& diag1, const std::vector<std::pair<double, double>>& diag2, double sigma, int N) {
- std::vector<std::pair<double, double>> pd1 = diag1; int numpts = diag1.size(); for(int i = 0; i < numpts; i++) pd1.emplace_back(diag1[i].second,diag1[i].first);
- std::vector<std::pair<double, double>> 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<std::pair<double, double>>& diag1, const std::vector<std::pair<double, double>>& 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<std::vector<double> > sw_matrix(const std::vector<std::vector<std::pair<double, double> > >& s1, const std::vector<std::vector<std::pair<double, double> > >& s2, double sigma, int N){
- std::vector<std::vector<double> > matrix;
- std::vector<Gudhi::Persistence_representations::Sliced_Wasserstein> 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<Gudhi::Persistence_representations::Sliced_Wasserstein> 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<double> 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<std::vector<double> > pwg_matrix(const std::vector<std::vector<std::pair<double, double> > >& s1, const std::vector<std::vector<std::pair<double, double> > >& s2, int N, std::string weight, double sigma, double C, double p){
- std::vector<std::vector<double> > 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<double> ps; for(int j = 0; j < num_diag_2; j++) ps.push_back(pwg(s1[i], s2[j], N, weight, sigma, C, p)); matrix.push_back(ps);
- }
- return matrix;
- }
-
- std::vector<std::vector<double> > pss_matrix(const std::vector<std::vector<std::pair<double, double> > >& s1, const std::vector<std::vector<std::pair<double, double> > >& s2, double sigma, int N){
- std::vector<std::vector<std::pair<double, double> > > ss1, ss2; std::vector<std::vector<double> > matrix; int num_diag_1 = s1.size(); int num_diag_2 = s2.size();
- for(int i = 0; i < num_diag_1; i++){
- std::vector<std::pair<double, double>> 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<std::pair<double, double>> 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<double> 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_
diff --git a/src/cython/include/Vectors_interface.h b/src/cython/include/Vectors_interface.h
deleted file mode 100644
index 902ccc10..00000000
--- a/src/cython/include/Vectors_interface.h
+++ /dev/null
@@ -1,59 +0,0 @@
-/* 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 <http://www.gnu.org/licenses/>.
- */
-
-#ifndef INCLUDE_VECTORS_INTERFACE_H_
-#define INCLUDE_VECTORS_INTERFACE_H_
-
-#include <gudhi/Persistence_landscape_on_grid_exact.h>
-#include <gudhi/Persistence_heat_maps_exact.h>
-#include <gudhi/Weight_functions.h>
-
-#include <iostream>
-#include <vector>
-#include <utility> // for std::pair
-
-using Weight = std::function<double (std::pair<double,double>) >;
-
-namespace Gudhi {
-
-namespace persistence_diagram {
-
- std::vector<std::vector<double> > compute_ls(const std::vector<std::pair<double, double> >& diag, int nb_ls, double min_x, double max_x, int res_x) {
- Gudhi::Persistence_representations::Persistence_landscape_on_grid_exact L(diag, nb_ls, min_x, max_x, res_x);
- return L.vectorize();
- }
-
- std::vector<std::vector<double> > compute_pim(const std::vector<std::pair<double, double> >& diag, double min_x, double max_x, int res_x, double min_y, double max_y, int res_y, std::string weight, double sigma, double C, double p) {
- Weight weight_fn;
- if(weight.compare("linear") == 0) weight_fn = Gudhi::Persistence_representations::linear_weight;
- if(weight.compare("arctan") == 0) weight_fn = Gudhi::Persistence_representations::arctan_weight(C,p);
- if(weight.compare("const") == 0) weight_fn = Gudhi::Persistence_representations::const_weight;
- Gudhi::Persistence_representations::Persistence_heat_maps_exact P(diag, min_x, max_x, res_x, min_y, max_y, res_y, weight_fn, sigma);
- return P.vectorize();
- }
-
-} // namespace persistence_diagram
-
-} // namespace Gudhi
-
-
-#endif // INCLUDE_VECTORS_INTERFACE_H_
generated by cgit v1.2.3 (git 2.39.1) at 2024-07-02 19:54:33 +0000