diff options
Diffstat (limited to 'example/Witness_complex')
6 files changed, 37 insertions, 393 deletions
diff --git a/example/Witness_complex/CMakeLists.txt b/example/Witness_complex/CMakeLists.txt index cbc53902..a8231392 100644 --- a/example/Witness_complex/CMakeLists.txt +++ b/example/Witness_complex/CMakeLists.txt @@ -13,39 +13,23 @@ install(TARGETS Witness_complex_example_nearest_landmark_table DESTINATION bin) # CGAL and Eigen3 are required for Euclidean version of Witness if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.6.0) add_executable( Witness_complex_example_off example_witness_complex_off.cpp ) - add_executable( Witness_complex_example_strong_off example_strong_witness_complex_off.cpp ) add_executable ( Witness_complex_example_sphere example_witness_complex_sphere.cpp ) - - add_executable ( Witness_complex_example_witness_persistence example_witness_complex_persistence.cpp ) - target_link_libraries(Witness_complex_example_witness_persistence ${Boost_PROGRAM_OPTIONS_LIBRARY}) - - add_executable ( Witness_complex_example_strong_witness_persistence example_strong_witness_persistence.cpp ) - target_link_libraries(Witness_complex_example_strong_witness_persistence ${Boost_PROGRAM_OPTIONS_LIBRARY}) - - if (TBB_FOUND) - target_link_libraries(Witness_complex_example_witness_persistence ${TBB_LIBRARIES}) - target_link_libraries(Witness_complex_example_strong_witness_persistence ${TBB_LIBRARIES}) - endif() + + add_executable( Witness_complex_example_strong_off example_strong_witness_complex_off.cpp ) + target_link_libraries(Witness_complex_example_strong_off) add_test(NAME Witness_complex_example_off_test_torus COMMAND $<TARGET_FILE:Witness_complex_example_off> "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "20" "1.0" "3") + add_test(NAME Witness_complex_example_test_sphere_10 + COMMAND $<TARGET_FILE:Witness_complex_example_sphere> "10") add_test(NAME Witness_complex_example_strong_off_test_torus COMMAND $<TARGET_FILE:Witness_complex_example_strong_off> "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "20" "1.0" "3") - add_test(NAME Witness_complex_example_test_sphere_10 - COMMAND $<TARGET_FILE:Witness_complex_example_sphere> "10") - add_test(NAME Witness_complex_example_test_torus_persistence - COMMAND $<TARGET_FILE:Witness_complex_example_witness_persistence> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-l" "20" "-a" "0.5") - add_test(NAME Witness_complex_example_strong_test_torus_persistence - COMMAND $<TARGET_FILE:Witness_complex_example_strong_witness_persistence> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-l" "20" "-a" "0.5") - + install(TARGETS Witness_complex_example_off DESTINATION bin) - install(TARGETS Witness_complex_example_strong_off DESTINATION bin) install(TARGETS Witness_complex_example_sphere DESTINATION bin) - install(TARGETS Witness_complex_example_witness_persistence DESTINATION bin) - install(TARGETS Witness_complex_example_strong_witness_persistence DESTINATION bin) + install(TARGETS Witness_complex_example_strong_off DESTINATION bin) + endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.6.0) diff --git a/example/Witness_complex/example_strong_witness_complex_off.cpp b/example/Witness_complex/example_strong_witness_complex_off.cpp index 0ee9ee90..346bef6d 100644 --- a/example/Witness_complex/example_strong_witness_complex_off.cpp +++ b/example/Witness_complex/example_strong_witness_complex_off.cpp @@ -23,6 +23,7 @@ #include <gudhi/Simplex_tree.h> #include <gudhi/Euclidean_strong_witness_complex.h> #include <gudhi/pick_n_random_points.h> +#include <gudhi/choose_n_farthest_points.h> #include <gudhi/Points_off_io.h> #include <CGAL/Epick_d.h> @@ -38,10 +39,9 @@ using Point_d = typename K::Point_d; using Witness_complex = Gudhi::witness_complex::Euclidean_strong_witness_complex<K>; using Point_vector = std::vector<Point_d>; -int main(int argc, char * const argv[]) { +int main(int argc, char* const argv[]) { if (argc != 5) { - std::cerr << "Usage: " << argv[0] - << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; + std::cerr << "Usage: " << argv[0] << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; return 0; } @@ -55,25 +55,25 @@ int main(int argc, char * const argv[]) { Point_vector point_vector, landmarks; Gudhi::Points_off_reader<Point_d> off_reader(file_name); if (!off_reader.is_valid()) { - std::cerr << "Strong witness complex - Unable to read file " << file_name << "\n"; - exit(-1); // ----- >> - } + std::cerr << "Strong witness complex - Unable to read file " << file_name << "\n"; + exit(-1); // ----- >> + } point_vector = Point_vector(off_reader.get_point_cloud()); std::cout << "Successfully read " << point_vector.size() << " points.