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Diffstat (limited to 'example')
81 files changed, 0 insertions, 6050 deletions
diff --git a/example/Alpha_complex/Alpha_complex_from_off.cpp b/example/Alpha_complex/Alpha_complex_from_off.cpp deleted file mode 100644 index d411e90a..00000000 --- a/example/Alpha_complex/Alpha_complex_from_off.cpp +++ /dev/null @@ -1,63 +0,0 @@ -#include <gudhi/Alpha_complex.h> -// to construct a simplex_tree from alpha complex -#include <gudhi/Simplex_tree.h> - -#include <CGAL/Epick_d.h> - -#include <iostream> -#include <string> - -void usage(int nbArgs, char * const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " filename.off alpha_square_max_value [ouput_file.txt]\n"; - std::cerr << " i.e.: " << progName << " ../../data/points/alphacomplexdoc.off 60.0\n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 3) && (argc != 4)) usage(argc, (argv[0] - 1)); - - std::string off_file_name {argv[1]}; - double alpha_square_max_value {atof(argv[2])}; - - // ---------------------------------------------------------------------------- - // Init of an alpha complex from an OFF file - // ---------------------------------------------------------------------------- - using Kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >; - Gudhi::alpha_complex::Alpha_complex<Kernel> alpha_complex_from_file(off_file_name); - - std::streambuf* streambufffer; - std::ofstream ouput_file_stream; - - if (argc == 4) { - ouput_file_stream.open(std::string(argv[3])); - streambufffer = ouput_file_stream.rdbuf(); - } else { - streambufffer = std::cout.rdbuf(); - } - - Gudhi::Simplex_tree<> simplex; - if (alpha_complex_from_file.create_complex(simplex, alpha_square_max_value)) { - std::ostream output_stream(streambufffer); - - // ---------------------------------------------------------------------------- - // Display information about the alpha complex - // ---------------------------------------------------------------------------- - output_stream << "Alpha complex is of dimension " << simplex.dimension() << - " - " << simplex.num_simplices() << " simplices - " << - simplex.num_vertices() << " vertices." << std::endl; - - output_stream << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : simplex.filtration_simplex_range()) { - output_stream << " ( "; - for (auto vertex : simplex.simplex_vertex_range(f_simplex)) { - output_stream << vertex << " "; - } - output_stream << ") -> " << "[" << simplex.filtration(f_simplex) << "] "; - output_stream << std::endl; - } - } - ouput_file_stream.close(); - return 0; -} diff --git a/example/Alpha_complex/Alpha_complex_from_points.cpp b/example/Alpha_complex/Alpha_complex_from_points.cpp deleted file mode 100644 index c19f7cc8..00000000 --- a/example/Alpha_complex/Alpha_complex_from_points.cpp +++ /dev/null @@ -1,68 +0,0 @@ -#include <gudhi/Alpha_complex.h> -// to construct a simplex_tree from alpha complex -#include <gudhi/Simplex_tree.h> - -#include <CGAL/Epick_d.h> - -#include <iostream> -#include <string> -#include <vector> -#include <limits> // for numeric limits - -using Kernel = CGAL::Epick_d< CGAL::Dimension_tag<2> >; -using Point = Kernel::Point_d; -using Vector_of_points = std::vector<Point>; - -void usage(int nbArgs, char * const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " [alpha_square_max_value]\n"; - std::cerr << " i.e.: " << progName << " 60.0\n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 1) && (argc != 2)) usage(argc, (argv[0] - 1)); - - // Delaunay complex if alpha_square_max_value is not given by the user. - double alpha_square_max_value {std::numeric_limits<double>::infinity()}; - if (argc == 2) - alpha_square_max_value = atof(argv[1]); - - // ---------------------------------------------------------------------------- - // Init of a list of points - // ---------------------------------------------------------------------------- - Vector_of_points points; - points.push_back(Point(1.0, 1.0)); - points.push_back(Point(7.0, 0.0)); - points.push_back(Point(4.0, 6.0)); - points.push_back(Point(9.0, 6.0)); - points.push_back(Point(0.0, 14.0)); - points.push_back(Point(2.0, 19.0)); - points.push_back(Point(9.0, 17.0)); - - // ---------------------------------------------------------------------------- - // Init of an alpha complex from the list of points - // ---------------------------------------------------------------------------- - Gudhi::alpha_complex::Alpha_complex<Kernel> alpha_complex_from_points(points); - - Gudhi::Simplex_tree<> simplex; - if (alpha_complex_from_points.create_complex(simplex, alpha_square_max_value)) { - // ---------------------------------------------------------------------------- - // Display information about the alpha complex - // ---------------------------------------------------------------------------- - std::cout << "Alpha complex is of dimension " << simplex.dimension() << - " - " << simplex.num_simplices() << " simplices - " << - simplex.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:" << std::endl; - for (auto f_simplex : simplex.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : simplex.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " << "[" << simplex.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - } - return 0; -} diff --git a/example/Alpha_complex/CMakeLists.txt b/example/Alpha_complex/CMakeLists.txt deleted file mode 100644 index 2fc62452..00000000 --- a/example/Alpha_complex/CMakeLists.txt +++ /dev/null @@ -1,35 +0,0 @@ -project(Alpha_complex_examples) - -# need CGAL 4.7 -# cmake -DCGAL_DIR=~/workspace/CGAL-4.7 .. -if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) - add_executable ( Alpha_complex_example_from_points Alpha_complex_from_points.cpp ) - target_link_libraries(Alpha_complex_example_from_points ${CGAL_LIBRARY}) - add_executable ( Alpha_complex_example_from_off Alpha_complex_from_off.cpp ) - target_link_libraries(Alpha_complex_example_from_off ${CGAL_LIBRARY}) - if (TBB_FOUND) - target_link_libraries(Alpha_complex_example_from_points ${TBB_LIBRARIES}) - target_link_libraries(Alpha_complex_example_from_off ${TBB_LIBRARIES}) - endif() - - add_test(NAME Alpha_complex_example_from_points COMMAND $<TARGET_FILE:Alpha_complex_example_from_points>) - - add_test(NAME Alpha_complex_example_from_off_60 COMMAND $<TARGET_FILE:Alpha_complex_example_from_off> - "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "60.0" "${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_result_60.txt") - add_test(NAME Alpha_complex_example_from_off_32 COMMAND $<TARGET_FILE:Alpha_complex_example_from_off> - "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "32.0" "${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_result_32.txt") - if (DIFF_PATH) - # Do not forget to copy test results files in current binary dir - file(COPY "alphaoffreader_for_doc_32.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - file(COPY "alphaoffreader_for_doc_60.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - - add_test(Alpha_complex_example_from_off_60_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_result_60.txt ${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_for_doc_60.txt) - add_test(Alpha_complex_example_from_off_32_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_result_32.txt ${CMAKE_CURRENT_BINARY_DIR}/alphaoffreader_for_doc_32.txt) - endif() - - install(TARGETS Alpha_complex_example_from_points DESTINATION bin) - install(TARGETS Alpha_complex_example_from_off DESTINATION bin) - -endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) diff --git a/example/Alpha_complex/alphaoffreader_for_doc_32.txt b/example/Alpha_complex/alphaoffreader_for_doc_32.txt deleted file mode 100644 index 13183e86..00000000 --- a/example/Alpha_complex/alphaoffreader_for_doc_32.txt +++ /dev/null @@ -1,22 +0,0 @@ -Alpha complex is of dimension 2 - 20 simplices - 7 vertices. -Iterator on alpha complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 3 2 ) -> [6.25] - ( 5 4 ) -> [7.25] - ( 2 0 ) -> [8.5] - ( 1 0 ) -> [9.25] - ( 3 1 ) -> [10] - ( 2 1 ) -> [11.25] - ( 3 2 1 ) -> [12.5] - ( 2 1 0 ) -> [12.9959] - ( 6 5 ) -> [13.25] - ( 4 2 ) -> [20] - ( 6 4 ) -> [22.7367] - ( 6 5 4 ) -> [22.7367] - ( 6 3 ) -> [30.25] diff --git a/example/Alpha_complex/alphaoffreader_for_doc_60.txt b/example/Alpha_complex/alphaoffreader_for_doc_60.txt deleted file mode 100644 index 71f29a00..00000000 --- a/example/Alpha_complex/alphaoffreader_for_doc_60.txt +++ /dev/null @@ -1,27 +0,0 @@ -Alpha complex is of dimension 2 - 25 simplices - 7 vertices. -Iterator on alpha complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 3 2 ) -> [6.25] - ( 5 4 ) -> [7.25] - ( 2 0 ) -> [8.5] - ( 1 0 ) -> [9.25] - ( 3 1 ) -> [10] - ( 2 1 ) -> [11.25] - ( 3 2 1 ) -> [12.5] - ( 2 1 0 ) -> [12.9959] - ( 6 5 ) -> [13.25] - ( 4 2 ) -> [20] - ( 6 4 ) -> [22.7367] - ( 6 5 4 ) -> [22.7367] - ( 6 3 ) -> [30.25] - ( 6 2 ) -> [36.5] - ( 6 3 2 ) -> [36.5] - ( 6 4 2 ) -> [37.2449] - ( 4 0 ) -> [59.7107] - ( 4 2 0 ) -> [59.7107] diff --git a/example/Bitmap_cubical_complex/CMakeLists.txt b/example/Bitmap_cubical_complex/CMakeLists.txt deleted file mode 100644 index dc659f2d..00000000 --- a/example/Bitmap_cubical_complex/CMakeLists.txt +++ /dev/null @@ -1,10 +0,0 @@ -project(Bitmap_cubical_complex_examples) - -add_executable ( Random_bitmap_cubical_complex Random_bitmap_cubical_complex.cpp ) -if (TBB_FOUND) - target_link_libraries(Random_bitmap_cubical_complex ${TBB_LIBRARIES}) -endif() -add_test(NAME Bitmap_cubical_complex_example_random COMMAND $<TARGET_FILE:Random_bitmap_cubical_complex> - "2" "100" "100") - -install(TARGETS Random_bitmap_cubical_complex DESTINATION bin) diff --git a/example/Bitmap_cubical_complex/Random_bitmap_cubical_complex.cpp b/example/Bitmap_cubical_complex/Random_bitmap_cubical_complex.cpp deleted file mode 100644 index 6eb24040..00000000 --- a/example/Bitmap_cubical_complex/Random_bitmap_cubical_complex.cpp +++ /dev/null @@ -1,82 +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 - * - * Copyright (C) 2015 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/>. - */ - -// for persistence algorithm -#include <gudhi/reader_utils.h> -#include <gudhi/Bitmap_cubical_complex.h> -#include <gudhi/Persistent_cohomology.h> - -// standard stuff -#include <iostream> -#include <sstream> -#include <vector> - -int main(int argc, char** argv) { - srand(time(0)); - - std::cout - << "This program computes persistent homology, by using bitmap_cubical_complex class, of cubical " - << "complexes. The first parameter of the program is the dimension D of the bitmap. The next D parameters are " - << "number of top dimensional cubes in each dimension of the bitmap. The program will create random cubical " - << "complex of that sizes and compute persistent homology of it." << std::endl; - - int p = 2; - double min_persistence = 0; - - if (argc < 3) { - std::cerr << "Wrong number of parameters, the program will now terminate\n"; - return 1; - } - - size_t dimensionOfBitmap = (size_t)atoi(argv[1]); - std::vector<unsigned> sizes; - size_t multipliers = 1; - for (size_t dim = 0; dim != dimensionOfBitmap; ++dim) { - unsigned sizeInThisDimension = (unsigned)atoi(argv[2 + dim]); - sizes.push_back(sizeInThisDimension); - multipliers *= sizeInThisDimension; - } - - std::vector<double> data; - for (size_t i = 0; i != multipliers; ++i) { - data.push_back(rand() / static_cast<double>(RAND_MAX)); - } - - typedef Gudhi::cubical_complex::Bitmap_cubical_complex_base<double> Bitmap_cubical_complex_base; - typedef Gudhi::cubical_complex::Bitmap_cubical_complex<Bitmap_cubical_complex_base> Bitmap_cubical_complex; - Bitmap_cubical_complex b(sizes, data); - - // Compute the persistence diagram of the complex - typedef Gudhi::persistent_cohomology::Field_Zp Field_Zp; - typedef Gudhi::persistent_cohomology::Persistent_cohomology<Bitmap_cubical_complex, Field_Zp> Persistent_cohomology; - Persistent_cohomology pcoh(b); - pcoh.init_coefficients(p); // initializes the coefficient field for homology - pcoh.compute_persistent_cohomology(min_persistence); - - std::stringstream ss; - ss << "randomComplex_persistence"; - std::ofstream out(ss.str().c_str()); - pcoh.output_diagram(out); - out.close(); - - return 0; -} diff --git a/example/Bottleneck_distance/CMakeLists.txt b/example/Bottleneck_distance/CMakeLists.txt deleted file mode 100644 index c6f10127..00000000 --- a/example/Bottleneck_distance/CMakeLists.txt +++ /dev/null @@ -1,21 +0,0 @@ -project(Bottleneck_distance_examples) - -if (NOT CGAL_VERSION VERSION_LESS 4.8.1) - add_executable (bottleneck_basic_example bottleneck_basic_example.cpp) - add_executable (alpha_rips_persistence_bottleneck_distance alpha_rips_persistence_bottleneck_distance.cpp) - target_link_libraries(alpha_rips_persistence_bottleneck_distance ${Boost_PROGRAM_OPTIONS_LIBRARY}) - - if (TBB_FOUND) - target_link_libraries(alpha_rips_persistence_bottleneck_distance ${TBB_LIBRARIES}) - target_link_libraries(bottleneck_basic_example ${TBB_LIBRARIES}) - endif(TBB_FOUND) - - add_test(NAME Bottleneck_distance_example_basic COMMAND $<TARGET_FILE:bottleneck_basic_example>) - add_test(NAME Bottleneck_distance_example_alpha_rips_persistence_bottleneck - COMMAND $<TARGET_FILE:alpha_rips_persistence_bottleneck_distance> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.15" "-m" "0.12" "-d" "3" "-p" "3") - - install(TARGETS bottleneck_basic_example DESTINATION bin) - install(TARGETS alpha_rips_persistence_bottleneck_distance DESTINATION bin) - -endif (NOT CGAL_VERSION VERSION_LESS 4.8.1) diff --git a/example/Bottleneck_distance/README b/example/Bottleneck_distance/README deleted file mode 100644 index 01bcd74a..00000000 --- a/example/Bottleneck_distance/README +++ /dev/null @@ -1,19 +0,0 @@ -# Bottleneck_distance #
-
-## `alpha_rips_persistence_bottleneck_distance` ##
-This program computes the persistent homology with coefficient field Z/pZ of a Rips complex defined on a set of input points. The output diagram contains one bar per line, written with the convention:
-
-`p dim birth death`
-
-where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients.
-
-Usage:
-`alpha_rips_persistence_bottleneck_distance [options] <OFF input file>`
-
-Allowed options:
-
-* `-h [ --help ]` Produce help message
-* `-r [ --max-edge-length ]` (default = inf) Maximal length of an edge for the Rips complex construction.`
-* `-d [ --cpx-dimension ]` (default = 1) Maximal dimension of the Rips complex we want to compute.`
-* `-p [ --field-charac ]` (default = 11) Characteristic p of the coefficient field Z/pZ for computing homology.
-* `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals.
diff --git a/example/Bottleneck_distance/alpha_rips_persistence_bottleneck_distance.cpp b/example/Bottleneck_distance/alpha_rips_persistence_bottleneck_distance.cpp deleted file mode 100644 index 2db1ef80..00000000 --- a/example/Bottleneck_distance/alpha_rips_persistence_bottleneck_distance.cpp +++ /dev/null @@ -1,190 +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): Vincent Rouvreau - * - * Copyright (C) 2017 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/Alpha_complex.h> -#include <gudhi/Rips_complex.h> -#include <gudhi/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Points_off_io.h> -#include <gudhi/Bottleneck.h> - -#include <CGAL/Epick_d.h> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> -#include <limits> // infinity -#include <utility> // for pair -#include <algorithm> // for transform - - -// 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 Kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >; -using Point_d = Kernel::Point_d; -using Points_off_reader = Gudhi::Points_off_reader<Point_d>; - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , Filtration_value & threshold - , int & dim_max - , int & p - , Filtration_value & min_persistence); - -static inline std::pair<double, double> compute_root_square(std::pair<double, double> input) { - return std::make_pair(std::sqrt(input.first), std::sqrt(input.second)); -} - -int main(int argc, char * argv[]) { - std::string off_file_points; - Filtration_value threshold; - int dim_max; - int p; - Filtration_value min_persistence; - - program_options(argc, argv, off_file_points, threshold, dim_max, p, min_persistence); - - Points_off_reader off_reader(off_file_points); - - // -------------------------------------------- - // Rips persistence - // -------------------------------------------- - Rips_complex rips_complex(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); - - // Construct the Rips complex in a Simplex Tree - Simplex_tree rips_stree; - - rips_complex.create_complex(rips_stree, dim_max); - std::cout << "The Rips complex contains " << rips_stree.num_simplices() << " simplices and has dimension " - << rips_stree.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - rips_stree.initialize_filtration(); - - // Compute the persistence diagram of the complex - Persistent_cohomology rips_pcoh(rips_stree); - // initializes the coefficient field for homology - rips_pcoh.init_coefficients(p); - rips_pcoh.compute_persistent_cohomology(min_persistence); - - // rips_pcoh.output_diagram(); - - // -------------------------------------------- - // Alpha persistence - // -------------------------------------------- - Gudhi::alpha_complex::Alpha_complex<Kernel> alpha_complex(off_reader.get_point_cloud()); - - Simplex_tree alpha_stree; - alpha_complex.create_complex(alpha_stree, threshold * threshold); - std::cout << "The Alpha complex contains " << alpha_stree.num_simplices() << " simplices and has dimension " - << alpha_stree.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - alpha_stree.initialize_filtration(); - - // Compute the persistence diagram of the complex - Persistent_cohomology alpha_pcoh(alpha_stree); - // initializes the coefficient field for homology - alpha_pcoh.init_coefficients(p); - alpha_pcoh.compute_persistent_cohomology(min_persistence * min_persistence); - - // alpha_pcoh.output_diagram(); - - // -------------------------------------------- - // Bottleneck distance between both persistence - // -------------------------------------------- - double max_b_distance {}; - for (int dim = 0; dim < dim_max; dim ++) { - std::vector< std::pair< Filtration_value , Filtration_value > > rips_intervals; - std::vector< std::pair< Filtration_value , Filtration_value > > alpha_intervals; - rips_intervals = rips_pcoh.intervals_in_dimension(dim); - alpha_intervals = alpha_pcoh.intervals_in_dimension(dim); - std::transform(alpha_intervals.begin(), alpha_intervals.end(), alpha_intervals.begin(), compute_root_square); - - double bottleneck_distance = Gudhi::persistence_diagram::bottleneck_distance(rips_intervals, alpha_intervals); - std::cout << "In dimension " << dim << ", bottleneck distance = " << bottleneck_distance << std::endl; - if (bottleneck_distance > max_b_distance) - max_b_distance = bottleneck_distance; - } - std::cout << "================================================================================" << std::endl; - std::cout << "Bottleneck distance is " << max_b_distance << std::endl; - - return 0; -} - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , Filtration_value & threshold - , 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>(&off_file_points), - "Name of an OFF file containing a point set.\n"); - - po::options_description visible("Allowed options", 100); - visible.add_options() - ("help,h", "produce help message") - ("max-edge-length,r", - po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), - "Maximal length 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 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; - exit(-1); - } -} diff --git a/example/Bottleneck_distance/bottleneck_basic_example.cpp b/example/Bottleneck_distance/bottleneck_basic_example.cpp deleted file mode 100644 index 3df7d12d..00000000 --- a/example/Bottleneck_distance/bottleneck_basic_example.cpp +++ /dev/null @@ -1,50 +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. - * - * Authors: Francois Godi, small modifications by Pawel Dlotko - * - * Copyright (C) 2015 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/Bottleneck.h> - -#include <iostream> -#include <vector> -#include <utility> // for pair -#include <limits> // for numeric_limits - -int main() { - std::vector< std::pair<double, double> > v1, v2; - - v1.emplace_back(2.7, 3.7); - v1.emplace_back(9.6, 14.); - v1.emplace_back(34.2, 34.974); - v1.emplace_back(3., std::numeric_limits<double>::infinity()); - - v2.emplace_back(2.8, 4.45); - v2.emplace_back(9.5, 14.1); - v2.emplace_back(3.2, std::numeric_limits<double>::infinity()); - - - double b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2); - - std::cout << "Bottleneck distance = " << b << std::endl; - - b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2, 0.1); - - std::cout << "Approx bottleneck distance = " << b << std::endl; -} diff --git a/example/Cech_complex/CMakeLists.txt b/example/Cech_complex/CMakeLists.txt deleted file mode 100644 index ab391215..00000000 --- a/example/Cech_complex/CMakeLists.txt +++ /dev/null @@ -1,16 +0,0 @@ -cmake_minimum_required(VERSION 2.6) -project(Cech_complex_examples) - -add_executable ( Cech_complex_example_step_by_step cech_complex_step_by_step.cpp ) -target_link_libraries(Cech_complex_example_step_by_step ${Boost_PROGRAM_OPTIONS_LIBRARY}) -if (TBB_FOUND) - target_link_libraries(Cech_complex_example_step_by_step ${TBB_LIBRARIES}) -endif() -add_test(NAME Cech_complex_utility_from_rips_on_tore_3D COMMAND $<TARGET_FILE:Cech_complex_example_step_by_step> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" "-r" "0.25" "-d" "3") - -add_executable ( Cech_complex_example_from_points cech_complex_example_from_points.cpp) -if (TBB_FOUND) - target_link_libraries(Cech_complex_example_from_points ${TBB_LIBRARIES}) -endif() -add_test(NAME Cech_complex_example_from_points COMMAND $<TARGET_FILE:Cech_complex_example_from_points>) diff --git a/example/Cech_complex/cech_complex_example_from_points.cpp b/example/Cech_complex/cech_complex_example_from_points.cpp deleted file mode 100644 index 3cc5a4df..00000000 --- a/example/Cech_complex/cech_complex_example_from_points.cpp +++ /dev/null @@ -1,54 +0,0 @@ -#include <gudhi/Cech_complex.h> -#include <gudhi/Simplex_tree.h> - -#include <iostream> -#include <string> -#include <vector> -#include <array> - -int main() { - // Type definitions - using Point_cloud = std::vector<std::array<double, 2>>; - using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; - using Filtration_value = Simplex_tree::Filtration_value; - using Cech_complex = Gudhi::cech_complex::Cech_complex<Simplex_tree, Point_cloud>; - - Point_cloud points; - points.push_back({1., 0.}); // 0 - points.push_back({0., 1.}); // 1 - points.push_back({2., 1.}); // 2 - points.push_back({3., 2.}); // 3 - points.push_back({0., 3.}); // 4 - points.push_back({3. + std::sqrt(3.), 3.}); // 5 - points.push_back({1., 4.}); // 6 - points.push_back({3., 4.}); // 7 - points.push_back({2., 4. + std::sqrt(3.)