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Diffstat (limited to 'src/Persistence_representations/include/gudhi/Persistence_image.h')
-rw-r--r-- | src/Persistence_representations/include/gudhi/Persistence_image.h | 126 |
1 files changed, 0 insertions, 126 deletions
diff --git a/src/Persistence_representations/include/gudhi/Persistence_image.h b/src/Persistence_representations/include/gudhi/Persistence_image.h deleted file mode 100644 index 76b34d8d..00000000 --- a/src/Persistence_representations/include/gudhi/Persistence_image.h +++ /dev/null @@ -1,126 +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 (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/>. - */ - -#ifndef PERSISTENCE_IMAGE_H_ -#define PERSISTENCE_IMAGE_H_ - -// gudhi include -#include <gudhi/read_persistence_from_file.h> -#include <gudhi/common_persistence_representations.h> -#include <gudhi/Weight_functions.h> -#include <gudhi/Debug_utils.h> - -// standard include -#include <cmath> -#include <iostream> -#include <vector> -#include <limits> -#include <fstream> -#include <sstream> -#include <algorithm> -#include <string> -#include <utility> -#include <functional> - -namespace Gudhi { -namespace Persistence_representations { - -/** - * \class Persistence_image gudhi/Persistence_image.h - * \brief A class implementing the persistence images. - * - * \ingroup Persistence_representations - * - * \details - * - * Persistence images are a way to build images from persistence diagrams. Roughly, the idea is to center Gaussians on each diagram point, with a weight that usually depends on - * the distance to the diagonal, so that the diagram is turned into a function, and then to discretize the plane into pixels, and integrate this function on each pixel. - * See \cite Persistence_Images_2017 for more details. - * -**/ - -class Persistence_image { - - protected: - Persistence_diagram diagram; - int res_x, res_y; - double min_x, max_x, min_y, max_y; - Weight weight; - double sigma; - - public: - - /** \brief Persistence Image constructor. - * \ingroup Persistence_image - * - * @param[in] _diagram persistence diagram. - * @param[in] _min_x minimum value of pixel abscissa. - * @param[in] _max_x maximum value of pixel abscissa. - * @param[in] _res_x number of pixels for the x-direction. - * @param[in] _min_y minimum value of pixel ordinate. - * @param[in] _max_y maximum value of pixel ordinate. - * @param[in] _res_y number of pixels for the y-direction. - * @param[in] _weight weight function for the Gaussians. - * @param[in] _sigma bandwidth parameter for the Gaussians. - * - */ - Persistence_image(const Persistence_diagram & _diagram, double _min_x = 0.0, double _max_x = 1.0, int _res_x = 10, double _min_y = 0.0, double _max_y = 1.0, int _res_y = 10, const Weight & _weight = arctan_weight(1,1), double _sigma = 1.0){ - diagram = _diagram; min_x = _min_x; max_x = _max_x; res_x = _res_x; min_y = _min_y; max_y = _max_y; res_y = _res_y, weight = _weight; sigma = _sigma; - } - - /** \brief Computes the persistence image of a diagram. - * \ingroup Persistence_image - * - */ - std::vector<std::vector<double> > vectorize() const { - std::vector<std::vector<double> > im; for(int i = 0; i < res_y; i++) im.emplace_back(); - double step_x = (max_x - min_x)/res_x; double step_y = (max_y - min_y)/res_y; - - int num_pts = diagram.size(); - - for(int i = 0; i < res_y; i++){ - double y = min_y + i*step_y; - for(int j = 0; j < res_x; j++){ - double x = min_x + j*step_x; - - double pixel_value = 0; - for(int k = 0; k < num_pts; k++){ - double px = diagram[k].first; double py = diagram[k].second; - pixel_value += weight(std::pair<double,double>(px,py)) * std::exp( -((x-px)*(x-px) + (y-(py-px))*(y-(py-px))) / (2*sigma*sigma) ) / (sigma*std::sqrt(2*pi)); - } - im[i].push_back(pixel_value); - - } - } - - return im; - - } - - - - -}; // class Persistence_image -} // namespace Persistence_representations -} // namespace Gudhi - -#endif // PERSISTENCE_IMAGE_H_ |