\n"; std::cout << "Ambient dimension is " << point_vector[0].dimension() << ".\n"; - // Choose landmarks - Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks)); + // Choose landmarks (decomment one of the following two lines) + // Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks)); + Gudhi::subsampling::choose_n_farthest_points(K(), point_vector, nbL, Gudhi::subsampling::random_starting_point, + std::back_inserter(landmarks)); // Compute witness complex start = clock(); - Witness_complex witness_complex(landmarks, - point_vector); + Witness_complex witness_complex(landmarks, point_vector); witness_complex.create_complex(simplex_tree, alpha2, lim_dim); end = clock(); - std::cout << "Strong witness complex took " - << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; + std::cout << "Strong witness complex took " << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; std::cout << "Number of simplices is: " << simplex_tree.num_simplices() << "\n"; } diff --git a/example/Witness_complex/example_strong_witness_persistence.cpp b/example/Witness_complex/example_strong_witness_persistence.cpp deleted file mode 100644 index f786fe7b..00000000 --- a/example/Witness_complex/example_strong_witness_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): Siargey Kachanovich - * - * Copyright (C) 2016 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/>. - */ - -#include <gudhi/Simplex_tree.h> -#include <gudhi/Euclidean_strong_witness_complex.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Points_off_io.h> -#include <gudhi/pick_n_random_points.h> - -#include <boost/program_options.hpp> - -#include <CGAL/Epick_d.h> - -#include <string> -#include <vector> -#include <limits> // infinity - -using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; -using Point_d = K::Point_d; - -using Point_vector = std::vector<Point_d>; -using Strong_witness_complex = Gudhi::witness_complex::Euclidean_strong_witness_complex<K>; -using SimplexTree = Gudhi::Simplex_tree<>; - -using Filtration_value = SimplexTree::Filtration_value; - -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<SimplexTree, Field_Zp>; - -void program_options(int argc, char * argv[] - , int & nbL - , std::string & file_name - , std::string & filediag - , Filtration_value & max_squared_alpha - , int & p - , int & dim_max - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string file_name; - std::string filediag; - Filtration_value max_squared_alpha; - int p, nbL, lim_d; - Filtration_value min_persistence; - SimplexTree simplex_tree; - - program_options(argc, argv, nbL, file_name, filediag, max_squared_alpha, p, lim_d, min_persistence); - - // Extract the points from the file file_name - Point_vector witnesses, landmarks; - Gudhi::Points_off_reader<Point_d> off_reader(file_name); - if (!off_reader.is_valid()) { - std::cerr << "Witness complex - Unable to read file " << file_name << "\n"; - exit(-1); // ----- >> - } - witnesses = Point_vector(off_reader.get_point_cloud()); - std::cout << "Successfully read " << witnesses.size() << " points.\n"; - std::cout << "Ambient dimension is " << witnesses[0].dimension() << ".\n"; - - // Choose landmarks from witnesses - Gudhi::subsampling::pick_n_random_points(witnesses, nbL, std::back_inserter(landmarks)); - - // Compute witness complex - Strong_witness_complex strong_witness_complex(landmarks, - witnesses); - - strong_witness_complex.create_complex(simplex_tree, max_squared_alpha, lim_d); - - 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); - - pcoh.compute_persistent_cohomology(min_persistence); - - // Output the diagram in filediag - if (filediag.empty()) { - pcoh.output_diagram(); - } else { - std::ofstream out(filediag); - pcoh.output_diagram(out); - out.close(); - } - - return 0; -} - -void program_options(int argc, char * argv[] - , int & nbL - , std::string & file_name - , std::string & filediag - , Filtration_value & max_squared_alpha - , int & p - , int & dim_max - , Filtration_value & min_persistence) { - namespace po = boost::program_options; - - po::options_description hidden("Hidden options"); - hidden.add_options() - ("input-file", po::value<std::string>(&file_name), - "Name of file containing a point set in off format."); - - po::options_description visible("Allowed options", 100); - Filtration_value default_alpha = std::numeric_limits<Filtration_value>::infinity(); - visible.add_options() - ("help,h", "produce help message") - ("landmarks,l", po::value<int>(&nbL), - "Number of landmarks to choose from the point cloud.") - ("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") - ("max-sq-alpha,a", po::value<Filtration_value>(&max_squared_alpha)->default_value(default_alpha), - "Maximal squared relaxation parameter.") - ("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)->default_value(0), - "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals") - ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(std::numeric_limits<int>::max()), - "Maximal dimension of the strong witness complex we want to compute."); - - 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 Strong witness complex defined on a set of input points.\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; - std::abort(); - } -} - diff --git a/example/Witness_complex/example_witness_complex_off.cpp b/example/Witness_complex/example_witness_complex_off.cpp index b36dac0d..be11c955 100644 --- a/example/Witness_complex/example_witness_complex_off.cpp +++ b/example/Witness_complex/example_witness_complex_off.cpp @@ -4,6 +4,7 @@ #include <gudhi/Simplex_tree.h> #include <gudhi/Euclidean_witness_complex.h> #include <gudhi/pick_n_random_points.h> +#include <gudhi/choose_n_farthest_points.h> #include <gudhi/Points_off_io.h> #include <CGAL/Epick_d.h> @@ -44,8 +45,9 @@ int main(int argc, char * const argv[]) { std::cout << "Successfully read " << point_vector.size() << " points.\n"; std::cout << "Ambient dimension is " << point_vector[0].dimension() << ".\n"; - // Choose landmarks - Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks)); + // Choose landmarks (decomment one of the following two lines) + // Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks)); + Gudhi::subsampling::choose_n_farthest_points(K(), point_vector, nbL, Gudhi::subsampling::random_starting_point, std::back_inserter(landmarks)); // Compute witness complex start = clock(); diff --git a/example/Witness_complex/example_witness_complex_persistence.cpp b/example/Witness_complex/example_witness_complex_persistence.cpp deleted file mode 100644 index a1146922..00000000 --- a/example/Witness_complex/example_witness_complex_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): Siargey Kachanovich - * - * Copyright (C) 2016 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/>. - */ - -#include <gudhi/Simplex_tree.h> -#include <gudhi/Euclidean_witness_complex.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Points_off_io.h> -#include <gudhi/pick_n_random_points.h> - -#include <boost/program_options.hpp> - -#include <CGAL/Epick_d.h> - -#include <string> -#include <vector> -#include <limits> // infinity - -using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; -using Point_d = K::Point_d; - -using Point_vector = std::vector<Point_d>; -using Witness_complex = Gudhi::witness_complex::Euclidean_witness_complex<K>; -using SimplexTree = Gudhi::Simplex_tree<>; - -using Filtration_value = SimplexTree::Filtration_value; - -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<SimplexTree, Field_Zp>; - -void program_options(int argc, char * argv[] - , int & nbL - , std::string & file_name - , std::string & filediag - , Filtration_value & max_squared_alpha - , int & p - , int & dim_max - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string file_name; - std::string filediag; - Filtration_value max_squared_alpha; - int p, nbL, lim_d; - Filtration_value min_persistence; - SimplexTree simplex_tree; - - program_options(argc, argv, nbL, file_name, filediag, max_squared_alpha, p, lim_d, min_persistence); - - // Extract the points from the file file_name - Point_vector witnesses, landmarks; - Gudhi::Points_off_reader<Point_d> off_reader(file_name); - if (!off_reader.is_valid()) { - std::cerr << "Witness complex - Unable to read file " << file_name << "\n"; - exit(-1); // ----- >> - } - witnesses = Point_vector(off_reader.get_point_cloud()); - std::cout << "Successfully read " << witnesses.size() << " points.\n"; - std::cout << "Ambient dimension is " << witnesses[0].dimension() << ".