}); // 8 - points.push_back({0., 4.}); // 9 - points.push_back({-0.5, 2.}); // 10 - - // ---------------------------------------------------------------------------- - // Init of a Cech complex from points - // ---------------------------------------------------------------------------- - Filtration_value max_radius = 1.; - Cech_complex cech_complex_from_points(points, max_radius); - - Simplex_tree stree; - cech_complex_from_points.create_complex(stree, 2); - // ---------------------------------------------------------------------------- - // Display information about the one skeleton Cech complex - // ---------------------------------------------------------------------------- - std::cout << "Cech complex is of dimension " << stree.dimension() << " - " << stree.num_simplices() << " simplices - " - << stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " - << "[" << stree.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - return 0; -} diff --git a/example/Cech_complex/cech_complex_example_from_points_for_doc.txt b/example/Cech_complex/cech_complex_example_from_points_for_doc.txt deleted file mode 100644 index be0afc76..00000000 --- a/example/Cech_complex/cech_complex_example_from_points_for_doc.txt +++ /dev/null @@ -1,31 +0,0 @@ -Iterator on Cech complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 7 ) -> [0] - ( 8 ) -> [0] - ( 9 ) -> [0] - ( 10 ) -> [0] - ( 9 4 ) -> [0.5] - ( 9 6 ) -> [0.5] - ( 10 1 ) -> [0.559017] - ( 10 4 ) -> [0.559017] - ( 1 0 ) -> [0.707107] - ( 2 0 ) -> [0.707107] - ( 3 2 ) -> [0.707107] - ( 6 4 ) -> [0.707107] - ( 9 6 4 ) -> [0.707107] - ( 2 1 ) -> [1] - ( 2 1 0 ) -> [1] - ( 4 1 ) -> [1] - ( 5 3 ) -> [1] - ( 7 3 ) -> [1] - ( 7 5 ) -> [1] - ( 7 6 ) -> [1] - ( 8 6 ) -> [1] - ( 8 7 ) -> [1] - ( 10 4 1 ) -> [1] diff --git a/example/Cech_complex/cech_complex_step_by_step.cpp b/example/Cech_complex/cech_complex_step_by_step.cpp deleted file mode 100644 index 6fbbde5b..00000000 --- a/example/Cech_complex/cech_complex_step_by_step.cpp +++ /dev/null @@ -1,166 +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): Vincent Rouvreau - * - * 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/>. - */ - -#include <gudhi/graph_simplicial_complex.h> -#include <gudhi/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Points_off_io.h> - -#include <gudhi/Miniball.hpp> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> -#include <limits> // infinity -#include <utility> // for pair -#include <map> - -// ---------------------------------------------------------------------------- -// rips_persistence_step_by_step is an example of each step that is required to -// build a Rips over a Simplex_tree. Please refer to rips_persistence to see -// how to do the same thing with the Rips_complex wrapper for less detailed -// steps. -// ---------------------------------------------------------------------------- - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<>; -using Simplex_handle = Simplex_tree::Simplex_handle; -using Filtration_value = Simplex_tree::Filtration_value; -using Point = std::vector<double>; -using Points_off_reader = Gudhi::Points_off_reader<Point>; -using Proximity_graph = Gudhi::Proximity_graph<Simplex_tree>; - -class Cech_blocker { - private: - using Point_cloud = std::vector<Point>; - using Point_iterator = Point_cloud::const_iterator; - using Coordinate_iterator = Point::const_iterator; - using Min_sphere = Gudhi::Miniball::Miniball<Gudhi::Miniball::CoordAccessor<Point_iterator, Coordinate_iterator>>; - - public: - bool operator()(Simplex_handle sh) { - std::vector<Point> points; - for (auto vertex : simplex_tree_.simplex_vertex_range(sh)) { - points.push_back(point_cloud_[vertex]); -#ifdef DEBUG_TRACES - std::cout << "#(" << vertex << ")#"; -#endif // DEBUG_TRACES - } - Filtration_value radius = Gudhi::Minimal_enclosing_ball_radius()(points); -#ifdef DEBUG_TRACES - std::cout << "radius = " << radius << " - " << (radius > max_radius_) << std::endl; -#endif // DEBUG_TRACES - simplex_tree_.assign_filtration(sh, radius); - return (radius > max_radius_); - } - Cech_blocker(Simplex_tree& simplex_tree, Filtration_value max_radius, const std::vector<Point>& point_cloud) - : simplex_tree_(simplex_tree), max_radius_(max_radius), point_cloud_(point_cloud) { - dimension_ = point_cloud_[0].size(); - } - - private: - Simplex_tree simplex_tree_; - Filtration_value max_radius_; - std::vector<Point> point_cloud_; - int dimension_; -}; - -void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& max_radius, int& dim_max); - -int main(int argc, char* argv[]) { - std::string off_file_points; - Filtration_value max_radius; - int dim_max; - - program_options(argc, argv, off_file_points, max_radius, dim_max); - - // Extract the points from the file filepoints - Points_off_reader off_reader(off_file_points); - - // Compute the proximity graph of the points - Proximity_graph prox_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(), max_radius, - Gudhi::Minimal_enclosing_ball_radius()); - - // Construct the Rips complex in a Simplex Tree - Simplex_tree st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion_with_blockers(dim_max, Cech_blocker(st, max_radius, off_reader.get_point_cloud())); - - std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << st.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - -#if DEBUG_TRACES - std::cout << "********************************************************************\n"; - std::cout << "* The complex contains " << st.num_simplices() << " simplices - dimension=" << st.dimension() << "\n"; - std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; - for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " - << "[" << st.filtration(f_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(f_simplex)) { - std::cout << static_cast<int>(vertex) << " "; - } - std::cout << std::endl; - } -#endif // DEBUG_TRACES - - return 0; -} - -void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& max_radius, int& dim_max) { - namespace po = boost::program_options; - po::options_description hidden("Hidden options"); - hidden.add_options()("input-file", po::value<std::string>(&off_file_points), - "Name of an OFF file containing a point set.\n"); - - po::options_description visible("Allowed options", 100); - visible.add_options()("help,h", "produce help message")( - "max-radius,r", - po::value<Filtration_value>(&max_radius)->default_value(std::numeric_limits<Filtration_value>::infinity()), - "Maximal length 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."); - - 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 << "Construct a Cech complex defined on a set of input points.\n \n"; - - std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; - std::cout << visible << std::endl; - exit(-1); - } -} diff --git a/example/Contraction/CMakeLists.txt b/example/Contraction/CMakeLists.txt deleted file mode 100644 index 582b7ab8..00000000 --- a/example/Contraction/CMakeLists.txt +++ /dev/null @@ -1,17 +0,0 @@ -project(Contraction_examples) - -add_executable(RipsContraction Rips_contraction.cpp) - -add_executable(GarlandHeckbert Garland_heckbert.cpp) -target_link_libraries(GarlandHeckbert ${Boost_TIMER_LIBRARY}) - -add_test(NAME Contraction_example_tore3D_0.2 COMMAND $<TARGET_FILE:RipsContraction> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "0.2") -# TODO(DS) : These tests are too long under Windows -#add_test(NAME Contraction_example_sphere_0.2 COMMAND $<TARGET_FILE:RipsContraction> -# "${CMAKE_SOURCE_DIR}/data/points/sphere3D_2646.off" "0.2") -#add_test(NAME Contraction_example_SO3_0.3 COMMAND $<TARGET_FILE:RipsContraction> -# "${CMAKE_SOURCE_DIR}/data/points/SO3_10000.off" "0.3") - -install(TARGETS RipsContraction DESTINATION bin) -install(TARGETS GarlandHeckbert DESTINATION bin) diff --git a/example/Contraction/Garland_heckbert.cpp b/example/Contraction/Garland_heckbert.cpp deleted file mode 100644 index 08dd932e..00000000 --- a/example/Contraction/Garland_heckbert.cpp +++ /dev/null @@ -1,192 +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): David Salinas - * - * Copyright (C) 2014 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 GARLAND_HECKBERT_H_ -#define GARLAND_HECKBERT_H_ - -#include <gudhi/Point.h> -#include <gudhi/Edge_contraction.h> -#include <gudhi/Skeleton_blocker.h> -#include <gudhi/Off_reader.h> - -#include <iostream> - -#include "Garland_heckbert/Error_quadric.h" - -struct Geometry_trait { - typedef Point_d Point; -}; - -/** - * The vertex stored in the complex contains a quadric. - */ -struct Garland_heckbert_traits - : public Gudhi::skeleton_blocker::Skeleton_blocker_simple_geometric_traits<Geometry_trait> { - public: - struct Garland_heckbert_vertex : public Simple_geometric_vertex { - Error_quadric<Geometry_trait::Point> quadric; - }; - typedef Garland_heckbert_vertex Graph_vertex; -}; - -using Complex = Gudhi::skeleton_blocker::Skeleton_blocker_geometric_complex< Garland_heckbert_traits >; -using EdgeProfile = Gudhi::contraction::Edge_profile<Complex>; -using Complex_contractor = Gudhi::contraction::Skeleton_blocker_contractor<Complex>; - -/** - * How the new vertex is placed after an edge collapse : here it is placed at - * the point minimizing the cost of the quadric. - */ -class GH_placement : public Gudhi::contraction::Placement_policy<EdgeProfile> { - Complex& complex_; - - public: - typedef Gudhi::contraction::Placement_policy<EdgeProfile>::Placement_type Placement_type; - - GH_placement(Complex& complex) : complex_(complex) { (void)complex_; } - - Placement_type operator()(const EdgeProfile& profile) const override { - auto sum_quad(profile.v0().quadric); - sum_quad += profile.v1().quadric; - - boost::optional<Point> min_quadric_pt(sum_quad.min_cost()); - if (min_quadric_pt) - return Placement_type(*min_quadric_pt); - else - return profile.p0(); - } -}; - -/** - * How much cost an edge collapse : here the costs is given by a quadric - * which expresses a squared distances with triangles planes. - */ -class GH_cost : public Gudhi::contraction::Cost_policy<EdgeProfile> { - Complex& complex_; - - public: - typedef Gudhi::contraction::Cost_policy<EdgeProfile>::Cost_type Cost_type; - - GH_cost(Complex& complex) : complex_(complex) { (void)complex_; } - - Cost_type operator()(EdgeProfile const& profile, boost::optional<Point> const& new_point) const override { - Cost_type res; - if (new_point) { - auto sum_quad(profile.v0().quadric); - sum_quad += profile.v1().quadric; - res = sum_quad.cost(*new_point); - } - return res; - } -}; - -/** - * Visitor that is called at several moment. - * Here we initializes the quadrics of every vertex at the on_started call back - * and we update them when contracting an edge (the quadric become the sum of both quadrics). - */ -class GH_visitor : public Gudhi::contraction::Contraction_visitor<EdgeProfile> { - Complex& complex_; - - public: - GH_visitor(Complex& complex) : complex_(complex) { (void)complex_; } - - // Compute quadrics for every vertex v - // The quadric of v consists in the sum of quadric - // of every triangles passing through v weighted by its area - - void on_started(Complex & complex) override { - for (auto v : complex.vertex_range()) { - auto & quadric_v(complex[v].quadric); - for (auto t : complex.triangle_range(v)) { - auto t_it = t.begin(); - const auto& p0(complex.point(*t_it++)); - const auto& p1(complex.point(*t_it++)); - const auto& p2(complex.point(*t_it++)); - quadric_v += Error_quadric<Point>(p0, p1, p2); - } - } - } - - /** - * @brief Called when an edge is about to be contracted and replaced by a vertex whose position is *placement. - */ - void on_contracting(EdgeProfile const &profile, boost::optional< Point > placement) - override { - profile.v0().quadric += profile.v1().quadric; - } -}; - -int main(int argc, char *argv[]) { - if (argc != 4) { - std::cerr << "Usage " << argv[0] << - " input.off output.off N to load the file input.off, contract N edges and save the result to output.off.\n"; - return EXIT_FAILURE; - } - - Complex complex; - typedef Complex::Vertex_handle Vertex_handle; - - // load the points - Gudhi::skeleton_blocker::Skeleton_blocker_off_reader<Complex> off_reader(argv[1], complex); - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file:" << argv[1] << std::endl; - return EXIT_FAILURE; - } - - if (!complex.empty() && !(complex.point(Vertex_handle(0)).dimension() == 3)) { - std::cerr << "Only points of dimension 3 are supported." << std::endl; - return EXIT_FAILURE; - } - - std::cout << "Load complex with " << complex.num_vertices() << " vertices" << std::endl; - - int num_contractions = atoi(argv[3]); - - // constructs the contractor object with Garland Heckbert policies. - Complex_contractor contractor(complex, - new GH_cost(complex), - new GH_placement(complex), - Gudhi::contraction::make_link_valid_contraction<EdgeProfile>(), - new GH_visitor(complex)); - - std::cout << "Contract " << num_contractions << " edges" << std::endl; - contractor.contract_edges(num_contractions); - - std::cout << "Final complex has " << - complex.num_vertices() << " vertices, " << - complex.num_edges() << " edges and " << - complex.num_triangles() << " triangles." << std::endl; - - // write simplified complex - Gudhi::skeleton_blocker::Skeleton_blocker_off_writer<Complex> off_writer(argv[2], complex); - - return EXIT_SUCCESS; -} - -#endif // GARLAND_HECKBERT_H_ - - - - diff --git a/example/Contraction/Garland_heckbert/Error_quadric.h b/example/Contraction/Garland_heckbert/Error_quadric.h deleted file mode 100644 index 8bd9b545..00000000 --- a/example/Contraction/Garland_heckbert/Error_quadric.h +++ /dev/null @@ -1,182 +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): David Salinas - * - * Copyright (C) 2014 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 GARLAND_HECKBERT_ERROR_QUADRIC_H_ -#define GARLAND_HECKBERT_ERROR_QUADRIC_H_ - -#include <boost/optional/optional.hpp> - -#include <vector> -#include <utility> - -template <typename Point> class Error_quadric { - private: - double coeff[10]; - - public: - Error_quadric() { - clear(); - } - - /** - * Quadric corresponding to the L2 distance to the plane. - * - * According to the notation of Garland Heckbert, they - * denote a quadric symetric matrix as : - * Q = [ q11 q12 q13 q14] - * [ q12 q22 q23 q24] - * [ q13 q23 q33 q34] - * [ q14 q24 q34 q44] - * - * which is represented by a vector with 10 elts that - * are denoted ci for clarity with : - * Q = [ c0 c1 c2 c3 ] - * [ c1 c4 c5 c6 ] - * [ c2 c5 c7 c8 ] - * [ c3 c6 c8 c9 ] - * - * The constructor return the quadrics that represents - * the squared distance to the plane defined by triangle p0,p1,p2 - * times the area of triangle p0,p1,p2. - */ - Error_quadric(const Point & p0, const Point & p1, const Point & p2) { - Point normal(unit_normal(p0, p1, p2)); - double a = normal[0]; - double b = normal[1]; - double c = normal[2]; - double d = -a * p0[0] - b * p0[1] - c * p0[2]; - coeff[0] = a*a; - coeff[1] = a*b; - coeff[2] = a*c; - coeff[3] = a*d; - coeff[4] = b*b; - coeff[5] = b*c; - coeff[6] = b*d; - coeff[7] = c*c; - coeff[8] = c*d; - coeff[9] = d*d; - - double area_p0p1p2 = std::sqrt(squared_area(p0, p1, p2)); - for (auto& x : coeff) - x *= area_p0p1p2; - } - - inline double squared_area(const Point& p0, const Point& p1, const Point& p2) { - // if (x1,x2,x3) = p1-p0 and (y1,y2,y3) = p2-p0 - // then the squared area is = (u^2+v^2+w^2)/4 - // with: u = x2 * y3 - x3 * y2; - // v = x3 * y1 - x1 * y3; - // w = x1 * y2 - x2 * y1; - Point p0p1(p1 - p0); - Point p0p2(p2 - p0); - double A = p0p1[1] * p0p2[2] - p0p1[2] * p0p2[1]; - double B = p0p1[2] * p0p2[0] - p0p1[0] * p0p2[2]; - double C = p0p1[0] * p0p2[1] - p0p1[1] * p0p2[0]; - return 1. / 4. * (A * A + B * B + C * C); - } - - void clear() { - for (auto& x : coeff) - x = 0; - } - - Error_quadric& operator+=(const Error_quadric& other) { - if (this != &other) { - for (int i = 0; i < 10; ++i) - coeff[i] += other.coeff[i]; - } - return *this; - } - - /** - * @return The quadric quost defined by the scalar product v^T Q v where Q is the quadratic form of Garland/Heckbert - */ - inline double cost(const Point& point) const { - double cost = - coeff[0] * point.x() * point.x() + coeff[4] * point.y() * point.y() + coeff[7] * point.z() * point.z() - + 2 * (coeff[1] * point.x() * point.y() + coeff[5] * point.y() * point.z() + coeff[2] * point.z() * point.x()) - + 2 * (coeff[3] * point.x() + coeff[6] * point.y() + coeff[8] * point.z()) - + coeff[9]; - if (cost < 0) { - return 0; - } else { - return cost; - } - } - - inline double grad_determinant() const { - return - coeff[0] * coeff[4] * coeff[7] - - coeff[0] * coeff[5] * coeff[5] - - coeff[1] * coeff[1] * coeff[7] - + 2 * coeff[1] * coeff[5] * coeff[2] - - coeff[4] * coeff[2] * coeff[2]; - } - - /** - * Return the point such that it minimizes the gradient of the quadric. - * Det must be passed with the determinant value of the gradient (should be non zero). - */ - inline Point solve_linear_gradient(double det) const { - return Point({ - (-coeff[1] * coeff[5] * coeff[8] + coeff[1] * coeff[7] * coeff[6] + coeff[2] * coeff[8] * coeff[4] - - coeff[2] * coeff[5] * coeff[6] - coeff[3] * coeff[4] * coeff[7] + coeff[3] * coeff[5] * coeff[5]) - / det, - (coeff[0] * coeff[5] * coeff[8] - coeff[0] * coeff[7] * coeff[6] - coeff[5] * coeff[2] * coeff[3] - - coeff[1] * coeff[2] * coeff[8] + coeff[6] * coeff[2] * coeff[2] + coeff[1] * coeff[3] * coeff[7]) - / det, - (-coeff[8] * coeff[0] * coeff[4] + coeff[8] * coeff[1] * coeff[1] + coeff[2] * coeff[3] * coeff[4] + - coeff[5] * coeff[0] * coeff[6] - coeff[5] * coeff[1] * coeff[3] - coeff[1] * coeff[2] * coeff[6]) - / det - }); - } - - /** - * returns the point that minimizes the quadric. - * It inverses the quadric if its determinant is higher that a given threshold . - * If the determinant is lower than this value the returned value is uninitialized. - */ - boost::optional<Point> min_cost(double scale = 1) const { - // const double min_determinant = 1e-4 * scale*scale; - const double min_determinant = 1e-5; - boost::optional<Point> pt_res; - double det = grad_determinant(); - if (std::abs(det) > min_determinant) - pt_res = solve_linear_gradient(det); - return pt_res; - } - - friend std::ostream& operator<<(std::ostream& stream, const Error_quadric& quadric) { - stream << "\n[ " << quadric.coeff[0] << "," << quadric.coeff[1] << "," << quadric.coeff[2] << "," << - quadric.coeff[3] << ";\n"; - stream << " " << quadric.coeff[1] << "," << quadric.coeff[4] << "," << quadric.coeff[5] << "," << - quadric.coeff[6] << ";\n"; - stream << " " << quadric.coeff[2] << "," << quadric.coeff[5] << "," << quadric.coeff[7] << "," << - quadric.coeff[8] << ";\n"; - stream << " " << quadric.coeff[3] << "," << quadric.coeff[6] << "," << quadric.coeff[8] << "," << - quadric.coeff[9] << "]"; - return stream; - } -}; - -#endif // GARLAND_HECKBERT_ERROR_QUADRIC_H_ diff --git a/example/Contraction/Rips_contraction.cpp b/example/Contraction/Rips_contraction.cpp deleted file mode 100644 index 7f9b150a..00000000 --- a/example/Contraction/Rips_contraction.cpp +++ /dev/null @@ -1,98 +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): David Salinas - * - * Copyright (C) 2014 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/Edge_contraction.h> -#include <gudhi/Skeleton_blocker.h> -#include <gudhi/Off_reader.h> -#include <gudhi/Point.h> -#include <gudhi/Clock.h> - -#include <iostream> - -struct Geometry_trait { - typedef Point_d Point; -}; - -using Complex_geometric_traits = Gudhi::skeleton_blocker::Skeleton_blocker_simple_geometric_traits<Geometry_trait>; -using Complex = Gudhi::skeleton_blocker::Skeleton_blocker_geometric_complex< Complex_geometric_traits >; -using Profile = Gudhi::contraction::Edge_profile<Complex>; -using Complex_contractor = Gudhi::contraction::Skeleton_blocker_contractor<Complex>; - - -template<typename ComplexType> -void build_rips(ComplexType& complex, double offset) { - if (offset <= 0) return; - auto vertices = complex.vertex_range(); - for (auto p = vertices.begin(); p != vertices.end(); ++p) - for (auto q = p; ++q != vertices.end(); /**/) { - if (squared_dist(complex.point(*p), complex.point(*q)) < 4 * offset * offset) - complex.add_edge_without_blockers(*p, *q); - } -} - -int main(int argc, char *argv[]) { - if (argc != 3) { - std::cerr << "Usage " << argv[0] << " ../../../data/meshes/SO3_10000.off 0.3 to load the file " << - "../../data/SO3_10000.off and contract the Rips complex built with paremeter 0.3.\n"; - return -1; - } - - Complex complex; - - // load only the points - Gudhi::skeleton_blocker::Skeleton_blocker_off_reader<Complex> off_reader(argv[1], complex, true); - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file:" << argv[1] << std::endl; - return EXIT_FAILURE; - } - - std::cout << "Build the Rips complex with " << complex.num_vertices() << " vertices" << std::endl; - - build_rips(complex, atof(argv[2])); - - Gudhi::Clock contraction_chrono("Time to simplify and enumerate simplices"); - - std::cout << "Initial complex has " << - complex.num_vertices() << " vertices and " << - complex.num_edges() << " edges" << std::endl; - - Complex_contractor contractor(complex, - new Gudhi::contraction::Edge_length_cost<Profile>, - Gudhi::contraction::make_first_vertex_placement<Profile>(), - Gudhi::contraction::make_link_valid_contraction<Profile>(), - Gudhi::contraction::make_remove_popable_blockers_visitor<Profile>()); - contractor.contract_edges(); - - std::cout << "Counting final number of simplices \n"; - unsigned num_simplices = std::distance(complex.complex_simplex_range().begin(), complex.complex_simplex_range().end()); - - std::cout << "Final complex has " << - complex.num_vertices() << " vertices, " << - complex.num_edges() << " edges, " << - complex.num_blockers() << " blockers and " << - num_simplices << " simplices" << std::endl; - - std::cout << contraction_chrono; - - return EXIT_SUCCESS; -} - - diff --git a/example/Nerve_GIC/CMakeLists.txt b/example/Nerve_GIC/CMakeLists.txt deleted file mode 100644 index fdecf86e..00000000 --- a/example/Nerve_GIC/CMakeLists.txt +++ /dev/null @@ -1,28 +0,0 @@ -project(Nerve_GIC_examples) - -if (NOT CGAL_VERSION VERSION_LESS 4.8.1) - - add_executable ( CoordGIC CoordGIC.cpp ) - add_executable ( FuncGIC FuncGIC.cpp ) - - if (TBB_FOUND) - target_link_libraries(CoordGIC ${TBB_LIBRARIES}) - target_link_libraries(FuncGIC ${TBB_LIBRARIES}) - endif() - - # Copy files for not to pollute sources when testing - file(COPY "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - file(COPY "${CMAKE_SOURCE_DIR}/data/points/COIL_database/lucky_cat.