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author | Gard Spreemann <gspr@nonempty.org> | 2019-09-25 14:29:41 +0200 |
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committer | Gard Spreemann <gspr@nonempty.org> | 2019-09-25 14:29:41 +0200 |
commit | 599d68cd916f533bdb66dd9e684dd5703233b6bb (patch) | |
tree | 4b825dc642cb6eb9a060e54bf8d69288fbee4904 /utilities/Rips_complex/rips_correlation_matrix_persistence.cpp | |
parent | a2e642954ae39025e041471d486ecbac25dff440 (diff) |
Delete all files in order to incorporate upstream's move to git.
Diffstat (limited to 'utilities/Rips_complex/rips_correlation_matrix_persistence.cpp')
-rw-r--r-- | utilities/Rips_complex/rips_correlation_matrix_persistence.cpp | 171 |
1 files changed, 0 insertions, 171 deletions
diff --git a/utilities/Rips_complex/rips_correlation_matrix_persistence.cpp b/utilities/Rips_complex/rips_correlation_matrix_persistence.cpp deleted file mode 100644 index 287e8915..00000000 --- a/utilities/Rips_complex/rips_correlation_matrix_persistence.cpp +++ /dev/null @@ -1,171 +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): Pawel Dlotko, Vincent Rouvreau - * - * Copyright (C) 2016 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/>. - */ - -#include <gudhi/Rips_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/reader_utils.h> -#include <gudhi/writing_persistence_to_file.h> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> -#include <limits> // infinity -#include <algorithm> // for sort - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; -using Filtration_value = Simplex_tree::Filtration_value; -using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>; -using Correlation_matrix = std::vector<std::vector<Filtration_value>>; -using intervals_common = Gudhi::Persistence_interval_common<double, int>; - -void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag, - Filtration_value& correlation_min, int& dim_max, int& p, Filtration_value& min_persistence); - -int main(int argc, char* argv[]) { - std::string csv_matrix_file; - std::string filediag; - Filtration_value correlation_min; - int dim_max; - int p; - Filtration_value min_persistence; - - program_options(argc, argv, csv_matrix_file, filediag, correlation_min, dim_max, p, min_persistence); - - Correlation_matrix correlations = - Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_matrix_file); - - Filtration_value threshold = 0; - - // Given a correlation matrix M, we compute component-wise M'[i,j] = 1-M[i,j] to get a distance matrix: - for (size_t i = 0; i != correlations.size(); ++i) { - for (size_t j = 0; j != correlations[i].size(); ++j) { - correlations[i][j] = 1 - correlations[i][j]; - // Here we make sure that the values of corelations lie between -1 and 1. - // If not, we throw an exception. - if ((correlations[i][j] < -1) || (correlations[i][j] > 1)) { - std::cerr << "The input matrix is not a correlation matrix. The program will now terminate. \n"; - throw "The input matrix is not a correlation matrix. The program will now terminate. \n"; - } - if (correlations[i][j] > threshold) threshold = correlations[i][j]; - } - } - - Rips_complex rips_complex_from_file(correlations, threshold); - - // Construct the Rips complex in a Simplex Tree - Simplex_tree simplex_tree; - - rips_complex_from_file.create_complex(simplex_tree, dim_max); - std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << simplex_tree.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - simplex_tree.initialize_filtration(); - - // Compute the persistence diagram of the complex - Persistent_cohomology pcoh(simplex_tree); - // initializes the coefficient field for homology - pcoh.init_coefficients(p); - // compute persistence - pcoh.compute_persistent_cohomology(min_persistence); - - // invert the persistence diagram. The reason for this procedure is the following: - // The input to the program is a corelation matrix M. When processing it, it is - // turned into 1-M and the obtained persistence intervals are in '1-M' units. - // Below we reverse every (birth,death) pair into (1-birth, 1-death) pair - // so that the input and the output to the program is expressed in the same - // units. - auto pairs = pcoh.get_persistent_pairs(); - std::vector<intervals_common> processed_persistence_intervals; - processed_persistence_intervals.reserve(pairs.size()); - for (auto pair : pairs) { - double birth = 1 - simplex_tree.filtration(get<0>(pair)); - double death = 1 - simplex_tree.filtration(get<1>(pair)); - unsigned dimension = (unsigned)simplex_tree.dimension(get<0>(pair)); - int field = get<2>(pair); - processed_persistence_intervals.push_back(intervals_common(birth, death, dimension, field)); - } - - // sort the processed intervals: - std::sort(processed_persistence_intervals.begin(), processed_persistence_intervals.end()); - - // and write them to a file - if (filediag.empty()) { - write_persistence_intervals_to_stream(processed_persistence_intervals); - } else { - std::ofstream out(filediag); - write_persistence_intervals_to_stream(processed_persistence_intervals, out); - } - return 0; -} - -void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag, - Filtration_value& correlation_min, int& dim_max, int& p, Filtration_value& min_persistence) { - namespace po = boost::program_options; - po::options_description hidden("Hidden options"); - hidden.add_options()( - "input-file", po::value<std::string>(&csv_matrix_file), - "Name of file containing a corelation matrix. Can be square or lower triangular matrix. Separator is ';'."); - po::options_description visible("Allowed options", 100); - visible.add_options()("help,h", "produce help message")( - "output-file,o", po::value<std::string>(&filediag)->default_value(std::string()), - "Name of file in which the persistence diagram is written. Default print in std::cout")( - "min-edge-corelation,c", po::value<Filtration_value>(&correlation_min)->default_value(0), - "Minimal corelation of an edge for the Rips complex construction.")( - "cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), - "Maximal dimension of the Rips complex we want to compute.")( - "field-charac,p", po::value<int>(&p)->default_value(11), - "Characteristic p of the coefficient field Z/pZ for computing homology.")( - "min-persistence,m", po::value<Filtration_value>(&min_persistence), - "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length " - "intervals"); - - po::positional_options_description pos; - pos.add("input-file", 1); - - po::options_description all; - all.add(visible).add(hidden); - - po::variables_map vm; - po::store(po::command_line_parser(argc, argv).options(all).positional(pos).run(), vm); - po::notify(vm); - - if (vm.count("help") || !vm.count("input-file")) { - std::cout << std::endl; - std::cout << "Compute the persistent homology with coefficient field Z/pZ \n"; - std::cout << "of a Rips complex defined on a corelation matrix.\n \n"; - std::cout << "The output diagram contains one bar per line, written with the convention: \n"; - std::cout << " p dim b d \n"; - std::cout << "where dim is the dimension of the homological feature,\n"; - std::cout << "b and d are respectively the birth and death of the feature and \n"; - std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl; - - std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; - std::cout << visible << std::endl; - exit(-1); - } -} |