\n"; - - // Choose landmarks from witnesses - Gudhi::subsampling::pick_n_random_points(witnesses, nbL, std::back_inserter(landmarks)); - - // Compute witness complex - Witness_complex witness_complex(landmarks, - witnesses); - - witness_complex.create_complex(simplex_tree, max_squared_alpha, lim_d); - - 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); - - pcoh.compute_persistent_cohomology(min_persistence); - - // Output the diagram in filediag - if (filediag.empty()) { - pcoh.output_diagram(); - } else { - std::ofstream out(filediag); - pcoh.output_diagram(out); - out.close(); - } - - return 0; -} - - -void program_options(int argc, char * argv[] - , int & nbL - , std::string & file_name - , std::string & filediag - , Filtration_value & max_squared_alpha - , int & p - , int & dim_max - , Filtration_value & min_persistence) { - namespace po = boost::program_options; - - po::options_description hidden("Hidden options"); - hidden.add_options() - ("input-file", po::value<std::string>(&file_name), - "Name of file containing a point set in off format."); - - Filtration_value default_alpha = std::numeric_limits<Filtration_value>::infinity(); - po::options_description visible("Allowed options", 100); - visible.add_options() - ("help,h", "produce help message") - ("landmarks,l", po::value<int>(&nbL), - "Number of landmarks to choose from the point cloud.") - ("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") - ("max-sq-alpha,a", po::value<Filtration_value>(&max_squared_alpha)->default_value(default_alpha), - "Maximal squared relaxation parameter.") - ("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)->default_value(0), - "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals") - ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(std::numeric_limits<int>::max()), - "Maximal dimension of the weak witness complex we want to compute."); - - 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 Weak witness complex defined on a set of input points.\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; - std::abort(); - } -} diff --git a/example/Witness_complex/example_witness_complex_sphere.cpp b/example/Witness_complex/example_witness_complex_sphere.cpp index 124fd99b..a6e9b11a 100644 --- a/example/Witness_complex/example_witness_complex_sphere.cpp +++ b/example/Witness_complex/example_witness_complex_sphere.cpp @@ -25,6 +25,7 @@ #include <gudhi/Simplex_tree.h> #include <gudhi/Euclidean_witness_complex.h> #include <gudhi/pick_n_random_points.h> +#include <gudhi/choose_n_farthest_points.h> #include <gudhi/reader_utils.h> #include <CGAL/Epick_d.h> @@ -41,27 +42,25 @@ /** Write a gnuplot readable file. * Data range is a random access range of pairs (arg, value) */ -template < typename Data_range > -void write_data(Data_range & data, std::string filename) { +template <typename Data_range> +void write_data(Data_range& data, std::string filename) { std::ofstream ofs(filename, std::ofstream::out); - for (auto entry : data) - ofs << entry.first << ", " << entry.second << "\n"; + for (auto entry : data) ofs << entry.first << ", " << entry.second << "\n"; ofs.close(); } -int main(int argc, char * const argv[]) { +int main(int argc, char* const argv[]) { using Kernel = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; using Witness_complex = Gudhi::witness_complex::Euclidean_witness_complex<Kernel>; if (argc != 2) { - std::cerr << "Usage: " << argv[0] - << " number_of_landmarks \n"; + std::cerr << "Usage: " << argv[0] << " number_of_landmarks \n"; return 0; } int number_of_landmarks = atoi(argv[1]); - std::vector< std::pair<int, double> > l_time; + std::vector<std::pair<int, double> > l_time; // Generate points for (int nbP = 500; nbP < 10000; nbP += 500) { @@ -75,16 +74,17 @@ int main(int argc, char * const argv[]) { // Choose landmarks start = clock(); - Gudhi::subsampling::pick_n_random_points(point_vector, number_of_landmarks, std::back_inserter(landmarks)); + // Gudhi::subsampling::pick_n_random_points(point_vector, number_of_landmarks, std::back_inserter(landmarks)); + Gudhi::subsampling::choose_n_farthest_points(K(), point_vector, number_of_landmarks, + Gudhi::subsampling::random_starting_point, + std::back_inserter(landmarks)); // Compute witness complex - Witness_complex witness_complex(landmarks, - point_vector); + Witness_complex witness_complex(landmarks, point_vector); witness_complex.create_complex(simplex_tree, 0); end = clock(); double time = static_cast<double>(end - start) / CLOCKS_PER_SEC; - std::cout << "Witness complex for " << number_of_landmarks << " landmarks took " - << time << " s. \n"; + std::cout << "Witness complex for " << number_of_landmarks << " landmarks took " << time << " s. \n"; std::cout << "Number of simplices is: " << simplex_tree.num_simplices() << "\n"; l_time.push_back(std::make_pair(nbP, time)); } |