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - file(COPY "${CMAKE_SOURCE_DIR}/data/points/COIL_database/lucky_cat_PCA1" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - - add_test(NAME Nerve_GIC_example_CoordGIC COMMAND $<TARGET_FILE:CoordGIC> - "${CMAKE_CURRENT_BINARY_DIR}/tore3D_1307.off" "0") - - add_test(NAME Nerve_GIC_example_FuncGIC COMMAND $<TARGET_FILE:FuncGIC> - "${CMAKE_CURRENT_BINARY_DIR}/lucky_cat.off" - "${CMAKE_CURRENT_BINARY_DIR}/lucky_cat_PCA1") - - install(TARGETS CoordGIC DESTINATION bin) - install(TARGETS FuncGIC DESTINATION bin) - -endif (NOT CGAL_VERSION VERSION_LESS 4.8.1) diff --git a/example/Nerve_GIC/CoordGIC.cpp b/example/Nerve_GIC/CoordGIC.cpp deleted file mode 100644 index 9889b198..00000000 --- a/example/Nerve_GIC/CoordGIC.cpp +++ /dev/null @@ -1,96 +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 Carrière - * - * Copyright (C) 2017 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/GIC.h> - -#include <string> -#include <vector> - -void usage(int nbArgs, char *const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " filename.off coordinate [-v] \n"; - std::cerr << " i.e.: " << progName << " ../../data/points/human.off 2 -v \n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 3) && (argc != 4)) usage(argc, argv[0]); - - using Point = std::vector<float>; - - std::string off_file_name(argv[1]); - int coord = atoi(argv[2]); - bool verb = 0; - if (argc == 4) verb = 1; - - // ----------------------------------------- - // Init of a functional GIC from an OFF file - // ----------------------------------------- - - Gudhi::cover_complex::Cover_complex<Point> GIC; - GIC.set_verbose(verb); - - bool check = GIC.read_point_cloud(off_file_name); - - if (!check) { - std::cout << "Incorrect OFF file." << std::endl; - } else { - GIC.set_type("GIC"); - - GIC.set_color_from_coordinate(coord); - GIC.set_function_from_coordinate(coord); - - GIC.set_graph_from_automatic_rips(Gudhi::Euclidean_distance()); - GIC.set_automatic_resolution(); - GIC.set_gain(); - GIC.set_cover_from_function(); - - GIC.find_simplices(); - - GIC.compute_distribution(10); - GIC.compute_p_value(); - - GIC.plot_DOT(); - - Gudhi::Simplex_tree<> stree; - GIC.create_complex(stree); - - // -------------------------------------------- - // Display information about the functional GIC - // -------------------------------------------- - - if (verb) { - std::cout << "Coordinate GIC is of dimension " << stree.dimension() << " - " << stree.num_simplices() - << " simplices - " << stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on coordinate GIC simplices" << std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - } - } - - return 0; -} diff --git a/example/Nerve_GIC/FuncGIC.cpp b/example/Nerve_GIC/FuncGIC.cpp deleted file mode 100644 index 1f5de999..00000000 --- a/example/Nerve_GIC/FuncGIC.cpp +++ /dev/null @@ -1,94 +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 Carrière - * - * Copyright (C) 2017 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/GIC.h> - -#include <string> -#include <vector> - -void usage(int nbArgs, char *const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " filename.off function [-v] \n"; - std::cerr << " i.e.: " << progName << " ../../data/points/COIL_database/lucky_cat.off " - "../../data/points/COIL_database/lucky_cat_PCA1 -v \n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 3) && (argc != 4)) usage(argc, argv[0]); - - using Point = std::vector<float>; - - std::string off_file_name(argv[1]); - std::string func_file_name = argv[2]; - bool verb = 0; - if (argc == 4) verb = 1; - - // ----------------------------------------- - // Init of a functional GIC from an OFF file - // ----------------------------------------- - - Gudhi::cover_complex::Cover_complex<Point> GIC; - GIC.set_verbose(verb); - - bool check = GIC.read_point_cloud(off_file_name); - - if (!check) { - std::cout << "Incorrect OFF file." << std::endl; - } else { - GIC.set_type("GIC"); - - GIC.set_color_from_file(func_file_name); - GIC.set_function_from_file(func_file_name); - - GIC.set_graph_from_automatic_rips(Gudhi::Euclidean_distance()); - GIC.set_automatic_resolution(); - GIC.set_gain(); - GIC.set_cover_from_function(); - - GIC.find_simplices(); - - GIC.plot_DOT(); - - Gudhi::Simplex_tree<> stree; - GIC.create_complex(stree); - - // -------------------------------------------- - // Display information about the functional GIC - // -------------------------------------------- - - if (verb) { - std::cout << "Functional GIC is of dimension " << stree.dimension() << " - " << stree.num_simplices() - << " simplices - " << stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on functional GIC simplices" << std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - } - } - - return 0; -} diff --git a/example/Persistence_representations/CMakeLists.txt b/example/Persistence_representations/CMakeLists.txt deleted file mode 100644 index 33558df3..00000000 --- a/example/Persistence_representations/CMakeLists.txt +++ /dev/null @@ -1,28 +0,0 @@ -project(Persistence_representations_example) - -add_executable ( Persistence_representations_example_landscape_on_grid persistence_landscape_on_grid.cpp ) -add_test(NAME Persistence_representations_example_landscape_on_grid - COMMAND $<TARGET_FILE:Persistence_representations_example_landscape_on_grid>) -install(TARGETS Persistence_representations_example_landscape_on_grid DESTINATION bin) - -add_executable ( Persistence_representations_example_landscape persistence_landscape.cpp ) -add_test(NAME Persistence_representations_example_landscape - COMMAND $<TARGET_FILE:Persistence_representations_example_landscape>) -install(TARGETS Persistence_representations_example_landscape DESTINATION bin) - -add_executable ( Persistence_representations_example_intervals persistence_intervals.cpp ) -add_test(NAME Persistence_representations_example_intervals - COMMAND $<TARGET_FILE:Persistence_representations_example_intervals> - "${CMAKE_SOURCE_DIR}/data/persistence_diagram/first.pers") -install(TARGETS Persistence_representations_example_intervals DESTINATION bin) - -add_executable ( Persistence_representations_example_vectors persistence_vectors.cpp ) -add_test(NAME Persistence_representations_example_vectors - COMMAND $<TARGET_FILE:Persistence_representations_example_vectors>) -install(TARGETS Persistence_representations_example_vectors DESTINATION bin) - -add_executable ( Persistence_representations_example_heat_maps persistence_heat_maps.cpp ) -add_test(NAME Persistence_representations_example_heat_maps - COMMAND $<TARGET_FILE:Persistence_representations_example_heat_maps>) -install(TARGETS Persistence_representations_example_heat_maps DESTINATION bin) - diff --git a/example/Persistence_representations/persistence_heat_maps.cpp b/example/Persistence_representations/persistence_heat_maps.cpp deleted file mode 100644 index 323b57e9..00000000 --- a/example/Persistence_representations/persistence_heat_maps.cpp +++ /dev/null @@ -1,80 +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 - * - * 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/Persistence_heat_maps.h> - -#include <iostream> -#include <vector> -#include <utility> - -using constant_scaling_function = Gudhi::Persistence_representations::constant_scaling_function; -using Persistence_heat_maps = Gudhi::Persistence_representations::Persistence_heat_maps<constant_scaling_function>; - -int main(int argc, char** argv) { - // create two simple vectors with birth--death pairs: - - std::vector<std::pair<double, double> > persistence1; - std::vector<std::pair<double, double> > persistence2; - - persistence1.push_back(std::make_pair(1, 2)); - persistence1.push_back(std::make_pair(6, 8)); - persistence1.push_back(std::make_pair(0, 4)); - persistence1.push_back(std::make_pair(3, 8)); - - persistence2.push_back(std::make_pair(2, 9)); - persistence2.push_back(std::make_pair(1, 6)); - persistence2.push_back(std::make_pair(3, 5)); - persistence2.push_back(std::make_pair(6, 10)); - - // over here we define a function we sill put on a top on every birth--death pair in the persistence interval. It can - // be anything. Over here we will use standard Gaussian - std::vector<std::vector<double> > filter = Gudhi::Persistence_representations::create_Gaussian_filter(5, 1); - - // creating two heat maps. - Persistence_heat_maps hm1(persistence1, filter, false, 20, 0, 11); - Persistence_heat_maps hm2(persistence2, filter, false, 20, 0, 11); - - std::vector<Persistence_heat_maps*> vector_of_maps; - vector_of_maps.push_back(&hm1); - vector_of_maps.push_back(&hm2); - - // compute median/mean of a vector of heat maps: - Persistence_heat_maps mean; - mean.compute_mean(vector_of_maps); - Persistence_heat_maps median; - median.compute_median(vector_of_maps); - - // to compute L^1 distance between hm1 and hm2: - std::cout << "The L^1 distance is : " << hm1.distance(hm2, 1) << std::endl; - - // to average of hm1 and hm2: - std::vector<Persistence_heat_maps*> to_average; - to_average.push_back(&hm1); - to_average.push_back(&hm2); - Persistence_heat_maps av; - av.compute_average(to_average); - - // to compute scalar product of hm1 and hm2: - std::cout << "Scalar product is : " << hm1.compute_scalar_product(hm2) << std::endl; - - return 0; -} diff --git a/example/Persistence_representations/persistence_intervals.cpp b/example/Persistence_representations/persistence_intervals.cpp deleted file mode 100644 index b5dcf25c..00000000 --- a/example/Persistence_representations/persistence_intervals.cpp +++ /dev/null @@ -1,89 +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 - * - * 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/Persistence_intervals.h> - -#include <iostream> -#include <utility> -#include <vector> - -using Persistence_intervals = Gudhi::Persistence_representations::Persistence_intervals; - -int main(int argc, char** argv) { - if (argc != 2) { - std::cout << "To run this program, please provide the name of a file with persistence diagram \n"; - return 1; - } - - Persistence_intervals p(argv[1]); - std::pair<double, double> min_max_ = p.get_x_range(); - std::cout << "Birth-death range : " << min_max_.first << " " << min_max_.second << std::endl; - - std::vector<double> dominant_ten_intervals_length = p.length_of_dominant_intervals(10); - std::cout << "Length of ten dominant intervals : " << std::endl; - for (size_t i = 0; i != dominant_ten_intervals_length.size(); ++i) { - std::cout << dominant_ten_intervals_length[i] << std::endl; - } - - std::vector<std::pair<double, double> > ten_dominant_intervals = p.dominant_intervals(10); - std::cout << "Here are the dominant intervals : " << std::endl; - for (size_t i = 0; i != ten_dominant_intervals.size(); ++i) { - std::cout << "( " << ten_dominant_intervals[i].first << "," << ten_dominant_intervals[i].second << std::endl; - } - - std::vector<size_t> histogram = p.histogram_of_lengths(10); - std::cout << "Here is the histogram of barcode's length : " << std::endl; - for (size_t i = 0; i != histogram.size(); ++i) { - std::cout << histogram[i] << " "; - } - std::cout << std::endl; - - std::vector<size_t> cumulative_histogram = p.cumulative_histogram_of_lengths(10); - std::cout << "Cumulative histogram : " << std::endl; - for (size_t i = 0; i != cumulative_histogram.size(); ++i) { - std::cout << cumulative_histogram[i] << " "; - } - std::cout << std::endl; - - std::vector<double> char_funct_diag = p.characteristic_function_of_diagram(min_max_.first, min_max_.second); - std::cout << "Characteristic function of diagram : " << std::endl; - for (size_t i = 0; i != char_funct_diag.size(); ++i) { - std::cout << char_funct_diag[i] << " "; - } - std::cout << std::endl; - - std::vector<double> cumul_char_funct_diag = - p.cumulative_characteristic_function_of_diagram(min_max_.first, min_max_.second); - std::cout << "Cumulative characteristic function of diagram : " << std::endl; - for (size_t i = 0; i != cumul_char_funct_diag.size(); ++i) { - std::cout << cumul_char_funct_diag[i] << " "; - } - std::cout << std::endl; - - std::cout << "Persistence Betti numbers \n"; - std::vector<std::pair<double, size_t> > pbns = p.compute_persistent_betti_numbers(); - for (size_t i = 0; i != pbns.size(); ++i) { - std::cout << pbns[i].first << " " << pbns[i].second << std::endl; - } - - return 0; -} diff --git a/example/Persistence_representations/persistence_landscape.cpp b/example/Persistence_representations/persistence_landscape.cpp deleted file mode 100644 index 27542cf7..00000000 --- a/example/Persistence_representations/persistence_landscape.cpp +++ /dev/null @@ -1,86 +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 - * - * 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/Persistence_landscape.h> - -#include <iostream> -#include <vector> -#include <utility> - -using Persistence_landscape = Gudhi::Persistence_representations::Persistence_landscape; - -int main(int argc, char** argv) { - // create two simple vectors with birth--death pairs: - - std::vector<std::pair<double, double> > persistence1; - std::vector<std::pair<double, double> > persistence2; - - persistence1.push_back(std::make_pair(1, 2)); - persistence1.push_back(std::make_pair(6, 8)); - persistence1.push_back(std::make_pair(0, 4)); - persistence1.push_back(std::make_pair(3, 8)); - - persistence2.push_back(std::make_pair(2, 9)); - persistence2.push_back(std::make_pair(1, 6)); - persistence2.push_back(std::make_pair(3, 5)); - persistence2.push_back(std::make_pair(6, 10)); - - // create two persistence landscapes based on persistence1 and persistence2: - Persistence_landscape l1(persistence1); - Persistence_landscape l2(persistence2); - - // This is how to compute integral of landscapes: - std::cout << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl; - std::cout << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl; - - // And here how to write landscapes to stream: - std::cout << "l1 : " << l1 << std::endl; - std::cout << "l2 : " << l2 << std::endl; - - // Arithmetic operations on landscapes: - Persistence_landscape sum = l1 + l2; - std::cout << "sum : " << sum << std::endl; - - // here are the maxima of the functions: - std::cout << "Maximum of l1 : " << l1.compute_maximum() << std::endl; - std::cout << "Maximum of l2 : " << l2.compute_maximum() << std::endl; - - // here are the norms of landscapes: - std::cout << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl; - std::cout << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl; - - // here is the average of landscapes: - Persistence_landscape average; - average.compute_average({&l1, &l2}); - std::cout << "average : " << average << std::endl; - - // here is the distance of landscapes: - std::cout << "Distance : " << l1.distance(l2) << std::endl; - - // here is the scalar product of landscapes: - std::cout << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl; - - // here is how to create a file which is suitable for visualization via gnuplot: - average.plot("average_landscape"); - - return 0; -} diff --git a/example/Persistence_representations/persistence_landscape_on_grid.cpp b/example/Persistence_representations/persistence_landscape_on_grid.cpp deleted file mode 100644 index 0f471a67..00000000 --- a/example/Persistence_representations/persistence_landscape_on_grid.cpp +++ /dev/null @@ -1,82 +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 - * - * 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/Persistence_landscape_on_grid.h> - -#include <iostream> -#include <utility> -#include <vector> - -using Persistence_landscape_on_grid = Gudhi::Persistence_representations::Persistence_landscape_on_grid; - -int main(int argc, char** argv) { - // create two simple vectors with birth--death pairs: - - std::vector<std::pair<double, double> > persistence1; - std::vector<std::pair<double, double> > persistence2; - - persistence1.push_back(std::make_pair(1, 2)); - persistence1.push_back(std::make_pair(6, 8)); - persistence1.push_back(std::make_pair(0, 4)); - persistence1.push_back(std::make_pair(3, 8)); - - persistence2.push_back(std::make_pair(2, 9)); - persistence2.push_back(std::make_pair(1, 6)); - persistence2.push_back(std::make_pair(3, 5)); - persistence2.push_back(std::make_pair(6, 10)); - - // create two persistence landscapes based on persistence1 and persistence2: - Persistence_landscape_on_grid l1(persistence1, 0, 11, 20); - Persistence_landscape_on_grid l2(persistence2, 0, 11, 20); - - // This is how to compute integral of landscapes: - std::cout << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl; - std::cout << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl; - - // And here how to write landscapes to stream: - std::cout << "l1 : " << l1 << std::endl; - std::cout << "l2 : " << l2 << std::endl; - - // here are the maxima of the functions: - std::cout << "Maximum of l1 : " << l1.compute_maximum() << std::endl; - std::cout << "Maximum of l2 : " << l2.compute_maximum() << std::endl; - - // here are the norms of landscapes: - std::cout << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl; - std::cout << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl; - - // here is the average of landscapes: - Persistence_landscape_on_grid average; - average.compute_average({&l1, &l2}); - std::cout << "average : " << average << std::endl; - - // here is the distance of landscapes: - std::cout << "Distance : " << l1.distance(l2) << std::endl; - - // here is the scalar product of landscapes: - std::cout << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl; - - // here is how to create a file which is suitable for visualization via gnuplot: - average.plot("average_landscape"); - - return 0; -} diff --git a/example/Persistence_representations/persistence_vectors.cpp b/example/Persistence_representations/persistence_vectors.cpp deleted file mode 100644 index 072e530d..00000000 --- a/example/Persistence_representations/persistence_vectors.cpp +++ /dev/null @@ -1,74 +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 - * - * 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/Persistence_vectors.h> - -#include <iostream> -#include <vector> -#include <cmath> -#include <iomanip> -#include <limits> -#include <utility> - -using Vector_distances_in_diagram = - Gudhi::Persistence_representations::Vector_distances_in_diagram<Gudhi::Euclidean_distance>; - -int main(int argc, char** argv) { - // create two simple vectors with birth--death pairs: - - std::vector<std::pair<double, double> > persistence1; - std::vector<std::pair<double, double> > persistence2; - - persistence1.push_back(std::make_pair(1, 2)); - persistence1.push_back(std::make_pair(6, 8)); - persistence1.push_back(std::make_pair(0, 4)); - persistence1.push_back(std::make_pair(3, 8)); - - persistence2.push_back(std::make_pair(2, 9)); - persistence2.push_back(std::make_pair(1, 6)); - persistence2.push_back(std::make_pair(3, 5)); - persistence2.push_back(std::make_pair(6, 10)); - - // create two persistence vectors based on persistence1 and persistence2: - Vector_distances_in_diagram v1(persistence1, std::numeric_limits<size_t>::max()); - Vector_distances_in_diagram v2(persistence2, std::numeric_limits<size_t>::max()); - - // writing to a stream: - std::cout << "v1 : " << v1 << std::endl; - std::cout << "v2 : " << v2 << std::endl; - - // averages: - Vector_distances_in_diagram average; - average.compute_average({&v1, &v2}); - std::cout << "Average : " << average << std::endl; - - // computations of distances: - std::cout << "l^1 distance : " << v1.distance(v2) << std::endl; - - // computations of scalar product: - std::cout << "Scalar product of l1 and l2 : " << v1.compute_scalar_product(v2) << std::endl; - - // create a file with a gnuplot script: - v1.plot("plot_of_vector_representation"); - - return 0; -} diff --git a/example/Persistent_cohomology/CMakeLists.txt b/example/Persistent_cohomology/CMakeLists.txt deleted file mode 100644 index 0f731519..00000000 --- a/example/Persistent_cohomology/CMakeLists.txt +++ /dev/null @@ -1,69 +0,0 @@ -project(Persistent_cohomology_examples) - -add_executable(plain_homology plain_homology.cpp) - -add_executable(persistence_from_simple_simplex_tree persistence_from_simple_simplex_tree.cpp) - -add_executable(rips_persistence_step_by_step rips_persistence_step_by_step.cpp) -target_link_libraries(rips_persistence_step_by_step ${Boost_PROGRAM_OPTIONS_LIBRARY}) - -add_executable(rips_persistence_via_boundary_matrix rips_persistence_via_boundary_matrix.cpp) -target_link_libraries(rips_persistence_via_boundary_matrix ${Boost_PROGRAM_OPTIONS_LIBRARY}) - -add_executable(persistence_from_file persistence_from_file.cpp) -target_link_libraries(persistence_from_file ${Boost_PROGRAM_OPTIONS_LIBRARY}) - -if (TBB_FOUND) - target_link_libraries(plain_homology ${TBB_LIBRARIES}) - target_link_libraries(persistence_from_simple_simplex_tree ${TBB_LIBRARIES}) - target_link_libraries(rips_persistence_step_by_step ${TBB_LIBRARIES}) - target_link_libraries(rips_persistence_via_boundary_matrix ${TBB_LIBRARIES}) - target_link_libraries(persistence_from_file ${TBB_LIBRARIES}) -endif() - -add_test(NAME Persistent_cohomology_example_plain_homology COMMAND $<TARGET_FILE:plain_homology>) -add_test(NAME Persistent_cohomology_example_from_simple_simplex_tree COMMAND $<TARGET_FILE:persistence_from_simple_simplex_tree> - "1" "0") -add_test(NAME Persistent_cohomology_example_from_rips_step_by_step_on_tore_3D COMMAND $<TARGET_FILE:rips_persistence_step_by_step> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "3") -add_test(NAME Persistent_cohomology_example_via_boundary_matrix COMMAND $<TARGET_FILE:rips_persistence_via_boundary_matrix> - "${CMAKE_SOURCE_DIR}/data/points/Kl.off" "-r" "0.16" "-d" "3" "-p" "3" "-m" "100") -add_test(NAME Persistent_cohomology_example_from_file_3_2_0 COMMAND $<TARGET_FILE:persistence_from_file> - "${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/bunny_5000_complex.fsc" "-p" "2" "-m" "0") -add_test(NAME Persistent_cohomology_example_from_file_3_3_100 COMMAND $<TARGET_FILE:persistence_from_file> - "${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/bunny_5000_complex.fsc" "-p" "3" "-m" "100") - -install(TARGETS plain_homology DESTINATION bin) -install(TARGETS persistence_from_simple_simplex_tree DESTINATION bin) -install(TARGETS rips_persistence_step_by_step DESTINATION bin) -install(TARGETS rips_persistence_via_boundary_matrix DESTINATION bin) -install(TARGETS persistence_from_file DESTINATION bin) - -if(GMP_FOUND) - if(GMPXX_FOUND) - add_executable(rips_multifield_persistence rips_multifield_persistence.cpp ) - target_link_libraries(rips_multifield_persistence - ${Boost_PROGRAM_OPTIONS_LIBRARY} ${GMPXX_LIBRARIES} ${GMP_LIBRARIES}) - if (TBB_FOUND) - target_link_libraries(rips_multifield_persistence ${TBB_LIBRARIES}) - endif(TBB_FOUND) - add_test(NAME Persistent_cohomology_example_multifield_2_71 COMMAND $<TARGET_FILE:rips_multifield_persistence> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "2" "-q" "71") - install(TARGETS rips_multifield_persistence DESTINATION bin) - endif(GMPXX_FOUND) -endif(GMP_FOUND) - -if(CGAL_FOUND) - if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) - add_executable(custom_persistence_sort custom_persistence_sort.cpp) - target_link_libraries(custom_persistence_sort ${CGAL_LIBRARY}) - - if (TBB_FOUND) - target_link_libraries(custom_persistence_sort ${TBB_LIBRARIES}) - endif(TBB_FOUND) - add_test(NAME Persistent_cohomology_example_custom_persistence_sort COMMAND $<TARGET_FILE:custom_persistence_sort>) - - install(TARGETS custom_persistence_sort DESTINATION bin) - - endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) -endif(CGAL_FOUND) diff --git a/example/Persistent_cohomology/README b/example/Persistent_cohomology/README deleted file mode 100644 index f39d9584..00000000 --- a/example/Persistent_cohomology/README +++ /dev/null @@ -1,67 +0,0 @@ -To build the examples, run in a Terminal: - -cd /path-to-examples/ -cmake . -make - -*********************************************************************************************************************** -Example of use of RIPS: - -Computation of the persistent homology with Z/2Z and Z/3Z coefficients simultaneously of the Rips complex -on points sampling a 3D torus: - -./rips_multifield_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.12 -d 3 -p 2 -q 3 - -output: -6 0 0 inf -6 1 0.0983494 inf -6 1 0.104347 inf -6 2 0.138335 inf -6 0 0 0.122545 -6 0 0 0.121171 -6 0 0 0.120964 -6 0 0 0.12057 -6 0 0 0.12047 -6 0 0 0.120414 - -Every line is of this format: p1*...*pr dim b d -where - p1*...*pr is the product of prime numbers pi such that the homology feature exists in homology with Z/piZ coefficients. - dim is the dimension of the homological feature, - b and d are respectively the birth and death of the feature and - -and the computation with all Z/pZ for 2 <= p <= 71 (20 first prime numbers): - - ./rips_multifield_persistence ../../data/points/Kl.off -r 0.25 -m 0.5 -d 3 -p 2 -q 71 - -output: -557940830126698960967415390 0 0 inf -557940830126698960967415390 1 0.0983494 inf -557940830126698960967415390 1 0.104347 inf -557940830126698960967415390 2 0.138335 inf -557940830126698960967415390 0 0 0.122545 -557940830126698960967415390 0 0 0.121171 -557940830126698960967415390 0 0 0.120964 -557940830126698960967415390 0 0 0.12057 -557940830126698960967415390 0 0 0.12047 -557940830126698960967415390 0 0 0.120414 - -*********************************************************************************************************************** -Example of use of PLAIN HOMOLOGY: - -This example computes the plain homology of the following simplicial complex without filtration values: - /* Complex to build. */ - /* 1 3 */ - /* o---o */ - /* /X\ / */ - /* o---o o */ - /* 2 0 4 */ - -./plain_homology - -output: -2 0 0 inf -2 0 0 inf -2 1 0 inf - -Here we retrieve the 2 entities {0,1,2,3} and {4} (Betti numbers[0] = 2) and the hole in {0,1,3} (Betti numbers[1] = 1) diff --git a/example/Persistent_cohomology/custom_persistence_sort.cpp b/example/Persistent_cohomology/custom_persistence_sort.cpp deleted file mode 100644 index 35366144..00000000 --- a/example/Persistent_cohomology/custom_persistence_sort.cpp +++ /dev/null @@ -1,137 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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 <CGAL/Epick_d.h> -#include <CGAL/point_generators_d.h> -#include <CGAL/algorithm.h> -#include <CGAL/assertions.h> - -#include <gudhi/Alpha_complex.h> -#include <gudhi/Persistent_cohomology.h> -// to construct a simplex_tree from alpha complex -#include <gudhi/Simplex_tree.h> - -#include <iostream> -#include <iterator> -#include <vector> -#include <fstream> // for std::ofstream -#include <algorithm> // for std::sort - - -using Kernel = CGAL::Epick_d< CGAL::Dimension_tag<3> >; -using Point = Kernel::Point_d; -using Alpha_complex = Gudhi::alpha_complex::Alpha_complex<Kernel>; -using Simplex_tree = Gudhi::Simplex_tree<>; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology< Simplex_tree, - Gudhi::persistent_cohomology::Field_Zp >; - -std::vector<Point> random_points() { - // Instanciate a random point generator - CGAL::Random rng(0); - - // Generate "points_number" random points in a vector - std::vector<Point> points; - - // Generates 1000 random 3D points on a sphere of radius 4.0 - CGAL::Random_points_on_sphere_d<Point> rand_outside(3, 4.0, rng); - CGAL::cpp11::copy_n(rand_outside, 1000, std::back_inserter(points)); - // Generates 2000 random 3D points in a sphere of radius 3.0 - CGAL::Random_points_in_ball_d<Point> rand_inside(3, 3.0, rng); - CGAL::cpp11::copy_n(rand_inside, 2000, std::back_inserter(points)); - - return points; -} - -/* - * Compare two intervals by dimension, then by length. - */ -struct cmp_intervals_by_dim_then_length { - explicit cmp_intervals_by_dim_then_length(Simplex_tree * sc) - : sc_(sc) { } - - template<typename Persistent_interval> - bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) { - if (sc_->dimension(get < 0 > (p1)) == sc_->dimension(get < 0 > (p2))) - return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1)) - > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2))); - else - return (sc_->dimension(get < 0 > (p1)) > sc_->dimension(get < 0 > (p2))); - } - Simplex_tree* sc_; -}; - -int main(int argc, char **argv) { - std::vector<Point> points = random_points(); - - std::cout << "Points size=" << points.size() << std::endl; - // Alpha complex persistence computation from generated points - Alpha_complex alpha_complex_from_points(points); - std::cout << "alpha_complex_from_points" << std::endl; - - Simplex_tree simplex; - std::cout << "simplex" << std::endl; - if (alpha_complex_from_points.create_complex(simplex, 0.6)) { - std::cout << "simplex" << std::endl; - // ---------------------------------------------------------------------------- - // Display information about the alpha complex - // ---------------------------------------------------------------------------- - std::cout << "Simplicial complex is of dimension " << simplex.dimension() << - " - " << simplex.num_simplices() << " simplices - " << - simplex.num_vertices() << " vertices." << std::endl; - - // Sort the simplices in the order of the filtration - simplex.initialize_filtration(); - - std::cout << "Simplex_tree dim: " << simplex.dimension() << std::endl; - - Persistent_cohomology pcoh(simplex); - - // initializes the coefficient field for homology - Z/3Z - pcoh.init_coefficients(3); - pcoh.compute_persistent_cohomology(0.2); - - // Custom sort and output persistence - cmp_intervals_by_dim_then_length cmp(&simplex); - auto persistent_pairs = pcoh.get_persistent_pairs(); - std::sort(std::begin(persistent_pairs), std::end(persistent_pairs), cmp); - for (auto pair : persistent_pairs) { - std::cout << simplex.dimension(get<0>(pair)) << " " - << simplex.filtration(get<0>(pair)) << " " - << simplex.filtration(get<1>(pair)) << std::endl; - } - - // Persistent Betti numbers - std::cout << "The persistent Betti numbers in interval [0.40, 0.41] are : "; - for (int dim = 0; dim < simplex.dimension(); dim++) - std::cout << "b" << dim << " = " << pcoh.persistent_betti_number(dim, 0.40, 0.41) << " ; "; - std::cout << std::endl; - - // Betti numbers - std::vector<int> betti_numbers = pcoh.betti_numbers(); - std::cout << "The Betti numbers are : "; - for (std::size_t i = 0; i < betti_numbers.size(); i++) - std::cout << "b" << i << " = " << betti_numbers[i] << " ; "; - std::cout << std::endl; - } - return 0; -} - diff --git a/example/Persistent_cohomology/persistence_from_file.cpp b/example/Persistent_cohomology/persistence_from_file.cpp deleted file mode 100644 index 53456919..00000000 --- a/example/Persistent_cohomology/persistence_from_file.cpp +++ /dev/null @@ -1,143 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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/reader_utils.h> -#include <gudhi/graph_simplicial_complex.h> -#include <gudhi/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> - -#include <boost/program_options.hpp> - -#include <string> - -using namespace Gudhi; -using namespace Gudhi::persistent_cohomology; - -typedef int Vertex_handle; -typedef double Filtration_value; - -void program_options(int argc, char * argv[] - , std::string & simplex_tree_file - , std::string & output_file - , int & p - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string simplex_tree_file; - std::string output_file; - int p; - Filtration_value min_persistence; - - program_options(argc, argv, simplex_tree_file, output_file, p, min_persistence); - - std::cout << "Simplex_tree from file=" << simplex_tree_file.c_str() << " - output_file=" << output_file.c_str() - << std::endl; - std::cout << " - p=" << p << " - min_persistence=" << min_persistence << std::endl; - - // Read the list of simplices from a file. - Simplex_tree<> simplex_tree; - - std::ifstream simplex_tree_stream(simplex_tree_file); - simplex_tree_stream >> simplex_tree; - - std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices" << std::endl; - std::cout << " - dimension " << simplex_tree.dimension() << std::endl; - - /* - std::cout << std::endl << std::endl << "Iterator on Simplices in the filtration, with [filtration value]:" << std::endl; - for( auto f_simplex : simplex_tree.filtration_simplex_range() ) - { std::cout << " " << "[" << simplex_tree.filtration(f_simplex) << "] "; - for( auto vertex : simplex_tree.simplex_vertex_range(f_simplex) ) - { std::cout << vertex << " "; } - std::cout << std::endl; - }*/ - - // Sort the simplices in the order of the filtration - simplex_tree.initialize_filtration(); - - // Compute the persistence diagram of the complex - Persistent_cohomology< Simplex_tree<>, Field_Zp > pcoh(simplex_tree); - // initializes the coefficient field for homology - pcoh.init_coefficients(p); - - pcoh.compute_persistent_cohomology(min_persistence); - - // Output the diagram in output_file - if (output_file.empty()) { - pcoh.output_diagram(); - } else { - std::ofstream out(output_file); - pcoh.output_diagram(out); - out.close(); - } - - return 0; -} - -void program_options(int argc, char * argv[] - , std::string & simplex_tree_file - , std::string & output_file - , 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>(&simplex_tree_file), - "Name of file containing a simplex set. Format is one simplex per line (cf. reader_utils.h - read_simplex): Dim1 X11 X12 ... X1d Fil1 "); - - po::options_description visible("Allowed options", 100); - visible.add_options() - ("help,h", "produce help message") - ("output-file,o", po::value<std::string>(&output_file)->default_value(std::string()), - "Name of file in which the persistence diagram is written. Default print in std::cout") - ("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"); - - 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 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; - exit(-1); - } -} diff --git a/example/Persistent_cohomology/persistence_from_simple_simplex_tree.cpp b/example/Persistent_cohomology/persistence_from_simple_simplex_tree.cpp deleted file mode 100644 index ffccfd86..00000000 --- a/example/Persistent_cohomology/persistence_from_simple_simplex_tree.cpp +++ /dev/null @@ -1,175 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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/graph_simplicial_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> - -#include <iostream> -#include <ctime> -#include <utility> -#include <vector> - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<>; -using Filtration_value = Simplex_tree::Filtration_value; -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; -using typeVectorVertex = std::vector< Simplex_tree::Vertex_handle >; - -void usage(char * const progName) { - std::cerr << "Usage: " << progName << " coeff_field_characteristic[integer > 0] min_persistence[float >= -1.0]\n"; - exit(-1); -} - -int main(int argc, char * const argv[]) { - // program args management - if (argc != 3) { - std::cerr << "Error: Number of arguments (" << argc << ") is not correct\n"; - usage(argv[0]); - } - - int coeff_field_characteristic = 0; - int returnedScanValue = sscanf(argv[1], "%d", &coeff_field_characteristic); - if ((returnedScanValue == EOF) || (coeff_field_characteristic <= 0)) { - std::cerr << "Error: " << argv[1] << " is not correct\n"; - usage(argv[0]); - } - - Filtration_value min_persistence = 0.0; - returnedScanValue = sscanf(argv[2], "%lf", &min_persistence); - if ((returnedScanValue == EOF) || (min_persistence < -1.0)) { - std::cerr << "Error: " << argv[2] << " is not correct\n"; - usage(argv[0]); - } - - // TEST OF INSERTION - std::cout << "********************************************************************" << std::endl; - std::cout << "TEST OF INSERTION" << std::endl; - Simplex_tree st; - - // ++ FIRST - std::cout << " - INSERT (0,1,2)" << std::endl; - typeVectorVertex SimplexVector = {0, 1, 2}; - st.insert_simplex_and_subfaces(SimplexVector, 0.3); - - // ++ SECOND - std::cout << " - INSERT 3" << std::endl; - SimplexVector = {3}; - st.insert_simplex_and_subfaces(SimplexVector, 0.1); - - // ++ THIRD - std::cout << " - INSERT (0,3)" << std::endl; - SimplexVector = {0, 3}; - st.insert_simplex_and_subfaces(SimplexVector, 0.2); - - // ++ FOURTH - std::cout << " - INSERT (0,1) (already inserted)" << std::endl; - SimplexVector = {0, 1}; - st.insert_simplex_and_subfaces(SimplexVector, 0.2); - - // ++ FIFTH - std::cout << " - INSERT (3,4,5)" << std::endl; - SimplexVector = {3, 4, 5}; - st.insert_simplex_and_subfaces(SimplexVector, 0.3); - - // ++ SIXTH - std::cout << " - INSERT (0,1,6,7)" << std::endl; - SimplexVector = {0, 1, 6, 7}; - st.insert_simplex_and_subfaces(SimplexVector, 0.4); - - // ++ SEVENTH - std::cout << " - INSERT (4,5,8,9)" << std::endl; - SimplexVector = {4, 5, 8, 9}; - st.insert_simplex_and_subfaces(SimplexVector, 0.4); - - // ++ EIGHTH - std::cout << " - INSERT (9,10,11)" << std::endl; - SimplexVector = {9, 10, 11}; - st.insert_simplex_and_subfaces(SimplexVector, 0.3); - - // ++ NINETH - std::cout << " - INSERT (2,10,12)" << std::endl; - SimplexVector = {2, 10, 12}; - st.insert_simplex_and_subfaces(SimplexVector, 0.3); - - // ++ TENTH - std::cout << " - INSERT (11,6)" << std::endl; - SimplexVector = {6, 11}; - st.insert_simplex_and_subfaces(SimplexVector, 0.2); - - // ++ ELEVENTH - std::cout << " - INSERT (13,14,15)" << std::endl; - SimplexVector = {13, 14, 15}; - st.insert_simplex_and_subfaces(SimplexVector, 0.25); - - /* Inserted simplex: */ - /* 1 6 */ - /* o---o */ - /* /X\7/ 4 2 */ - /* o---o---o---o o */ - /* 2 0 3\X/8\ 10 /X\ */ - /* o---o---o---o */ - /* 5 9\X/ 12 */ - /* o---o */ - /* 11 6 */ - /* In other words: */ - /* A facet [2,1,0] */ - /* An edge [0,3] */ - /* A facet [3,4,5] */ - /* A cell [0,1,6,7] */ - /* A cell [4,5,8,9] */ - /* A facet [9,10,11] */ - /* An edge [11,6] */ - /* An edge [10,12,2] */ - - - std::cout << "The complex contains " << st.num_simplices() << " simplices - " << st.num_vertices() << " vertices " - << std::endl; - std::cout << " - dimension " << st.dimension() << std::endl; - std::cout << std::endl << std::endl << "Iterator on Simplices in the filtration, with [filtration value]:" - << std::endl; - std::cout << "**************************************************************" << std::endl; - std::cout << "strict graph G { " << std::endl; - - for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " << "[" << st.filtration(f_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(f_simplex)) { - std::cout << static_cast<int>(vertex) << " -- "; - } - std::cout << ";" << std::endl; - } - - std::cout << "}" << std::endl; - std::cout << "**************************************************************" << std::endl; - - // Compute the persistence diagram of the complex - Persistent_cohomology pcoh(st); - // initializes the coefficient field for homology - pcoh.init_coefficients(coeff_field_characteristic); - - pcoh.compute_persistent_cohomology(min_persistence); - - // Output the diagram in filediag - pcoh.output_diagram(); - return 0; -} diff --git a/example/Persistent_cohomology/plain_homology.cpp b/example/Persistent_cohomology/plain_homology.cpp deleted file mode 100644 index a2256060..00000000 --- a/example/Persistent_cohomology/plain_homology.cpp +++ /dev/null @@ -1,94 +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): Marc Glisse - * - * Copyright (C) 2015 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/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> - -#include <iostream> -#include <vector> -#include <cstdint> // for std::uint8_t - -/* We could perfectly well use the default Simplex_tree<> (which uses - * Simplex_tree_options_full_featured), the following simply demonstrates - * how to save on storage by not storing a filtration value. */ - -struct MyOptions : Gudhi::Simplex_tree_options_full_featured { - // Implicitly use 0 as filtration value for all simplices - static const bool store_filtration = false; - // The persistence algorithm needs this - static const bool store_key = true; - // I have few vertices - typedef short Vertex_handle; - // Maximum number of simplices to compute persistence is 2^8 - 1 = 255. One is reserved for null_key - typedef std::uint8_t Simplex_key; -}; - -using ST = Gudhi::Simplex_tree<MyOptions>; -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<ST, Field_Zp>; - -int main() { - ST st; - - /* Complex to build. */ - /* 1 3 */ - /* o---o */ - /* /X\ / */ - /* o---o o */ - /* 2 0 4 */ - - const short triangle012[] = {0, 1, 2}; - const short edge03[] = {0, 3}; - const short edge13[] = {1, 3}; - const short vertex4[] = {4}; - st.insert_simplex_and_subfaces(triangle012); - st.insert_simplex_and_subfaces(edge03); - st.insert_simplex(edge13); - st.insert_simplex(vertex4); - - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - - // Class for homology computation - Persistent_cohomology pcoh(st); - - // Initialize the coefficient field Z/2Z for homology - pcoh.init_coefficients(2); - - // Compute the persistence diagram of the complex - pcoh.compute_persistent_cohomology(); - - // Print the result. The format is, on each line: 2 dim 0 inf - // where 2 represents the field, dim the dimension of the feature. - // 2 0 0 inf - // 2 0 0 inf - // 2 1 0 inf - // means that in Z/2Z-homology, the Betti numbers are b0=2 and b1=1. - pcoh.output_diagram(); - - // Print the Betti numbers are b0=2 and b1=1. - std::cout << std::endl; - std::cout << "The Betti numbers are : "; - for (int i = 0; i < st.dimension(); i++) - std::cout << "b" << i << " = " << pcoh.betti_number(i) << " ; "; - std::cout << std::endl; -} diff --git a/example/Persistent_cohomology/rips_multifield_persistence.cpp b/example/Persistent_cohomology/rips_multifield_persistence.cpp deleted file mode 100644 index d6a5bdad..00000000 --- a/example/Persistent_cohomology/rips_multifield_persistence.cpp +++ /dev/null @@ -1,154 +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): Clément Maria - * - * Copyright (C) 2014 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/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Persistent_cohomology/Multi_field.h> -#include <gudhi/Points_off_io.h> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> - -// 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 Multi_field = Gudhi::persistent_cohomology::Multi_field; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Multi_field >; -using Point = std::vector<double>; -using Points_off_reader = Gudhi::Points_off_reader<Point>; - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , int & dim_max - , int & min_p - , int & max_p - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string off_file_points; - std::string filediag; - Filtration_value threshold; - int dim_max; - int min_p; - int max_p; - Filtration_value min_persistence; - - program_options(argc, argv, off_file_points, filediag, threshold, dim_max, min_p, max_p, min_persistence); - - Points_off_reader off_reader(off_file_points); - Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); - - // 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(min_p, max_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[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , int & dim_max - , int & min_p - , int & max_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>(&off_file_points), - "Name of an OFF file containing a point set.\n"); - - po::options_description visible("Allowed options"); - 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") - ("max-edge-length,r", po::value<Filtration_value>(&threshold)->default_value(0), - "Maximal length 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.") - ("min-field-charac,p", po::value<int>(&min_p)->default_value(2), - "Minimal characteristic p of the coefficient field Z/pZ.") - ("max-field-charac,q", po::value<int>(&max_p)->default_value(1223), - "Minimial characteristic q of the coefficient field Z/pZ.") - ("min-persistence,m", po::value<Filtration_value>(&min_persistence), - "Minimal lifetime of homology feature to be recorded. Default is 0"); - - 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 various coefficient fields \n"; - std::cout << "of a Rips complex defined on a set of input points. The coefficient \n"; - std::cout << "fields are all the Z/rZ for a prime number r contained in the \n"; - std::cout << "specified range [p,q]\n \n"; - std::cout << "The output diagram contains one bar per line, written with the convention: \n"; - std::cout << " p1*...*pr 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 << "p1*...*pr is the product of prime numbers pi such that the homology \n"; - std::cout << "feature exists in homology with Z/piZ coefficients." << std::endl << std::endl; - - std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; - std::cout << visible << std::endl; - exit(-1); - } -} diff --git a/example/Persistent_cohomology/rips_persistence_step_by_step.cpp b/example/Persistent_cohomology/rips_persistence_step_by_step.cpp deleted file mode 100644 index 796cfa3a..00000000 --- a/example/Persistent_cohomology/rips_persistence_step_by_step.cpp +++ /dev/null @@ -1,166 +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): Clément Maria - * - * Copyright (C) 2014 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/graph_simplicial_complex.h> -#include <gudhi/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Points_off_io.h> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> -#include <limits> // infinity -#include <utility> // for pair -#include <map> - -// ---------------------------------------------------------------------------- -// rips_persistence_step_by_step is an example of each step that is required to -// build a Rips over a Simplex_tree. Please refer to rips_persistence to see -// how to do the same thing with the Rips_complex wrapper for less detailed -// steps. -// ---------------------------------------------------------------------------- - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; -using Vertex_handle = Simplex_tree::Vertex_handle; -using Filtration_value = Simplex_tree::Filtration_value; -using Proximity_graph = Gudhi::Proximity_graph<Simplex_tree>; - -using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; -using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >; -using Point = std::vector<double>; -using Points_off_reader = Gudhi::Points_off_reader<Point>; - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , int & dim_max - , int & p - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string off_file_points; - std::string filediag; - Filtration_value threshold; - int dim_max; - int p; - Filtration_value min_persistence; - - program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); - - // Extract the points from the file filepoints - Points_off_reader off_reader(off_file_points); - - // Compute the proximity graph of the points - Proximity_graph prox_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(), - threshold, - Gudhi::Euclidean_distance()); - - // Construct the Rips complex in a Simplex Tree - Simplex_tree st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion(dim_max); - - std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << st.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - - // Compute the persistence diagram of the complex - Persistent_cohomology pcoh(st); - // 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[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , 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>(&off_file_points), - "Name of an OFF file containing a point set.\n"); - - 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") - ("max-edge-length,r", - po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), - "Maximal length 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 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; - exit(-1); - } -} diff --git a/example/Persistent_cohomology/rips_persistence_via_boundary_matrix.cpp b/example/Persistent_cohomology/rips_persistence_via_boundary_matrix.cpp deleted file mode 100644 index 71fc0802..00000000 --- a/example/Persistent_cohomology/rips_persistence_via_boundary_matrix.cpp +++ /dev/null @@ -1,172 +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): Clément Maria, Marc Glisse - * - * Copyright (C) 2014 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/Simplex_tree.h> -#include <gudhi/Persistent_cohomology.h> -#include <gudhi/Rips_complex.h> -#include <gudhi/Hasse_complex.h> -#include <gudhi/Points_off_io.h> -#include <gudhi/distance_functions.h> - -#include <boost/program_options.hpp> - -#ifdef GUDHI_USE_TBB -#include <tbb/task_scheduler_init.h> -#endif - -#include <string> -#include <vector> - -//////////////////////////////////////////////////////////////// -// // -// WARNING: persistence computation itself is not parallel, // -// and this uses more memory than rips_persistence. // -// // -//////////////////////////////////////////////////////////////// - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<>; -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 Point = std::vector<double>; -using Points_off_reader = Gudhi::Points_off_reader<Point>; - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , int & dim_max - , int & p - , Filtration_value & min_persistence); - -int main(int argc, char * argv[]) { - std::string off_file_points; - std::string filediag; - Filtration_value threshold; - int dim_max; - int p; - Filtration_value min_persistence; - - program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); - - Points_off_reader off_reader(off_file_points); - Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); - - // Construct the Rips complex in a Simplex Tree - Simplex_tree& st = *new Simplex_tree; - rips_complex_from_file.create_complex(st, dim_max); - - std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << st.dimension() << " \n"; - -#ifdef GUDHI_USE_TBB - // Unnecessary, but clarifies which operations are parallel. - tbb::task_scheduler_init ts; -#endif - - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - int count = 0; - for (auto sh : st.filtration_simplex_range()) - st.assign_key(sh, count++); - - // Convert to a more convenient representation. - Gudhi::Hasse_complex<> hcpx(st); - -#ifdef GUDHI_USE_TBB - ts.terminate(); -#endif - - // Free some space. - delete &st; - - // Compute the persistence diagram of the complex - Gudhi::persistent_cohomology::Persistent_cohomology< Gudhi::Hasse_complex<>, Field_Zp > pcoh(hcpx); - // 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(); - } -} - -void program_options(int argc, char * argv[] - , std::string & off_file_points - , std::string & filediag - , Filtration_value & threshold - , 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>(&off_file_points), - "Name of file containing a point set. Format is one point per line: X1 ... Xd "); - - 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") - ("max-edge-length,r", po::value<Filtration_value>(&threshold)->default_value(0), - "Maximal length 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 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; - exit(-1); - } -} diff --git a/example/Rips_complex/CMakeLists.txt b/example/Rips_complex/CMakeLists.txt deleted file mode 100644 index e7772bdb..00000000 --- a/example/Rips_complex/CMakeLists.txt +++ /dev/null @@ -1,71 +0,0 @@ -project(Rips_complex_examples) - -# Point cloud -add_executable ( Rips_complex_example_from_off example_rips_complex_from_off_file.cpp ) - -add_executable ( Rips_complex_example_one_skeleton_from_points example_one_skeleton_rips_from_points.cpp ) - -# Distance matrix -add_executable ( Rips_complex_example_one_skeleton_from_distance_matrix example_one_skeleton_rips_from_distance_matrix.cpp ) - -add_executable ( Rips_complex_example_from_csv_distance_matrix example_rips_complex_from_csv_distance_matrix_file.cpp ) - -# Sparse rips from points -add_executable ( Rips_complex_example_sparse example_sparse_rips.cpp ) - -# Correlation matrix -add_executable ( Rips_complex_example_one_skeleton_rips_from_correlation_matrix example_one_skeleton_rips_from_correlation_matrix.cpp ) - -if (TBB_FOUND) - target_link_libraries(Rips_complex_example_from_off ${TBB_LIBRARIES}) - target_link_libraries(Rips_complex_example_one_skeleton_from_points ${TBB_LIBRARIES}) - target_link_libraries(Rips_complex_example_one_skeleton_from_distance_matrix ${TBB_LIBRARIES}) - target_link_libraries(Rips_complex_example_from_csv_distance_matrix ${TBB_LIBRARIES}) - target_link_libraries(Rips_complex_example_sparse ${TBB_LIBRARIES}) - target_link_libraries(Rips_complex_example_one_skeleton_rips_from_correlation_matrix ${TBB_LIBRARIES}) -endif() - -add_test(NAME Rips_complex_example_one_skeleton_from_points - COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_from_points>) -add_test(NAME Rips_complex_example_one_skeleton_from_distance_matrix - COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_from_distance_matrix>) -add_test(NAME Rips_complex_example_sparse - COMMAND $<TARGET_FILE:Rips_complex_example_sparse>) -add_test(NAME Rips_complex_example_one_skeleton_rips_from_correlation_matrix - COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_rips_from_correlation_matrix>) - -add_test(NAME Rips_complex_example_from_off_doc_12_1 COMMAND $<TARGET_FILE:Rips_complex_example_from_off> - "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "12.0" "1" "${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_1.txt") -add_test(NAME Rips_complex_example_from_off_doc_12_3 COMMAND $<TARGET_FILE:Rips_complex_example_from_off> - "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "12.0" "3" "${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_3.txt") - -add_test(NAME Rips_complex_example_from_csv_distance_matrix_doc_12_1 COMMAND $<TARGET_FILE:Rips_complex_example_from_csv_distance_matrix> - "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" "12.0" "1" "${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_1.txt") -add_test(NAME Rips_complex_example_from_csv_distance_matrix_doc_12_3 COMMAND $<TARGET_FILE:Rips_complex_example_from_csv_distance_matrix> - "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" "12.0" "3" "${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_3.txt") - - -if (DIFF_PATH) - # Do not forget to copy test results files in current binary dir - file(COPY "one_skeleton_rips_for_doc.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - file(COPY "full_skeleton_rips_for_doc.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - - add_test(Rips_complex_example_from_off_doc_12_1_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_1.txt - ${CMAKE_CURRENT_BINARY_DIR}/one_skeleton_rips_for_doc.txt) - add_test(Rips_complex_example_from_off_doc_12_3_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_3.txt - ${CMAKE_CURRENT_BINARY_DIR}/full_skeleton_rips_for_doc.txt) - add_test(Rips_complex_example_from_csv_distance_matrix_doc_12_1_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_1.txt - ${CMAKE_CURRENT_BINARY_DIR}/one_skeleton_rips_for_doc.txt) - add_test(Rips_complex_example_from_csv_distance_matrix_doc_12_3_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/ripscsvreader_result_12_3.txt - ${CMAKE_CURRENT_BINARY_DIR}/full_skeleton_rips_for_doc.txt) -endif() - -install(TARGETS Rips_complex_example_from_off DESTINATION bin) -install(TARGETS Rips_complex_example_one_skeleton_from_points DESTINATION bin) -install(TARGETS Rips_complex_example_one_skeleton_from_distance_matrix DESTINATION bin) -install(TARGETS Rips_complex_example_from_csv_distance_matrix DESTINATION bin) -install(TARGETS Rips_complex_example_one_skeleton_rips_from_correlation_matrix DESTINATION bin) diff --git a/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp b/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp deleted file mode 100644 index 05bacb9f..00000000 --- a/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp +++ /dev/null @@ -1,81 +0,0 @@ -#include <gudhi/Rips_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <string> -#include <vector> -#include <limits> // for std::numeric_limits - -int main() { - // Type definitions - using Simplex_tree = Gudhi::Simplex_tree<>; - using Filtration_value = Simplex_tree::Filtration_value; - using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; - using Distance_matrix = std::vector<std::vector<Filtration_value>>; - - // User defined correlation matrix is: - // |1 0.06 0.23 0.01 0.89| - // |0.06 1 0.74 0.01 0.61| - // |0.23 0.74 1 0.72 0.03| - // |0.01 0.01 0.72 1 0.7 | - // |0.89 0.61 0.03 0.7 1 | - - Distance_matrix correlations; - correlations.push_back({}); - correlations.push_back({0.06}); - correlations.push_back({0.23, 0.74}); - correlations.push_back({0.01, 0.01, 0.72}); - correlations.push_back({0.89, 0.61, 0.03, 0.7}); - - // ---------------------------------------------------------------------------- - // Convert correlation matrix to a distance matrix: - // ---------------------------------------------------------------------------- - double threshold = 0; - for (size_t i = 0; i != correlations.size(); ++i) { - for (size_t j = 0; j != correlations[i].size(); ++j) { - // Here we check if our data comes from corelation matrix. - 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"; - } - correlations[i][j] = 1 - correlations[i][j]; - // Here we make sure that we will get the treshold value equal to maximal - // distance in the matrix. - if (correlations[i][j] > threshold) threshold = correlations[i][j]; - } - } - - //----------------------------------------------------------------------------- - // Now the correlation matrix is a distance matrix and can be processed further. - //----------------------------------------------------------------------------- - Distance_matrix distances = correlations; - - Rips_complex rips_complex_from_points(distances, threshold); - - Simplex_tree stree; - rips_complex_from_points.create_complex(stree, 1); - // ---------------------------------------------------------------------------- - // Display information about the one skeleton Rips complex. Note that - // the filtration displayed here comes from the distance matrix computed - // above, which is 1 - initial correlation matrix. Only this way, we obtain - // a complex with filtration. If a correlation matrix is used instead, we would - // have a reverse filtration (i.e. filtration of boundary of each simplex S - // is greater or equal to the filtration of S). - // ---------------------------------------------------------------------------- - std::cout << "Rips complex is of dimension " << stree.dimension() << " - " << stree.num_simplices() << " simplices - " - << stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " - << "[" << stree.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - - return 0; -} diff --git a/example/Rips_complex/example_one_skeleton_rips_from_distance_matrix.cpp b/example/Rips_complex/example_one_skeleton_rips_from_distance_matrix.cpp deleted file mode 100644 index bbc3c755..00000000 --- a/example/Rips_complex/example_one_skeleton_rips_from_distance_matrix.cpp +++ /dev/null @@ -1,58 +0,0 @@ -#include <gudhi/Rips_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <string> -#include <vector> -#include <limits> // for std::numeric_limits - -int main() { - // Type definitions - using Simplex_tree = Gudhi::Simplex_tree<>; - using Filtration_value = Simplex_tree::Filtration_value; - using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; - using Distance_matrix = std::vector<std::vector<Filtration_value>>; - - // User defined distance matrix is: - // | 0 0.94 0.77 0.99 0.11 | - // | 0.94 0 0.26 0.99 0.39 | - // | 0.77 0.26 0 0.28 0.97 | - // | 0.99 0.99 0.28 0 0.30 | - // | 0.11 0.39 0.97 0.30 0 | - - Distance_matrix distances; - distances.push_back({}); - distances.push_back({0.94}); - distances.push_back({0.77, 0.26}); - distances.push_back({0.99, 0.99, 0.28}); - distances.push_back({0.11, 0.39, 0.97, 0.30}); - - // ---------------------------------------------------------------------------- - // Init of a Rips complex from points - // ---------------------------------------------------------------------------- - double threshold = 1.0; - Rips_complex rips_complex_from_points(distances, threshold); - - Simplex_tree stree; - rips_complex_from_points.create_complex(stree, 1); - // ---------------------------------------------------------------------------- - // Display information about the one skeleton Rips complex - // ---------------------------------------------------------------------------- - std::cout << "Rips complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - - return 0; -} diff --git a/example/Rips_complex/example_one_skeleton_rips_from_points.cpp b/example/Rips_complex/example_one_skeleton_rips_from_points.cpp deleted file mode 100644 index a1db8910..00000000 --- a/example/Rips_complex/example_one_skeleton_rips_from_points.cpp +++ /dev/null @@ -1,52 +0,0 @@ -#include <gudhi/Rips_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <string> -#include <vector> -#include <limits> // for std::numeric_limits - -int main() { - // Type definitions - using Point = std::vector<double>; - 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>; - - std::vector<Point> points; - points.push_back({1.0, 1.0}); - points.push_back({7.0, 0.0}); - points.push_back({4.0, 6.0}); - points.push_back({9.0, 6.0}); - points.push_back({0.0, 14.0}); - points.push_back({2.0, 19.0}); - points.push_back({9.0, 17.0}); - - // ---------------------------------------------------------------------------- - // Init of a Rips complex from points - // ---------------------------------------------------------------------------- - double threshold = 12.0; - Rips_complex rips_complex_from_points(points, threshold, Gudhi::Euclidean_distance()); - - Simplex_tree stree; - rips_complex_from_points.create_complex(stree, 1); - // ---------------------------------------------------------------------------- - // Display information about the one skeleton Rips complex - // ---------------------------------------------------------------------------- - std::cout << "Rips complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - return 0; -} diff --git a/example/Rips_complex/example_rips_complex_from_csv_distance_matrix_file.cpp b/example/Rips_complex/example_rips_complex_from_csv_distance_matrix_file.cpp deleted file mode 100644 index 9e182f1e..00000000 --- a/example/Rips_complex/example_rips_complex_from_csv_distance_matrix_file.cpp +++ /dev/null @@ -1,72 +0,0 @@ -#include <gudhi/Rips_complex.h> -// to construct Rips_complex from a csv file representing a distance matrix -#include <gudhi/reader_utils.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <string> -#include <vector> - -void usage(int nbArgs, char * const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " filename.csv threshold dim_max [ouput_file.txt]\n"; - std::cerr << " i.e.: " << progName << " ../../data/distance_matrix/full_square_distance_matrix.csv 1.0 3\n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 4) && (argc != 5)) usage(argc, (argv[0] - 1)); - - std::string csv_file_name(argv[1]); - double threshold = atof(argv[2]); - int dim_max = atoi(argv[3]); - - // Type definitions - using Simplex_tree = Gudhi::Simplex_tree<>; - using Filtration_value = Simplex_tree::Filtration_value; - using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; - using Distance_matrix = std::vector<std::vector<Filtration_value>>; - - // ---------------------------------------------------------------------------- - // Init of a Rips complex from a distance matrix in a csv file - // Default separator is ';' - // ---------------------------------------------------------------------------- - Distance_matrix distances = Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_file_name); - Rips_complex rips_complex_from_file(distances, threshold); - - std::streambuf* streambufffer; - std::ofstream ouput_file_stream; - - if (argc == 5) { - ouput_file_stream.open(std::string(argv[4])); - streambufffer = ouput_file_stream.rdbuf(); - } else { - streambufffer = std::cout.rdbuf(); - } - - Simplex_tree stree; - rips_complex_from_file.create_complex(stree, dim_max); - std::ostream output_stream(streambufffer); - - // ---------------------------------------------------------------------------- - // Display information about the Rips complex - // ---------------------------------------------------------------------------- - output_stream << "Rips complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; - - output_stream << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - output_stream << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - output_stream << vertex << " "; - } - output_stream << ") -> " << "[" << stree.filtration(f_simplex) << "] "; - output_stream << std::endl; - } - - ouput_file_stream.close(); - return 0; -} diff --git a/example/Rips_complex/example_rips_complex_from_off_file.cpp b/example/Rips_complex/example_rips_complex_from_off_file.cpp deleted file mode 100644 index de2e4ea4..00000000 --- a/example/Rips_complex/example_rips_complex_from_off_file.cpp +++ /dev/null @@ -1,71 +0,0 @@ -#include <gudhi/Rips_complex.h> -// to construct Rips_complex from a OFF file of points -#include <gudhi/Points_off_io.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <string> -#include <vector> - -void usage(int nbArgs, char * const progName) { - std::cerr << "Error: Number of arguments (" << nbArgs << ") is not correct\n"; - std::cerr << "Usage: " << progName << " filename.off threshold dim_max [ouput_file.txt]\n"; - std::cerr << " i.e.: " << progName << " ../../data/points/alphacomplexdoc.off 60.0\n"; - exit(-1); // ----- >> -} - -int main(int argc, char **argv) { - if ((argc != 4) && (argc != 5)) usage(argc, (argv[0] - 1)); - - std::string off_file_name(argv[1]); - double threshold = atof(argv[2]); - int dim_max = atoi(argv[3]); - - // Type definitions - using Point = std::vector<float>; - using Simplex_tree = Gudhi::Simplex_tree<>; - using Filtration_value = Simplex_tree::Filtration_value; - using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>; - - // ---------------------------------------------------------------------------- - // Init of a Rips complex from an OFF file - // ---------------------------------------------------------------------------- - Gudhi::Points_off_reader<Point> off_reader(off_file_name); - Rips_complex rips_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); - - std::streambuf* streambufffer; - std::ofstream ouput_file_stream; - - if (argc == 5) { - ouput_file_stream.open(std::string(argv[4])); - streambufffer = ouput_file_stream.rdbuf(); - } else { - streambufffer = std::cout.rdbuf(); - } - - Simplex_tree stree; - rips_complex_from_file.create_complex(stree, dim_max); - std::ostream output_stream(streambufffer); - - // ---------------------------------------------------------------------------- - // Display information about the Rips complex - // ---------------------------------------------------------------------------- - output_stream << "Rips complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; - - output_stream << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - output_stream << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - output_stream << vertex << " "; - } - output_stream << ") -> " << "[" << stree.filtration(f_simplex) << "] "; - output_stream << std::endl; - } - - ouput_file_stream.close(); - return 0; -} diff --git a/example/Rips_complex/example_sparse_rips.cpp b/example/Rips_complex/example_sparse_rips.cpp deleted file mode 100644 index 1c95b48c..00000000 --- a/example/Rips_complex/example_sparse_rips.cpp +++ /dev/null @@ -1,30 +0,0 @@ -#include <gudhi/Sparse_rips_complex.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/distance_functions.h> - -#include <iostream> -#include <vector> - -int main() { - using Point = std::vector<double>; - using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>; - using Filtration_value = Simplex_tree::Filtration_value; - using Sparse_rips = Gudhi::rips_complex::Sparse_rips_complex<Filtration_value>; - - Point points[] = {{1.0, 1.0}, {7.0, 0.0}, {4.0, 6.0}, {9.0, 6.0}, {0.0, 14.0}, {2.0, 19.0}, {9.0, 17.0}}; - - // ---------------------------------------------------------------------------- - // Init from Euclidean points - // ---------------------------------------------------------------------------- - double epsilon = 2; // very rough, no guarantees - Sparse_rips sparse_rips(points, Gudhi::Euclidean_distance(), epsilon); - - Simplex_tree stree; - sparse_rips.create_complex(stree, 10); - - // ---------------------------------------------------------------------------- - // Display information about the complex - // ---------------------------------------------------------------------------- - std::cout << "Sparse Rips complex is of dimension " << stree.dimension() << " - " << stree.num_simplices() - << " simplices - " << stree.num_vertices() << " vertices." << std::endl; -} diff --git a/example/Rips_complex/full_skeleton_rips_for_doc.txt b/example/Rips_complex/full_skeleton_rips_for_doc.txt deleted file mode 100644 index 55de4ab8..00000000 --- a/example/Rips_complex/full_skeleton_rips_for_doc.txt +++ /dev/null @@ -1,26 +0,0 @@ -Rips complex is of dimension 3 - 24 simplices - 7 vertices. -Iterator on Rips complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 3 2 ) -> [5] - ( 5 4 ) -> [5.38516] - ( 2 0 ) -> [5.83095] - ( 1 0 ) -> [6.08276] - ( 3 1 ) -> [6.32456] - ( 2 1 ) -> [6.7082] - ( 2 1 0 ) -> [6.7082] - ( 3 2 1 ) -> [6.7082] - ( 6 5 ) -> [7.28011] - ( 4 2 ) -> [8.94427] - ( 3 0 ) -> [9.43398] - ( 3 1 0 ) -> [9.43398] - ( 3 2 0 ) -> [9.43398] - ( 3 2 1 0 ) -> [9.43398] - ( 6 4 ) -> [9.48683] - ( 6 5 4 ) -> [9.48683] - ( 6 3 ) -> [11] diff --git a/example/Rips_complex/one_skeleton_rips_for_doc.txt b/example/Rips_complex/one_skeleton_rips_for_doc.txt deleted file mode 100644 index 706512a5..00000000 --- a/example/Rips_complex/one_skeleton_rips_for_doc.txt +++ /dev/null @@ -1,20 +0,0 @@ -Rips complex is of dimension 1 - 18 simplices - 7 vertices. -Iterator on Rips complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 3 2 ) -> [5] - ( 5 4 ) -> [5.38516] - ( 2 0 ) -> [5.83095] - ( 1 0 ) -> [6.08276] - ( 3 1 ) -> [6.32456] - ( 2 1 ) -> [6.7082] - ( 6 5 ) -> [7.28011] - ( 4 2 ) -> [8.94427] - ( 3 0 ) -> [9.43398] - ( 6 4 ) -> [9.48683] - ( 6 3 ) -> [11] diff --git a/example/Rips_complex/one_skeleton_rips_from_correlation_matrix_for_doc.txt b/example/Rips_complex/one_skeleton_rips_from_correlation_matrix_for_doc.txt deleted file mode 100644 index 640d7083..00000000 --- a/example/Rips_complex/one_skeleton_rips_from_correlation_matrix_for_doc.txt +++ /dev/null @@ -1,17 +0,0 @@ -Rips complex is of dimension 1 - 15 simplices - 5 vertices. -Iterator on Rips complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 4 0 ) -> [0.11] - ( 2 1 ) -> [0.26] - ( 3 2 ) -> [0.28] - ( 4 3 ) -> [0.3] - ( 4 1 ) -> [0.39] - ( 2 0 ) -> [0.77] - ( 1 0 ) -> [0.94] - ( 4 2 ) -> [0.97] - ( 3 0 ) -> [0.99] - ( 3 1 ) -> [0.99] diff --git a/example/Simplex_tree/CMakeLists.txt b/example/Simplex_tree/CMakeLists.txt deleted file mode 100644 index 857e8518..00000000 --- a/example/Simplex_tree/CMakeLists.txt +++ /dev/null @@ -1,54 +0,0 @@ -project(Simplex_tree_examples) - -add_executable ( Simplex_tree_example_from_cliques_of_graph simplex_tree_from_cliques_of_graph.cpp ) -if (TBB_FOUND) - target_link_libraries(Simplex_tree_example_from_cliques_of_graph ${TBB_LIBRARIES}) -endif() -add_test(NAME Simplex_tree_example_from_cliques_of_graph_2 COMMAND $<TARGET_FILE:Simplex_tree_example_from_cliques_of_graph> - "${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/Klein_bottle_complex.fsc" "2") -add_test(NAME Simplex_tree_example_from_cliques_of_graph_3 COMMAND $<TARGET_FILE:Simplex_tree_example_from_cliques_of_graph> - "${CMAKE_SOURCE_DIR}/data/filtered_simplicial_complex/Klein_bottle_complex.fsc" "3") - -add_executable ( Simplex_tree_example_simple_simplex_tree simple_simplex_tree.cpp ) -if (TBB_FOUND) - target_link_libraries(Simplex_tree_example_simple_simplex_tree ${TBB_LIBRARIES}) -endif() -add_test(NAME Simplex_tree_example_simple_simplex_tree COMMAND $<TARGET_FILE:Simplex_tree_example_simple_simplex_tree>) - -add_executable ( Simplex_tree_example_mini_simplex_tree mini_simplex_tree.cpp ) -add_test(NAME Simplex_tree_example_mini_simplex_tree COMMAND $<TARGET_FILE:Simplex_tree_example_mini_simplex_tree>) - -install(TARGETS Simplex_tree_example_from_cliques_of_graph DESTINATION bin) -install(TARGETS Simplex_tree_example_simple_simplex_tree DESTINATION bin) -install(TARGETS Simplex_tree_example_mini_simplex_tree DESTINATION bin) - -# An example with Simplex-tree using CGAL alpha_shapes_3 -if(GMP_FOUND AND CGAL_FOUND) - add_executable ( Simplex_tree_example_alpha_shapes_3_from_off example_alpha_shapes_3_simplex_tree_from_off_file.cpp ) - target_link_libraries(Simplex_tree_example_alpha_shapes_3_from_off ${GMP_LIBRARIES} ${CGAL_LIBRARY}) - if (TBB_FOUND) - target_link_libraries(Simplex_tree_example_alpha_shapes_3_from_off ${TBB_LIBRARIES}) - endif() - add_test(NAME Simplex_tree_example_alpha_shapes_3_from_off COMMAND $<TARGET_FILE:Simplex_tree_example_alpha_shapes_3_from_off> - "${CMAKE_SOURCE_DIR}/data/points/bunny_5000.off") - - install(TARGETS Simplex_tree_example_alpha_shapes_3_from_off DESTINATION bin) - - add_executable ( Simplex_tree_example_cech_complex_cgal_mini_sphere_3d cech_complex_cgal_mini_sphere_3d.cpp ) - target_link_libraries(Simplex_tree_example_cech_complex_cgal_mini_sphere_3d ${Boost_PROGRAM_OPTIONS_LIBRARY} ${CGAL_LIBRARY}) - if (TBB_FOUND) - target_link_libraries(Simplex_tree_example_cech_complex_cgal_mini_sphere_3d ${TBB_LIBRARIES}) - endif() - add_test(NAME Simplex_tree_example_cech_complex_cgal_mini_sphere_3d COMMAND $<TARGET_FILE:Simplex_tree_example_cech_complex_cgal_mini_sphere_3d> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" -r 0.3 -d 3) - - install(TARGETS Simplex_tree_example_alpha_shapes_3_from_off DESTINATION bin) -endif() - -add_executable ( Simplex_tree_example_graph_expansion_with_blocker graph_expansion_with_blocker.cpp ) -if (TBB_FOUND) - target_link_libraries(Simplex_tree_example_graph_expansion_with_blocker ${TBB_LIBRARIES}) -endif() -add_test(NAME Simplex_tree_example_graph_expansion_with_blocker COMMAND $<TARGET_FILE:Simplex_tree_example_graph_expansion_with_blocker>) - -install(TARGETS Simplex_tree_example_graph_expansion_with_blocker DESTINATION bin) diff --git a/example/Simplex_tree/README b/example/Simplex_tree/README deleted file mode 100644 index a9498173..00000000 --- a/example/Simplex_tree/README +++ /dev/null @@ -1,73 +0,0 @@ -To build the example, run in a Terminal: - -cd /path-to-gudhi/ -cmake . -cd /path-to-example/ -make - - -Example of use : - -*** Simple simplex tree construction - -./Simplex_tree_example_simple_simplex_tree - -******************************************************************** -EXAMPLE OF SIMPLE INSERTION - * INSERT 0 - + 0 INSERTED - * INSERT 1 - + 1 INSERTED - * INSERT (0,1) - + (0,1) INSERTED - * INSERT 2 - + 2 INSERTED - * INSERT (2,0) - + (2,0) INSERTED - * INSERT (2,1) - + (2,1) INSERTED - * INSERT (2,1,0) - + (2,1,0) INSERTED - * INSERT 3 - + 3 INSERTED - * INSERT (3,0) - + (3,0) INSERTED - * INSERT 0 (already inserted) - - 0 NOT INSERTED - * INSERT (2,1,0) (already inserted) - - (2,1,0) NOT INSERTED -******************************************************************** -* The complex contains 9 simplices - - dimension 2 - filtration 0.4 -* Iterator on Simplices in the filtration, with [filtration value]: - [0.1] 0 - [0.1] 1 - [0.1] 2 - [0.1] 3 - [0.2] 1 0 - [0.2] 2 0 - [0.2] 2 1 - [0.2] 3 0 - [0.3] 2 1 0 - -*** Simplex tree construction with Z/2Z coefficients on weighted graph Klein bottle file: - -./Simplex_tree_example_from_cliques_of_graph ../../../data/points/Klein_bottle_complex.txt 2 -Insert the 1-skeleton in the simplex tree in 0 s. -Expand the simplex tree in 0 s. -Information of the Simplex Tree: - Number of vertices = 10 Number of simplices = 82 - -with Z/3Z coefficients: - -./Simplex_tree_example_from_cliques_of_graph ../../../data/points/Klein_bottle_complex.txt 3 - -Insert the 1-skeleton in the simplex tree in 0 s. -Expand the simplex tree in 0 s. -Information of the Simplex Tree: - Number of vertices = 10 Number of simplices = 106 - -*** Simplex_tree computed and displayed from a 3D alpha complex: - [ Requires CGAL, GMP and GMPXX to be installed] - -./Simplex_tree_example_alpha_shapes_3_from_off ../../../data/points/bunny_5000 diff --git a/example/Simplex_tree/cech_complex_cgal_mini_sphere_3d.cpp b/example/Simplex_tree/cech_complex_cgal_mini_sphere_3d.cpp deleted file mode 100644 index 34092ef6..00000000 --- a/example/Simplex_tree/cech_complex_cgal_mini_sphere_3d.cpp +++ /dev/null @@ -1,221 +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): Vincent Rouvreau - * - * Copyright (C) 2017 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/graph_simplicial_complex.h> -#include <gudhi/distance_functions.h> -#include <gudhi/Simplex_tree.h> -#include <gudhi/Points_off_io.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Min_sphere_of_spheres_d.h> -#include <CGAL/Min_sphere_of_points_d_traits_d.h> - -#include <boost/program_options.hpp> - -#include <string> -#include <vector> -#include <limits> // infinity -#include <utility> // for pair -#include <map> - -// ------------------------------------------------------------------------------- -// cech_complex_cgal_mini_sphere_3d is an example of each step that is required to -// build a Cech over a Simplex_tree. Please refer to cech_persistence to see -// how to do the same thing with the Cech_complex wrapper for less detailed -// steps. -// ------------------------------------------------------------------------------- - -// Types definition -using Simplex_tree = Gudhi::Simplex_tree<>; -using Vertex_handle = Simplex_tree::Vertex_handle; -using Simplex_handle = Simplex_tree::Simplex_handle; -using Filtration_value = Simplex_tree::Filtration_value; -using Siblings = Simplex_tree::Siblings; -using Graph_t = boost::adjacency_list<boost::vecS, boost::vecS, boost::undirectedS, - boost::property<Gudhi::vertex_filtration_t, Filtration_value>, - boost::property<Gudhi::edge_filtration_t, Filtration_value> >; -using Edge_t = std::pair<Vertex_handle, Vertex_handle>; - -using Kernel = CGAL::Epick_d<CGAL::Dimension_tag<3> >; -using Point = Kernel::Point_d; -using Traits = CGAL::Min_sphere_of_points_d_traits_d<Kernel, Filtration_value, 3>; -using Min_sphere = CGAL::Min_sphere_of_spheres_d<Traits>; - -using Points_off_reader = Gudhi::Points_off_reader<Point>; - -class Cech_blocker { - public: - bool operator()(Simplex_handle sh) { - std::vector<Point> points; -#if DEBUG_TRACES - std::cout << "Cech_blocker on ["; -#endif // DEBUG_TRACES - for (auto vertex : simplex_tree_.simplex_vertex_range(sh)) { - points.push_back(point_cloud_[vertex]); -#if DEBUG_TRACES - std::cout << vertex << ", "; -#endif // DEBUG_TRACES - } - Min_sphere ms(points.begin(), points.end()); - Filtration_value radius = ms.radius(); -#if DEBUG_TRACES - std::cout << "] - radius = " << radius << " - returns " << (radius > threshold_) << std::endl; -#endif // DEBUG_TRACES - simplex_tree_.assign_filtration(sh, radius); - return (radius > threshold_); - } - Cech_blocker(Simplex_tree& simplex_tree, Filtration_value threshold, const std::vector<Point>& point_cloud) - : simplex_tree_(simplex_tree), threshold_(threshold), point_cloud_(point_cloud) {} - - private: - Simplex_tree simplex_tree_; - Filtration_value threshold_; - std::vector<Point> point_cloud_; -}; - -template <typename InputPointRange> -Graph_t compute_proximity_graph(InputPointRange& points, Filtration_value threshold); - -void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& threshold, int& dim_max); - -int main(int argc, char* argv[]) { - std::string off_file_points; - Filtration_value threshold; - int dim_max; - - program_options(argc, argv, off_file_points, threshold, dim_max); - - // Extract the points from the file filepoints - Points_off_reader off_reader(off_file_points); - - // Compute the proximity graph of the points - Graph_t prox_graph = compute_proximity_graph(off_reader.get_point_cloud(), threshold); - - // Min_sphere sph1(off_reader.get_point_cloud()[0], off_reader.get_point_cloud()[1], off_reader.get_point_cloud()[2]); - // Construct the Rips complex in a Simplex Tree - Simplex_tree st; - // insert the proximity graph in the simplex tree - st.insert_graph(prox_graph); - // expand the graph until dimension dim_max - st.expansion_with_blockers(dim_max, Cech_blocker(st, threshold, off_reader.get_point_cloud())); - - std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; - std::cout << " and has dimension " << st.dimension() << " \n"; - - // Sort the simplices in the order of the filtration - st.initialize_filtration(); - -#if DEBUG_TRACES - std::cout << "********************************************************************\n"; - // Display the Simplex_tree - Can not be done in the middle of 2 inserts - std::cout << "* The complex contains " << st.num_simplices() << " simplices - dimension=" << st.dimension() << "\n"; - std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; - for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " - << "[" << st.filtration(f_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(f_simplex)) { - std::cout << static_cast<int>(vertex) << " "; - } - std::cout << std::endl; - } -#endif // DEBUG_TRACES - return 0; -} - -void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& threshold, int& dim_max) { - namespace po = boost::program_options; - po::options_description hidden("Hidden options"); - hidden.add_options()("input-file", po::value<std::string>(&off_file_points), - "Name of an OFF file containing a 3d point set.\n"); - - po::options_description visible("Allowed options", 100); - visible.add_options()("help,h", "produce help message")( - "max-edge-length,r", - po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()), - "Maximal length of an edge for the Cech complex construction.")( - "cpx-dimension,d", po::value<int>(&dim_max)->default_value(1), - "Maximal dimension of the Cech 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 << "Construct a Cech complex defined on a set of input points.\n \n"; - - std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; - std::cout << visible << std::endl; - exit(-1); - } -} - -/** Output the proximity graph of the points. - * - * If points contains n elements, the proximity graph is the graph - * with n vertices, and an edge [u,v] iff the distance function between - * points u and v is smaller than threshold. - * - * The type PointCloud furnishes .begin() and .end() methods, that return - * iterators with value_type Point. - */ -template <typename InputPointRange> -Graph_t compute_proximity_graph(InputPointRange& points, Filtration_value threshold) { - std::vector<Edge_t> edges; - std::vector<Filtration_value> edges_fil; - - Kernel k; - Vertex_handle idx_u, idx_v; - Filtration_value fil; - idx_u = 0; - for (auto it_u = points.begin(); it_u != points.end(); ++it_u) { - idx_v = idx_u + 1; - for (auto it_v = it_u + 1; it_v != points.end(); ++it_v, ++idx_v) { - fil = k.squared_distance_d_object()(*it_u, *it_v); - // For Cech Complex, threshold is a radius (distance /2) - fil = std::sqrt(fil) / 2.; - if (fil <= threshold) { - edges.emplace_back(idx_u, idx_v); - edges_fil.push_back(fil); - } - } - ++idx_u; - } - - Graph_t skel_graph(edges.begin(), edges.end(), edges_fil.begin(), - idx_u); // number of points labeled from 0 to idx_u-1 - - auto vertex_prop = boost::get(Gudhi::vertex_filtration_t(), skel_graph); - - boost::graph_traits<Graph_t>::vertex_iterator vi, vi_end; - for (std::tie(vi, vi_end) = boost::vertices(skel_graph); vi != vi_end; ++vi) { - boost::put(vertex_prop, *vi, 0.); - } - - return skel_graph; -} diff --git a/example/Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp b/example/Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp deleted file mode 100644 index 290a9d9b..00000000 --- a/example/Simplex_tree/example_alpha_shapes_3_simplex_tree_from_off_file.cpp +++ /dev/null @@ -1,276 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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/Simplex_tree.h> -#include <gudhi/Points_3D_off_io.h> - -#include <boost/variant.hpp> - -#include <CGAL/Exact_predicates_inexact_constructions_kernel.h> -#include <CGAL/Delaunay_triangulation_3.h> -#include <CGAL/Alpha_shape_3.h> -#include <CGAL/Alpha_shape_vertex_base_3.h> -#include <CGAL/Alpha_shape_cell_base_3.h> -#include <CGAL/iterator.h> - -#include <fstream> -#include <cmath> -#include <string> -#include <tuple> // for tuple<> -#include <map> -#include <utility> // for pair<> -#include <list> -#include <vector> - -// Alpha_shape_3 templates type definitions -typedef CGAL::Exact_predicates_inexact_constructions_kernel Kernel; -typedef CGAL::Alpha_shape_vertex_base_3<Kernel> Vb; -typedef CGAL::Alpha_shape_cell_base_3<Kernel> Fb; -typedef CGAL::Triangulation_data_structure_3<Vb, Fb> Tds; -typedef CGAL::Delaunay_triangulation_3<Kernel, Tds> Triangulation_3; -typedef CGAL::Alpha_shape_3<Triangulation_3> Alpha_shape_3; - -// From file type definition -typedef Kernel::Point_3 Point; - -// filtration with alpha values needed type definition -typedef Alpha_shape_3::FT Alpha_value_type; -typedef CGAL::Object Object; -typedef CGAL::Dispatch_output_iterator< -CGAL::cpp11::tuple<Object, Alpha_value_type>, -CGAL::cpp11::tuple<std::back_insert_iterator< std::vector<Object> >, - std::back_insert_iterator< std::vector<Alpha_value_type> > > > Dispatch; -typedef Alpha_shape_3::Cell_handle Cell_handle; -typedef Alpha_shape_3::Facet Facet; -typedef Alpha_shape_3::Edge Edge; -typedef std::list<Alpha_shape_3::Vertex_handle> Vertex_list; - -// gudhi type definition -typedef Gudhi::Simplex_tree<> Simplex_tree; -typedef Simplex_tree::Vertex_handle Simplex_tree_vertex; -typedef std::map<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex > Alpha_shape_simplex_tree_map; -typedef std::pair<Alpha_shape_3::Vertex_handle, Simplex_tree_vertex> Alpha_shape_simplex_tree_pair; -typedef std::vector< Simplex_tree_vertex > Simplex_tree_vector_vertex; - -Vertex_list from(const Cell_handle& ch) { - Vertex_list the_list; - for (auto i = 0; i < 4; i++) { -#ifdef DEBUG_TRACES - std::cout << "from cell[" << i << "]=" << ch->vertex(i)->point() << std::endl; -#endif // DEBUG_TRACES - the_list.push_back(ch->vertex(i)); - } - return the_list; -} - -Vertex_list from(const Facet& fct) { - Vertex_list the_list; - for (auto i = 0; i < 4; i++) { - if (fct.second != i) { -#ifdef DEBUG_TRACES - std::cout << "from facet=[" << i << "]" << fct.first->vertex(i)->point() << std::endl; -#endif // DEBUG_TRACES - the_list.push_back(fct.first->vertex(i)); - } - } - return the_list; -} - -Vertex_list from(const Edge& edg) { - Vertex_list the_list; - for (auto i = 0; i < 4; i++) { - if ((edg.second == i) || (edg.third == i)) { -#ifdef DEBUG_TRACES - std::cout << "from edge[" << i << "]=" << edg.first->vertex(i)->point() << std::endl; -#endif // DEBUG_TRACES - the_list.push_back(edg.first->vertex(i)); - } - } - return the_list; -} - -Vertex_list from(const Alpha_shape_3::Vertex_handle& vh) { - Vertex_list the_list; -#ifdef DEBUG_TRACES - std::cout << "from vertex=" << vh->point() << std::endl; -#endif // DEBUG_TRACES - the_list.push_back(vh); - return the_list; -} - -int main(int argc, char * const argv[]) { - // program args management - if (argc != 2) { - std::cerr << "Usage: " << argv[0] - << " path_to_off_file \n"; - return 0; - } - - // Read points from file - std::string offInputFile(argv[1]); - // Read the OFF file (input file name given as parameter) and triangulate points - Gudhi::Points_3D_off_reader<Point> off_reader(offInputFile); - // Check the read operation was correct - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file " << argv[1] << std::endl; - return 0; - } - // Retrieve the triangulation - std::vector<Point> lp = off_reader.get_point_cloud(); - - // alpha shape construction from points. CGAL has a strange behavior in REGULARIZED mode. - Alpha_shape_3 as(lp.begin(), lp.end(), 0, Alpha_shape_3::GENERAL); -#ifdef DEBUG_TRACES - std::cout << "Alpha shape computed in GENERAL mode" << std::endl; -#endif // DEBUG_TRACES - - // filtration with alpha values from alpha shape - std::vector<Object> the_objects; - std::vector<Alpha_value_type> the_alpha_values; - - Dispatch disp = CGAL::dispatch_output<Object, Alpha_value_type>(std::back_inserter(the_objects), - std::back_inserter(the_alpha_values)); - - as.filtration_with_alpha_values(disp); -#ifdef DEBUG_TRACES - std::cout << "filtration_with_alpha_values returns : " << the_objects.size() << " objects" << std::endl; -#endif // DEBUG_TRACES - - Alpha_shape_3::size_type count_vertices = 0; - Alpha_shape_3::size_type count_edges = 0; - Alpha_shape_3::size_type count_facets = 0; - Alpha_shape_3::size_type count_cells = 0; - - // Loop on objects vector - Vertex_list vertex_list; - Simplex_tree simplex_tree; - Alpha_shape_simplex_tree_map map_cgal_simplex_tree; - std::vector<Alpha_value_type>::iterator the_alpha_value_iterator = the_alpha_values.begin(); - for (auto object_iterator : the_objects) { - // Retrieve Alpha shape vertex list from object - if (const Cell_handle * cell = CGAL::object_cast<Cell_handle>(&object_iterator)) { - vertex_list = from(*cell); - count_cells++; - } else if (const Facet * facet = CGAL::object_cast<Facet>(&object_iterator)) { - vertex_list = from(*facet); - count_facets++; - } else if (const Edge * edge = CGAL::object_cast<Edge>(&object_iterator)) { - vertex_list = from(*edge); - count_edges++; - } else if (const Alpha_shape_3::Vertex_handle * vertex = - CGAL::object_cast<Alpha_shape_3::Vertex_handle>(&object_iterator)) { - count_vertices++; - vertex_list = from(*vertex); - } - // Construction of the vector of simplex_tree vertex from list of alpha_shapes vertex - Simplex_tree_vector_vertex the_simplex_tree; - for (auto the_alpha_shape_vertex : vertex_list) { - Alpha_shape_simplex_tree_map::iterator the_map_iterator = map_cgal_simplex_tree.find(the_alpha_shape_vertex); - if (the_map_iterator == map_cgal_simplex_tree.end()) { - // alpha shape not found - Simplex_tree_vertex vertex = map_cgal_simplex_tree.size(); -#ifdef DEBUG_TRACES - std::cout << "vertex [" << the_alpha_shape_vertex->point() << "] not found - insert_simplex " << vertex << "\n"; -#endif // DEBUG_TRACES - the_simplex_tree.push_back(vertex); - map_cgal_simplex_tree.insert(Alpha_shape_simplex_tree_pair(the_alpha_shape_vertex, vertex)); - } else { - // alpha shape found - Simplex_tree_vertex vertex = the_map_iterator->second; -#ifdef DEBUG_TRACES - std::cout << "vertex [" << the_alpha_shape_vertex->point() << "] found in " << vertex << std::endl; -#endif // DEBUG_TRACES - the_simplex_tree.push_back(vertex); - } - } - // Construction of the simplex_tree -#ifdef DEBUG_TRACES - std::cout << "filtration = " << *the_alpha_value_iterator << std::endl; -#endif // DEBUG_TRACES - simplex_tree.insert_simplex(the_simplex_tree, std::sqrt(*the_alpha_value_iterator)); - if (the_alpha_value_iterator != the_alpha_values.end()) - ++the_alpha_value_iterator; - else - std::cerr << "This shall not happen" << std::endl; - } -#ifdef DEBUG_TRACES - std::cout << "vertices \t\t" << count_vertices << std::endl; - std::cout << "edges \t\t" << count_edges << std::endl; - std::cout << "facets \t\t" << count_facets << std::endl; - std::cout << "cells \t\t" << count_cells << std::endl; - - - std::cout << "Information of the Simplex Tree:\n"; - std::cout << " Number of vertices = " << simplex_tree.num_vertices() << " "; - std::cout << " Number of simplices = " << simplex_tree.num_simplices() << std::endl << std::endl; -#endif // DEBUG_TRACES - -#ifdef DEBUG_TRACES - std::cout << "Iterator on vertices: \n"; - for (auto vertex : simplex_tree.complex_vertex_range()) { - std::cout << vertex << " "; - } -#endif // DEBUG_TRACES - - std::cout << simplex_tree << std::endl; - -#ifdef DEBUG_TRACES - std::cout << std::endl << std::endl << "Iterator on simplices:\n"; - for (auto simplex : simplex_tree.complex_simplex_range()) { - std::cout << " "; - for (auto vertex : simplex_tree.simplex_vertex_range(simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } -#endif // DEBUG_TRACES -#ifdef DEBUG_TRACES - std::cout << std::endl << std::endl << "Iterator on Simplices in the filtration, with [filtration value]:\n"; - for (auto f_simplex : simplex_tree.filtration_simplex_range()) { - std::cout << " " << "[" << simplex_tree.filtration(f_simplex) << "] "; - for (auto vertex : simplex_tree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } -#endif // DEBUG_TRACES -#ifdef DEBUG_TRACES - std::cout << std::endl << std::endl << "Iterator on Simplices in the filtration, and their boundary simplices:\n"; - for (auto f_simplex : simplex_tree.filtration_simplex_range()) { - std::cout << " " << "[" << simplex_tree.filtration(f_simplex) << "] "; - for (auto vertex : simplex_tree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - - for (auto b_simplex : simplex_tree.boundary_simplex_range(f_simplex)) { - std::cout << " " << "[" << simplex_tree.filtration(b_simplex) << "] "; - for (auto vertex : simplex_tree.simplex_vertex_range(b_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - } -#endif // DEBUG_TRACES - - return 0; -} diff --git a/example/Simplex_tree/graph_expansion_with_blocker.cpp b/example/Simplex_tree/graph_expansion_with_blocker.cpp deleted file mode 100644 index f39de31f..00000000 --- a/example/Simplex_tree/graph_expansion_with_blocker.cpp +++ /dev/null @@ -1,77 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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/Simplex_tree.h> - -#include <iostream> - -using Simplex_tree = Gudhi::Simplex_tree<>; -using Simplex_handle = Simplex_tree::Simplex_handle; - -int main(int argc, char* const argv[]) { - // Construct the Simplex Tree with a 1-skeleton graph example - Simplex_tree stree; - - stree.insert_simplex({0, 1}, 0.); - stree.insert_simplex({0, 2}, 1.); - stree.insert_simplex({0, 3}, 2.); - stree.insert_simplex({1, 2}, 3.); - stree.insert_simplex({1, 3}, 4.); - stree.insert_simplex({2, 3}, 5.); - stree.insert_simplex({2, 4}, 6.); - stree.insert_simplex({3, 6}, 7.); - stree.insert_simplex({4, 5}, 8.); - stree.insert_simplex({4, 6}, 9.); - stree.insert_simplex({5, 6}, 10.); - stree.insert_simplex({6}, 10.); - - stree.expansion_with_blockers(3, [&](Simplex_handle sh) { - bool result = false; - std::cout << "Blocker on ["; - // User can loop on the vertices from the given simplex_handle i.e. - for (auto vertex : stree.simplex_vertex_range(sh)) { - // We block the expansion, if the vertex '6' is in the given list of vertices - if (vertex == 6) result = true; - std::cout << vertex << ", "; - } - std::cout << "] ( " << stree.filtration(sh); - // User can re-assign a new filtration value directly in the blocker (default is the maximal value of boudaries) - stree.assign_filtration(sh, stree.filtration(sh) + 1.); - - std::cout << " + 1. ) = " << result << std::endl; - - return result; - }); - - std::cout << "********************************************************************\n"; - std::cout << "* The complex contains " << stree.num_simplices() << " simplices"; - std::cout << " - dimension " << stree.dimension() << "\n"; - std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " " - << "[" << stree.filtration(f_simplex) << "] "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) std::cout << "(" << vertex << ")"; - std::cout << std::endl; - } - - return 0; -} diff --git a/example/Simplex_tree/mini_simplex_tree.cpp b/example/Simplex_tree/mini_simplex_tree.cpp deleted file mode 100644 index e7c7177f..00000000 --- a/example/Simplex_tree/mini_simplex_tree.cpp +++ /dev/null @@ -1,66 +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): Marc Glisse - * - * Copyright (C) 2015 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/Simplex_tree.h> -#include <iostream> -#include <initializer_list> - -struct MyOptions : Gudhi::Simplex_tree_options_full_featured { - // Not doing persistence, so we don't need those - static const bool store_key = false; - static const bool store_filtration = false; - // I have few vertices - typedef short Vertex_handle; -}; - -using ST = Gudhi::Simplex_tree<MyOptions>; - -// Dictionary should be private, but for now this is the easiest way. -static_assert(sizeof(ST::Dictionary::value_type) < sizeof(Gudhi::Simplex_tree<>::Dictionary::value_type), - "Not storing the filtration and key should save some space"); - -int main() { - ST st; - - /* Complex to build. */ - /* 1 */ - /* o */ - /* /X\ */ - /* o---o---o */ - /* 2 0 3 */ - - auto triangle012 = {0, 1, 2}; - auto edge03 = {0, 3}; - st.insert_simplex_and_subfaces(triangle012); - st.insert_simplex_and_subfaces(edge03); - - auto edge02 = {0, 2}; - ST::Simplex_handle e = st.find(edge02); - // We are not using filtrations so everything has value 0 - assert(st.filtration(e) == 0); - for (ST::Simplex_handle t : st.cofaces_simplex_range(e, 1)) { - // Only coface is 012 - for (ST::Vertex_handle v : st.simplex_vertex_range(t)) // v in { 0, 1, 2 } - std::cout << v; - std::cout << '\n'; - } -} diff --git a/example/Simplex_tree/simple_simplex_tree.cpp b/example/Simplex_tree/simple_simplex_tree.cpp deleted file mode 100644 index d71b5608..00000000 --- a/example/Simplex_tree/simple_simplex_tree.cpp +++ /dev/null @@ -1,268 +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): Vincent Rouvreau - * - * Copyright (C) 2014 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/graph_simplicial_complex.h> -#include <gudhi/Simplex_tree.h> - -#include <iostream> -#include <utility> // for pair -#include <vector> - -using Simplex_tree = Gudhi::Simplex_tree<>; -using Vertex_handle = Simplex_tree::Vertex_handle; -using Filtration_value = Simplex_tree::Filtration_value; -using typeVectorVertex = std::vector<Vertex_handle>; -using typePairSimplexBool = std::pair<Simplex_tree::Simplex_handle, bool>; - -int main(int argc, char* const argv[]) { - const Filtration_value FIRST_FILTRATION_VALUE = 0.1; - const Filtration_value SECOND_FILTRATION_VALUE = 0.2; - const Filtration_value THIRD_FILTRATION_VALUE = 0.3; - const Filtration_value FOURTH_FILTRATION_VALUE = 0.4; - - // TEST OF INSERTION - std::cout << "********************************************************************" << std::endl; - std::cout << "EXAMPLE OF SIMPLE INSERTION" << std::endl; - // Construct the Simplex Tree - Simplex_tree simplexTree; - - /* Simplex to be inserted: */ - /* 1 */ - /* o */ - /* /X\ */ - /* o---o---o */ - /* 2 0 3 */ - - // ++ FIRST - std::cout << " * INSERT 0" << std::endl; - typeVectorVertex firstSimplexVector = {0}; - typePairSimplexBool returnValue = - simplexTree.insert_simplex(firstSimplexVector, Filtration_value(FIRST_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + 0 INSERTED" << std::endl; - } else { - std::cout << " - 0 NOT INSERTED" << std::endl; - } - - // ++ SECOND - std::cout << " * INSERT 1" << std::endl; - typeVectorVertex secondSimplexVector = {1}; - returnValue = simplexTree.insert_simplex(secondSimplexVector, Filtration_value(FIRST_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + 1 INSERTED" << std::endl; - } else { - std::cout << " - 1 NOT INSERTED" << std::endl; - } - - // ++ THIRD - std::cout << " * INSERT (0,1)" << std::endl; - typeVectorVertex thirdSimplexVector = {0, 1}; - returnValue = simplexTree.insert_simplex(thirdSimplexVector, Filtration_value(SECOND_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (0,1) INSERTED" << std::endl; - } else { - std::cout << " - (0,1) NOT INSERTED" << std::endl; - } - - // ++ FOURTH - std::cout << " * INSERT 2" << std::endl; - typeVectorVertex fourthSimplexVector = {2}; - returnValue = simplexTree.insert_simplex(fourthSimplexVector, Filtration_value(FIRST_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + 2 INSERTED" << std::endl; - } else { - std::cout << " - 2 NOT INSERTED" << std::endl; - } - - // ++ FIFTH - std::cout << " * INSERT (2,0)" << std::endl; - typeVectorVertex fifthSimplexVector = {2, 0}; - returnValue = simplexTree.insert_simplex(fifthSimplexVector, Filtration_value(SECOND_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (2,0) INSERTED" << std::endl; - } else { - std::cout << " - (2,0) NOT INSERTED" << std::endl; - } - - // ++ SIXTH - std::cout << " * INSERT (2,1)" << std::endl; - typeVectorVertex sixthSimplexVector = {2, 1}; - returnValue = simplexTree.insert_simplex(sixthSimplexVector, Filtration_value(SECOND_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (2,1) INSERTED" << std::endl; - } else { - std::cout << " - (2,1) NOT INSERTED" << std::endl; - } - - // ++ SEVENTH - std::cout << " * INSERT (2,1,0)" << std::endl; - typeVectorVertex seventhSimplexVector = {2, 1, 0}; - returnValue = simplexTree.insert_simplex(seventhSimplexVector, Filtration_value(THIRD_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (2,1,0) INSERTED" << std::endl; - } else { - std::cout << " - (2,1,0) NOT INSERTED" << std::endl; - } - - // ++ EIGHTH - std::cout << " * INSERT 3" << std::endl; - typeVectorVertex eighthSimplexVector = {3}; - returnValue = simplexTree.insert_simplex(eighthSimplexVector, Filtration_value(FIRST_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + 3 INSERTED" << std::endl; - } else { - std::cout << " - 3 NOT INSERTED" << std::endl; - } - - // ++ NINETH - std::cout << " * INSERT (3,0)" << std::endl; - typeVectorVertex ninethSimplexVector = {3, 0}; - returnValue = simplexTree.insert_simplex(ninethSimplexVector, Filtration_value(SECOND_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (3,0) INSERTED" << std::endl; - } else { - std::cout << " - (3,0) NOT INSERTED" << std::endl; - } - - // ++ TENTH - std::cout << " * INSERT 0 (already inserted)" << std::endl; - typeVectorVertex tenthSimplexVector = {0}; - // With a different filtration value - returnValue = simplexTree.insert_simplex(tenthSimplexVector, Filtration_value(FOURTH_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + 0 INSERTED" << std::endl; - } else { - std::cout << " - 0 NOT INSERTED" << std::endl; - } - - // ++ ELEVENTH - std::cout << " * INSERT (2,1,0) (already inserted)" << std::endl; - typeVectorVertex eleventhSimplexVector = {2, 1, 0}; - returnValue = simplexTree.insert_simplex(eleventhSimplexVector, Filtration_value(FOURTH_FILTRATION_VALUE)); - - if (returnValue.second == true) { - std::cout << " + (2,1,0) INSERTED" << std::endl; - } else { - std::cout << " - (2,1,0) NOT INSERTED" << std::endl; - } - - // ++ GENERAL VARIABLE SET - - std::cout << "********************************************************************\n"; - // Display the Simplex_tree - Can not be done in the middle of 2 inserts - std::cout << "* The complex contains " << simplexTree.num_simplices() << " simplices\n"; - std::cout << " - dimension " << simplexTree.dimension() << "\n"; - std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; - for (auto f_simplex : simplexTree.filtration_simplex_range()) { - std::cout << " " - << "[" << simplexTree.filtration(f_simplex) << "] "; - for (auto vertex : simplexTree.simplex_vertex_range(f_simplex)) std::cout << "(" << vertex << ")"; - std::cout << std::endl; - } - // [0.1] 0 - // [0.1] 1 - // [0.1] 2 - // [0.1] 3 - // [0.2] 1 0 - // [0.2] 2 0 - // [0.2] 2 1 - // [0.2] 3 0 - // [0.3] 2 1 0 - - // ------------------------------------------------------------------------------------------------------------------ - // Find in the simplex_tree - // ------------------------------------------------------------------------------------------------------------------ - Simplex_tree::Simplex_handle simplexFound = simplexTree.find(secondSimplexVector); - std::cout << "**************IS THE SIMPLEX {1} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - typeVectorVertex unknownSimplexVector = {15}; - simplexFound = simplexTree.find(unknownSimplexVector); - std::cout << "**************IS THE SIMPLEX {15} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - simplexFound = simplexTree.find(fifthSimplexVector); - std::cout << "**************IS THE SIMPLEX {2,0} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - typeVectorVertex otherSimplexVector = {1, 15}; - simplexFound = simplexTree.find(otherSimplexVector); - std::cout << "**************IS THE SIMPLEX {15,1} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - typeVectorVertex invSimplexVector = {1, 2, 0}; - simplexFound = simplexTree.find(invSimplexVector); - std::cout << "**************IS THE SIMPLEX {1,2,0} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - simplexFound = simplexTree.find({0, 1}); - std::cout << "**************IS THE SIMPLEX {0,1} IN THE SIMPLEX TREE ?\n"; - if (simplexFound != simplexTree.null_simplex()) - std::cout << "***+ YES IT IS!\n"; - else - std::cout << "***- NO IT ISN'T\n"; - - std::cout << "**************COFACES OF {0,1} IN CODIMENSION 1 ARE\n"; - for (auto& simplex : simplexTree.cofaces_simplex_range(simplexTree.find({0, 1}), 1)) { - for (auto vertex : simplexTree.simplex_vertex_range(simplex)) std::cout << "(" << vertex << ")"; - std::cout << std::endl; - } - - std::cout << "**************STARS OF {0,1} ARE\n"; - for (auto& simplex : simplexTree.star_simplex_range(simplexTree.find({0, 1}))) { - for (auto vertex : simplexTree.simplex_vertex_range(simplex)) std::cout << "(" << vertex << ")"; - std::cout << std::endl; - } - - std::cout << "**************BOUNDARIES OF {0,1,2} ARE\n"; - for (auto& simplex : simplexTree.boundary_simplex_range(simplexTree.find({0, 1, 2}))) { - for (auto vertex : simplexTree.simplex_vertex_range(simplex)) std::cout << "(" << vertex << ")"; - std::cout << std::endl; - } - - return 0; -} diff --git a/example/Simplex_tree/simplex_tree_from_cliques_of_graph.cpp b/example/Simplex_tree/simplex_tree_from_cliques_of_graph.cpp deleted file mode 100644 index 6d70f3d1..00000000 --- a/example/Simplex_tree/simplex_tree_from_cliques_of_graph.cpp +++ /dev/null @@ -1,121 +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): Clément Maria - * - * Copyright (C) 2014 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/reader_utils.h> -#include <gudhi/Simplex_tree.h> - -#include <iostream> -#include <ctime> -#include <string> -#include <utility> // for std::pair - -using namespace Gudhi; - -typedef int Vertex_handle; -typedef double Filtration_value; -typedef boost::adjacency_list < boost::vecS, boost::vecS, boost::undirectedS, - boost::property < vertex_filtration_t, Filtration_value >, - boost::property < edge_filtration_t, Filtration_value > > Graph_t; - -int main(int argc, char * const argv[]) { - if (argc != 3) { - std::cerr << "Usage: " << argv[0] - << " path_to_file_graph max_dim \n"; - return 0; - } - std::string filegraph = argv[1]; - int max_dim = atoi(argv[2]); - - clock_t start, end; - // Construct the Simplex Tree - Simplex_tree<> st; - - start = clock(); - auto g = read_graph<Graph_t, Filtration_value, Vertex_handle>(filegraph); - // insert the graph in the simplex tree as 1-skeleton - st.insert_graph(g); - end = clock(); - std::cout << "Insert the 1-skeleton in the simplex tree in " - << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; - - start = clock(); - // expand the 1-skeleton until dimension max_dim - st.expansion(max_dim); - end = clock(); - std::cout << "max_dim = " << max_dim << "\n"; - std::cout << "Expand the simplex tree in " - << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n"; - - std::cout << "Information of the Simplex Tree: " << std::endl; - std::cout << " Number of vertices = " << st.num_vertices() << " "; - std::cout << " Number of simplices = " << st.num_simplices() << std::endl; - std::cout << std::endl << std::endl; - - std::cout << "Iterator on vertices: "; - for (auto vertex : st.complex_vertex_range()) { - std::cout << vertex << " "; - } - - std::cout << std::endl; - - std::cout << std::endl << std::endl; - - std::cout << "Iterator on simplices: " << std::endl; - for (auto simplex : st.complex_simplex_range()) { - std::cout << " "; - for (auto vertex : st.simplex_vertex_range(simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - - std::cout << std::endl << std::endl; - - std::cout << "Iterator on Simplices in the filtration, with [filtration value]:" << std::endl; - for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " << "[" << st.filtration(f_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - - std::cout << std::endl << std::endl; - - std::cout << "Iterator on Simplices in the filtration, and their boundary simplices:" << std::endl; - for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " << "[" << st.filtration(f_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - - for (auto b_simplex : st.boundary_simplex_range(f_simplex)) { - std::cout << " " << "[" << st.filtration(b_simplex) << "] "; - for (auto vertex : st.simplex_vertex_range(b_simplex)) { - std::cout << vertex << " "; - } - std::cout << std::endl; - } - } - return 0; -} diff --git a/example/Skeleton_blocker/CMakeLists.txt b/example/Skeleton_blocker/CMakeLists.txt deleted file mode 100644 index 0e5d2f11..00000000 --- a/example/Skeleton_blocker/CMakeLists.txt +++ /dev/null @@ -1,13 +0,0 @@ -project(Skeleton_blocker_examples) - -add_executable(Skeleton_blocker_example_from_simplices Skeleton_blocker_from_simplices.cpp) -add_executable(Skeleton_blocker_example_iteration Skeleton_blocker_iteration.cpp) -add_executable(Skeleton_blocker_example_link Skeleton_blocker_link.cpp) - -add_test(NAME Skeleton_blocker_example_from_simplices COMMAND $<TARGET_FILE:Skeleton_blocker_example_from_simplices>) -add_test(NAME Skeleton_blocker_example_iteration COMMAND $<TARGET_FILE:Skeleton_blocker_example_iteration>) -add_test(NAME Skeleton_blocker_example_link COMMAND $<TARGET_FILE:Skeleton_blocker_example_link>) - -install(TARGETS Skeleton_blocker_example_from_simplices DESTINATION bin) -install(TARGETS Skeleton_blocker_example_iteration DESTINATION bin) -install(TARGETS Skeleton_blocker_example_link DESTINATION bin) diff --git a/example/Skeleton_blocker/Skeleton_blocker_from_simplices.cpp b/example/Skeleton_blocker/Skeleton_blocker_from_simplices.cpp deleted file mode 100644 index f288e39c..00000000 --- a/example/Skeleton_blocker/Skeleton_blocker_from_simplices.cpp +++ /dev/null @@ -1,77 +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): David Salinas - * - * Copyright (C) 2014 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/Skeleton_blocker.h> - -#include <stdio.h> -#include <stdlib.h> -#include <string> -#include <fstream> -#include <sstream> -#include <vector> - -typedef Gudhi::skeleton_blocker::Skeleton_blocker_simple_traits Traits; -typedef Gudhi::skeleton_blocker::Skeleton_blocker_complex<Traits> Complex; -typedef Complex::Vertex_handle Vertex_handle; -typedef Complex::Simplex Simplex; - -int main(int argc, char *argv[]) { - std::vector<Simplex> simplices; - - // add 4 triangles of a tetrahedron 0123 - simplices.push_back(Simplex(Vertex_handle(0), Vertex_handle(1), Vertex_handle(2))); - simplices.push_back(Simplex(Vertex_handle(1), Vertex_handle(2), Vertex_handle(3))); - simplices.push_back(Simplex(Vertex_handle(3), Vertex_handle(0), Vertex_handle(2))); - simplices.push_back(Simplex(Vertex_handle(3), Vertex_handle(0), Vertex_handle(1))); - - // get complex from top faces - Complex complex(Gudhi::skeleton_blocker::make_complex_from_top_faces<Complex>(simplices.begin(), simplices.end())); - - - std::cout << "Simplices:" << std::endl; - for (const Simplex & s : complex.complex_simplex_range()) - std::cout << s << " "; - std::cout << std::endl; - - // One blocker as simplex 0123 is not in the complex but all its proper faces are. - std::cout << "Blockers: " << complex.blockers_to_string() << std::endl; - - // now build a complex from its full list of simplices - simplices.clear(); - simplices.push_back(Simplex(Vertex_handle(0))); - simplices.push_back(Simplex(Vertex_handle(1))); - simplices.push_back(Simplex(Vertex_handle(2))); - simplices.push_back(Simplex(Vertex_handle(0), Vertex_handle(1))); - simplices.push_back(Simplex(Vertex_handle(1), Vertex_handle(2))); - simplices.push_back(Simplex(Vertex_handle(2), Vertex_handle(0))); - complex = Complex(simplices.begin(), simplices.end()); - - std::cout << "Simplices:" << std::endl; - for (const Simplex & s : complex.complex_simplex_range()) - std::cout << s << " "; - std::cout << std::endl; - - // One blocker as simplex 012 is not in the complex but all its proper faces are. - std::cout << "Blockers: " << complex.blockers_to_string() << std::endl; - - return EXIT_SUCCESS; -} diff --git a/example/Skeleton_blocker/Skeleton_blocker_iteration.cpp b/example/Skeleton_blocker/Skeleton_blocker_iteration.cpp deleted file mode 100644 index 4d008450..00000000 --- a/example/Skeleton_blocker/Skeleton_blocker_iteration.cpp +++ /dev/null @@ -1,85 +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): David Salinas - * - * Copyright (C) 2014 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/Skeleton_blocker.h> -#include <gudhi/Clock.h> - -#include <stdio.h> -#include <stdlib.h> -#include <string> -#include <fstream> -#include <sstream> - -typedef Gudhi::skeleton_blocker::Skeleton_blocker_simple_traits Traits; -typedef Gudhi::skeleton_blocker::Skeleton_blocker_complex<Traits> Complex; -typedef Complex::Vertex_handle Vertex_handle; -typedef Complex::Simplex Simplex; - -Complex build_complete_complex(int n) { - // build a full complex with n vertices and 2^n-1 simplices - Complex complex; - for (int i = 0; i < n; i++) - complex.add_vertex(); - for (int i = 0; i < n; i++) - for (int j = 0; j < i; j++) - complex.add_edge_without_blockers(Vertex_handle(i), Vertex_handle(j)); - return complex; -} - -int main(int argc, char *argv[]) { - Gudhi::Clock skbl_chrono("Time to build the complete complex, enumerate simplices and Euler Characteristic"); - const int n = 15; - - // build a full complex with n vertices and 2^n-1 simplices - Complex complex(build_complete_complex(n)); - - // this is just to illustrate iterators, to count number of vertices - // or edges, complex.num_vertices() and complex.num_edges() are - // more appropriated! - unsigned num_vertices = 0; - for (auto v : complex.vertex_range()) { - std::cout << "Vertex " << v << std::endl; - ++num_vertices; - } - - // such loop can also be done directly with distance as iterators are STL compliant - auto edges = complex.edge_range(); - unsigned num_edges = std::distance(edges.begin(), edges.end()); - - unsigned euler = 0; - unsigned num_simplices = 0; - // we use a reference to a simplex instead of a copy - // value here because a simplex is a set of integers - // and copying it cost time - for (const Simplex & s : complex.complex_simplex_range()) { - ++num_simplices; - if (s.dimension() % 2 == 0) - euler += 1; - else - euler -= 1; - } - std::cout << "Saw " << num_vertices << " vertices, " << num_edges << " edges and " << num_simplices << " simplices" - << std::endl; - std::cout << "The Euler Characteristic is " << euler << std::endl; - std::cout << skbl_chrono; - return EXIT_SUCCESS; -} diff --git a/example/Skeleton_blocker/Skeleton_blocker_link.cpp b/example/Skeleton_blocker/Skeleton_blocker_link.cpp deleted file mode 100644 index 2ec72128..00000000 --- a/example/Skeleton_blocker/Skeleton_blocker_link.cpp +++ /dev/null @@ -1,69 +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): David Salinas - * - * Copyright (C) 2014 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/Skeleton_blocker.h> - -#include <stdio.h> -#include <stdlib.h> -#include <string> -#include <fstream> -#include <sstream> - -typedef Gudhi::skeleton_blocker::Skeleton_blocker_simple_traits Traits; -typedef Gudhi::skeleton_blocker::Skeleton_blocker_complex<Traits> Complex; -typedef Complex::Vertex_handle Vertex_handle; -typedef Complex::Root_vertex_handle Root_vertex_handle; -typedef Complex::Simplex Simplex; - -int main(int argc, char *argv[]) { - // build a full complex with 4 vertices and 2^4-1 simplices - - // Create a complex with four vertices (0,1,2,3) - Complex complex; - - // Add a tetrahedron to this complex - Simplex tetrahedron(Vertex_handle(0), Vertex_handle(1), Vertex_handle(2), Vertex_handle(3)); - complex.add_simplex(tetrahedron); - - std::cout << "complex:" << complex.to_string() << std::endl; - - // build the link of vertex 1, eg a triangle {0,2,3} - auto link = complex.link(Vertex_handle(1)); - std::cout << "link:" << link.to_string() << std::endl; - - // Internally link is a subcomplex of 'complex' and its vertices are stored in a vector. - // They can be accessed via Vertex_handle(x) where x is an index of the vector. - // In that example, link has three vertices and thus it contains only - // Vertex_handle(0),Vertex_handle(1) and Vertex_handle(2) are). - for (int i = 0; i < 5; ++i) - std::cout << "link.contains_vertex(Vertex_handle(" << i << ")):" << link.contains_vertex(Vertex_handle(i)) << - std::endl; - std::cout << std::endl; - - // To access to the initial vertices eg (0,1,2,3,4), Root_vertex_handle must be used. - // For instance, to test if the link contains the vertex that was labeled i: - for (int i = 0; i < 5; ++i) - std::cout << "link.contains_vertex(Root_vertex_handle(" << i << ")):" << - link.contains_vertex(Root_vertex_handle(i)) << std::endl; - - return EXIT_SUCCESS; -} diff --git a/example/Spatial_searching/CMakeLists.txt b/example/Spatial_searching/CMakeLists.txt deleted file mode 100644 index 0f799987..00000000 --- a/example/Spatial_searching/CMakeLists.txt +++ /dev/null @@ -1,9 +0,0 @@ -project(Spatial_searching_examples) - -if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) - add_executable( Spatial_searching_example_spatial_searching example_spatial_searching.cpp ) - target_link_libraries(Spatial_searching_example_spatial_searching ${CGAL_LIBRARY}) - add_test(NAME Spatial_searching_example_spatial_searching - COMMAND $<TARGET_FILE:Spatial_searching_example_spatial_searching>) - install(TARGETS Spatial_searching_example_spatial_searching DESTINATION bin) -endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) diff --git a/example/Spatial_searching/example_spatial_searching.cpp b/example/Spatial_searching/example_spatial_searching.cpp deleted file mode 100644 index 034ad24a..00000000 --- a/example/Spatial_searching/example_spatial_searching.cpp +++ /dev/null @@ -1,60 +0,0 @@ -#include <gudhi/Kd_tree_search.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <vector> - -namespace gss = Gudhi::spatial_searching; - -int main(void) { - typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; - typedef typename K::Point_d Point; - typedef std::vector<Point> Points; - - typedef gss::Kd_tree_search<K, Points> Points_ds; - - CGAL::Random rd; - - Points points; - for (int i = 0; i < 500; ++i) - points.push_back(Point(rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1), rd.get_double(-1., 1))); - - Points_ds points_ds(points); - - // 10-nearest neighbor query - std::cout << "10 nearest neighbors from points[20]:\n"; - auto knn_range = points_ds.k_nearest_neighbors(points[20], 10, true); - for (auto const& nghb : knn_range) - std::cout << nghb.first << " (sq. dist. = " << nghb.second << ")\n"; - - // Incremental nearest neighbor query - std::cout << "Incremental nearest neighbors:\n"; - auto inn_range = points_ds.incremental_nearest_neighbors(points[45]); - // Get the neighbors in distance order until we hit the first point - for (auto ins_iterator = inn_range.begin(); ins_iterator->first != 0; ++ins_iterator) - std::cout << ins_iterator->first << " (sq. dist. = " << ins_iterator->second << ")\n"; - - // 10-furthest neighbor query - std::cout << "10 furthest neighbors from points[20]:\n"; - auto kfn_range = points_ds.k_furthest_neighbors(points[20], 10, true); - for (auto const& nghb : kfn_range) - std::cout << nghb.first << " (sq. dist. = " << nghb.second << ")\n"; - - // Incremental furthest neighbor query - std::cout << "Incremental furthest neighbors:\n"; - auto ifn_range = points_ds.incremental_furthest_neighbors(points[45]); - // Get the neighbors in distance reverse order until we hit the first point - for (auto ifs_iterator = ifn_range.begin(); ifs_iterator->first != 0; ++ifs_iterator) - std::cout << ifs_iterator->first << " (sq. dist. = " << ifs_iterator->second << ")\n"; - - // All-near-neighbors search - std::cout << "All-near-neighbors search:\n"; - std::vector<std::size_t> rs_result; - points_ds.all_near_neighbors(points[45], 0.5, std::back_inserter(rs_result)); - K k; - for (auto const& p_idx : rs_result) - std::cout << p_idx << " (sq. dist. = " << k.squared_distance_d_object()(points[p_idx], points[45]) << ")\n"; - - return 0; -} diff --git a/example/Subsampling/CMakeLists.txt b/example/Subsampling/CMakeLists.txt deleted file mode 100644 index f26d107f..00000000 --- a/example/Subsampling/CMakeLists.txt +++ /dev/null @@ -1,22 +0,0 @@ -project(Subsampling_examples) - -if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) - add_executable(Subsampling_example_pick_n_random_points example_pick_n_random_points.cpp) - add_executable(Subsampling_example_choose_n_farthest_points example_choose_n_farthest_points.cpp) - add_executable(Subsampling_example_custom_kernel example_custom_kernel.cpp) - add_executable(Subsampling_example_sparsify_point_set example_sparsify_point_set.cpp) - target_link_libraries(Subsampling_example_sparsify_point_set ${CGAL_LIBRARY}) - - add_test(NAME Subsampling_example_pick_n_random_points - COMMAND $<TARGET_FILE:Subsampling_example_pick_n_random_points>) - add_test(NAME Subsampling_example_choose_n_farthest_points - COMMAND $<TARGET_FILE:Subsampling_example_choose_n_farthest_points>) - add_test(NAME Subsampling_example_sparsify_point_set - COMMAND $<TARGET_FILE:Subsampling_example_sparsify_point_set>) - - install(TARGETS Subsampling_example_pick_n_random_points DESTINATION bin) - install(TARGETS Subsampling_example_choose_n_farthest_points DESTINATION bin) - install(TARGETS Subsampling_example_custom_kernel DESTINATION bin) - install(TARGETS Subsampling_example_sparsify_point_set DESTINATION bin) - -endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) diff --git a/example/Subsampling/example_choose_n_farthest_points.cpp b/example/Subsampling/example_choose_n_farthest_points.cpp deleted file mode 100644 index ebf631fc..00000000 --- a/example/Subsampling/example_choose_n_farthest_points.cpp +++ /dev/null @@ -1,29 +0,0 @@ -#include <gudhi/choose_n_farthest_points.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <vector> -#include <iterator> - -int main(void) { - typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; - typedef typename K::Point_d Point_d; - - CGAL::Random rd; - - std::vector<Point_d> points; - for (int i = 0; i < 500; ++i) - points.push_back(Point_d(rd.get_double(-1., 1), rd.get_double(-1., 1), - rd.get_double(-1., 1), rd.get_double(-1., 1))); - - K k; - std::vector<Point_d> results; - Gudhi::subsampling::choose_n_farthest_points(k, points, 100, - Gudhi::subsampling::random_starting_point, - std::back_inserter(results)); - std::cout << "Before sparsification: " << points.size() << " points.\n"; - std::cout << "After sparsification: " << results.size() << " points.\n"; - - return 0; -} diff --git a/example/Subsampling/example_custom_kernel.cpp b/example/Subsampling/example_custom_kernel.cpp deleted file mode 100644 index 2d42bdde..00000000 --- a/example/Subsampling/example_custom_kernel.cpp +++ /dev/null @@ -1,65 +0,0 @@ -#include <gudhi/choose_n_farthest_points.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <vector> -#include <iterator> - - -/* The class Kernel contains a distance function defined on the set of points {0, 1, 2, 3} - * and computes a distance according to the matrix: - * 0 1 2 4 - * 1 0 4 2 - * 2 4 0 1 - * 4 2 1 0 - */ -class Kernel { - public: - typedef double FT; - typedef unsigned Point_d; - - // Class Squared_distance_d - class Squared_distance_d { - private: - std::vector<std::vector<FT>> matrix_; - - public: - Squared_distance_d() { - matrix_.push_back(std::vector<FT>({0, 1, 2, 4})); - matrix_.push_back(std::vector<FT>({1, 0, 4, 2})); - matrix_.push_back(std::vector<FT>({2, 4, 0, 1})); - matrix_.push_back(std::vector<FT>({4, 2, 1, 0})); - } - - FT operator()(Point_d p1, Point_d p2) { - return matrix_[p1][p2]; - } - }; - - // Constructor - Kernel() {} - - // Object of type Squared_distance_d - Squared_distance_d squared_distance_d_object() const { - return Squared_distance_d(); - } -}; - -int main(void) { - typedef Kernel K; - typedef typename K::Point_d Point_d; - - K k; - std::vector<Point_d> points = {0, 1, 2, 3}; - std::vector<Point_d> results; - - Gudhi::subsampling::choose_n_farthest_points(k, points, 2, - Gudhi::subsampling::random_starting_point, - std::back_inserter(results)); - std::cout << "Before sparsification: " << points.size() << " points.\n"; - std::cout << "After sparsification: " << results.size() << " points.\n"; - std::cout << "Result table: {" << results[0] << "," << results[1] << "}\n"; - - return 0; -} diff --git a/example/Subsampling/example_pick_n_random_points.cpp b/example/Subsampling/example_pick_n_random_points.cpp deleted file mode 100644 index 1e38e405..00000000 --- a/example/Subsampling/example_pick_n_random_points.cpp +++ /dev/null @@ -1,27 +0,0 @@ -#include <gudhi/pick_n_random_points.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <vector> -#include <iterator> - -int main(void) { - typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; - typedef typename K::Point_d Point_d; - - CGAL::Random rd; - - std::vector<Point_d> points; - for (int i = 0; i < 500; ++i) - points.push_back(Point_d(rd.get_double(-1., 1), rd.get_double(-1., 1), - rd.get_double(-1., 1), rd.get_double(-1., 1))); - - K k; - std::vector<Point_d> results; - Gudhi::subsampling::pick_n_random_points(points, 100, std::back_inserter(results)); - std::cout << "Before sparsification: " << points.size() << " points.\n"; - std::cout << "After sparsification: " << results.size() << " points.\n"; - - return 0; -} diff --git a/example/Subsampling/example_sparsify_point_set.cpp b/example/Subsampling/example_sparsify_point_set.cpp deleted file mode 100644 index b35a18d9..00000000 --- a/example/Subsampling/example_sparsify_point_set.cpp +++ /dev/null @@ -1,27 +0,0 @@ -#include <gudhi/sparsify_point_set.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <vector> -#include <iterator> - -int main(void) { - typedef CGAL::Epick_d<CGAL::Dimension_tag<4> > K; - typedef typename K::Point_d Point_d; - - CGAL::Random rd; - - std::vector<Point_d> points; - for (int i = 0; i < 500; ++i) - points.push_back(Point_d(rd.get_double(-1., 1), rd.get_double(-1., 1), - rd.get_double(-1., 1), rd.get_double(-1., 1))); - - K k; - std::vector<Point_d> results; - Gudhi::subsampling::sparsify_point_set(k, points, 0.4, std::back_inserter(results)); - std::cout << "Before sparsification: " << points.size() << " points.\n"; - std::cout << "After sparsification: " << results.size() << " points.\n"; - - return 0; -} diff --git a/example/Tangential_complex/CMakeLists.txt b/example/Tangential_complex/CMakeLists.txt deleted file mode 100644 index af0dac51..00000000 --- a/example/Tangential_complex/CMakeLists.txt +++ /dev/null @@ -1,20 +0,0 @@ -project(Tangential_complex_examples) - -if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) - add_executable( Tangential_complex_example_basic example_basic.cpp ) - target_link_libraries(Tangential_complex_example_basic ${CGAL_LIBRARY}) - add_executable( Tangential_complex_example_with_perturb example_with_perturb.cpp ) - target_link_libraries(Tangential_complex_example_with_perturb ${CGAL_LIBRARY}) - if (TBB_FOUND) - target_link_libraries(Tangential_complex_example_basic ${TBB_LIBRARIES}) - target_link_libraries(Tangential_complex_example_with_perturb ${TBB_LIBRARIES}) - endif(TBB_FOUND) - - add_test(NAME Tangential_complex_example_basic - COMMAND $<TARGET_FILE:Tangential_complex_example_basic>) - add_test(NAME Tangential_complex_example_with_perturb - COMMAND $<TARGET_FILE:Tangential_complex_example_with_perturb>) - - install(TARGETS Tangential_complex_example_basic DESTINATION bin) - install(TARGETS Tangential_complex_example_with_perturb DESTINATION bin) -endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) diff --git a/example/Tangential_complex/example_basic.cpp b/example/Tangential_complex/example_basic.cpp deleted file mode 100644 index 4f2b859e..00000000 --- a/example/Tangential_complex/example_basic.cpp +++ /dev/null @@ -1,46 +0,0 @@ -#include <gudhi/Tangential_complex.h> -#include <gudhi/sparsify_point_set.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <array> -#include <vector> - -namespace tc = Gudhi::tangential_complex; - -typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> Kernel; -typedef Kernel::FT FT; -typedef Kernel::Point_d Point; -typedef Kernel::Vector_d Vector; -typedef tc::Tangential_complex< -Kernel, CGAL::Dynamic_dimension_tag, -CGAL::Parallel_tag> TC; - -int main(void) { - const int INTRINSIC_DIM = 2; - const int AMBIENT_DIM = 3; - const int NUM_POINTS = 1000; - - Kernel k; - - // Generate points on a 2-sphere - CGAL::Random_points_on_sphere_d<Point> generator(AMBIENT_DIM, 3.); - std::vector<Point> points; - points.reserve(NUM_POINTS); - for (int i = 0; i < NUM_POINTS; ++i) - points.push_back(*generator++); - - // Compute the TC - TC tc(points, INTRINSIC_DIM, k); - tc.compute_tangential_complex(); - - // Export the TC into a Simplex_tree - Gudhi::Simplex_tree<> stree; - tc.create_complex(stree); - - // Display stats about inconsistencies - tc.number_of_inconsistent_simplices(true); // verbose - - return 0; -} diff --git a/example/Tangential_complex/example_with_perturb.cpp b/example/Tangential_complex/example_with_perturb.cpp deleted file mode 100644 index d0d877ea..00000000 --- a/example/Tangential_complex/example_with_perturb.cpp +++ /dev/null @@ -1,53 +0,0 @@ -#include <gudhi/Tangential_complex.h> -#include <gudhi/sparsify_point_set.h> - -#include <CGAL/Epick_d.h> -#include <CGAL/Random.h> - -#include <array> -#include <vector> - -namespace subsampl = Gudhi::subsampling; -namespace tc = Gudhi::tangential_complex; - -typedef CGAL::Epick_d<CGAL::Dimension_tag < 3 >> Kernel; -typedef Kernel::FT FT; -typedef Kernel::Point_d Point; -typedef Kernel::Vector_d Vector; -typedef tc::Tangential_complex< -Kernel, CGAL::Dimension_tag<2>, -CGAL::Parallel_tag> TC; - -int main(void) { - const int INTRINSIC_DIM = 2; - const int AMBIENT_DIM = 3; - const int NUM_POINTS = 50; - - Kernel k; - - // Generate points on a 2-sphere - CGAL::Random_points_on_sphere_d<Point> generator(AMBIENT_DIM, 3.); - std::vector<Point> points; - points.reserve(NUM_POINTS); - for (int i = 0; i < NUM_POINTS; ++i) - points.push_back(*generator++); - - // Sparsify the point set - std::vector<Point> sparsified_points; - subsampl::sparsify_point_set(k, points, 0.1 * 0.1, - std::back_inserter(sparsified_points)); - sparsified_points.swap(points); - - // Compute the TC - TC tc(points, INTRINSIC_DIM, k); - tc.compute_tangential_complex(); - - // Try to fix inconsistencies. Give it 10 seconds to succeed - tc.fix_inconsistencies_using_perturbation(0.05, 10); - - // Export the TC into a Simplex_tree - Gudhi::Simplex_tree<> stree; - tc.create_complex(stree); - - return 0; -} diff --git a/example/Witness_complex/CMakeLists.txt b/example/Witness_complex/CMakeLists.txt deleted file mode 100644 index 3d838c0d..00000000 --- a/example/Witness_complex/CMakeLists.txt +++ /dev/null @@ -1,34 +0,0 @@ -project(Witness_complex_examples) - -add_executable ( Witness_complex_example_nearest_landmark_table example_nearest_landmark_table.cpp ) -if (TBB_FOUND) - target_link_libraries(Witness_complex_example_nearest_landmark_table ${TBB_LIBRARIES}) -endif() -add_test(NAME Witness_complex_example_nearest_landmark_table - COMMAND $<TARGET_FILE:Witness_complex_example_nearest_landmark_table>) - -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_sphere example_witness_complex_sphere.cpp ) - - 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") - - install(TARGETS Witness_complex_example_off DESTINATION bin) - install(TARGETS Witness_complex_example_sphere 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_nearest_landmark_table.cpp b/example/Witness_complex/example_nearest_landmark_table.cpp deleted file mode 100644 index acaf7c54..00000000 --- a/example/Witness_complex/example_nearest_landmark_table.cpp +++ /dev/null @@ -1,47 +0,0 @@ -#define BOOST_PARAMETER_MAX_ARITY 12 - -#include <gudhi/Simplex_tree.h> -#include <gudhi/Witness_complex.h> -#include <gudhi/Persistent_cohomology.h> - -#include <iostream> -#include <fstream> -#include <utility> -#include <string> -#include <vector> - -int main(int argc, char * const argv[]) { - using Nearest_landmark_range = std::vector<std::pair<std::size_t, double>>; - using Nearest_landmark_table = std::vector<Nearest_landmark_range>; - using Witness_complex = Gudhi::witness_complex::Witness_complex<Nearest_landmark_table>; - using Simplex_tree = Gudhi::Simplex_tree<>; - using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; - using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>; - - Simplex_tree simplex_tree; - Nearest_landmark_table nlt; - - // Example contains 5 witnesses and 5 landmarks - Nearest_landmark_range w0 = {std::make_pair(0, 0), std::make_pair(1, 1), std::make_pair(2, 2), - std::make_pair(3, 3), std::make_pair(4, 4)}; nlt.push_back(w0); - Nearest_landmark_range w1 = {std::make_pair(1, 0), std::make_pair(2, 1), std::make_pair(3, 2), - std::make_pair(4, 3), std::make_pair(0, 4)}; nlt.push_back(w1); - Nearest_landmark_range w2 = {std::make_pair(2, 0), std::make_pair(3, 1), std::make_pair(4, 2), - std::make_pair(0, 3), std::make_pair(1, 4)}; nlt.push_back(w2); - Nearest_landmark_range w3 = {std::make_pair(3, 0), std::make_pair(4, 1), std::make_pair(0, 2), - std::make_pair(1, 3), std::make_pair(2, 4)}; nlt.push_back(w3); - Nearest_landmark_range w4 = {std::make_pair(4, 0), std::make_pair(0, 1), std::make_pair(1, 2), - std::make_pair(2, 3), std::make_pair(3, 4)}; nlt.push_back(w4); - - Witness_complex witness_complex(nlt); - witness_complex.create_complex(simplex_tree, 4.1); - - std::cout << "Number of simplices: " << simplex_tree.num_simplices() << std::endl; - - Persistent_cohomology pcoh(simplex_tree); - // initializes the coefficient field for homology - pcoh.init_coefficients(11); - - pcoh.compute_persistent_cohomology(-0.1); - pcoh.output_diagram(); -} diff --git a/example/Witness_complex/example_strong_witness_complex_off.cpp b/example/Witness_complex/example_strong_witness_complex_off.cpp deleted file mode 100644 index 19f73836..00000000 --- a/example/Witness_complex/example_strong_witness_complex_off.cpp +++ /dev/null @@ -1,57 +0,0 @@ -#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> - -#include <iostream> -#include <fstream> -#include <ctime> -#include <string> -#include <vector> - -using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; -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[]) { - if (argc != 5) { - std::cerr << "Usage: " << argv[0] << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n"; - return 0; - } - - std::string file_name = argv[1]; - int nbL = atoi(argv[2]), lim_dim = atoi(argv[4]); - double alpha2 = atof(argv[3]); - clock_t start, end; - Gudhi::Simplex_tree<> simplex_tree; - - // Read the point file - 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); // ----- >> - } - 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 (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.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 << "Number of simplices is: " << simplex_tree.num_simplices() << "\n"; -} diff --git a/example/Witness_complex/example_witness_complex_off.cpp b/example/Witness_complex/example_witness_complex_off.cpp deleted file mode 100644 index be11c955..00000000 --- a/example/Witness_complex/example_witness_complex_off.cpp +++ /dev/null @@ -1,62 +0,0 @@ -#include <sys/types.h> -#include <sys/stat.h> - -#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> - -#include <iostream> -#include <fstream> -#include <ctime> -#include <string> -#include <vector> - -using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; -using Point_d = K::Point_d; -using Witness_complex = Gudhi::witness_complex::Euclidean_witness_complex<K>; -using Point_vector = std::vector< Point_d >; - -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"; - return 0; - } - - std::string file_name = argv[1]; - int nbL = atoi(argv[2]), lim_dim = atoi(argv[4]); - double alpha2 = atof(argv[3]); - clock_t start, end; - Gudhi::Simplex_tree<> simplex_tree; - - // Read the point file - Point_vector point_vector, 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); // ----- >> - } - 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 (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.create_complex(simplex_tree, alpha2, lim_dim); - end = clock(); - std::cout << "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_witness_complex_sphere.cpp b/example/Witness_complex/example_witness_complex_sphere.cpp deleted file mode 100644 index 9e3c972d..00000000 --- a/example/Witness_complex/example_witness_complex_sphere.cpp +++ /dev/null @@ -1,70 +0,0 @@ -#define BOOST_PARAMETER_MAX_ARITY 12 - -#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> - -#include <iostream> -#include <fstream> -#include <ctime> -#include <utility> -#include <string> -#include <vector> - -#include "generators.h" - -/** 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) { - std::ofstream ofs(filename, std::ofstream::out); - for (auto entry : data) ofs << entry.first << ", " << entry.second << "\n"; - ofs.close(); -} - -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"; - return 0; - } - - int number_of_landmarks = atoi(argv[1]); - - std::vector<std::pair<int, double> > l_time; - - // Generate points - for (int nbP = 500; nbP < 10000; nbP += 500) { - clock_t start, end; - // Construct the Simplex Tree - Gudhi::Simplex_tree<> simplex_tree; - Point_Vector point_vector, landmarks; - generate_points_sphere(point_vector, nbP, 4); - std::cout << "Successfully generated " << point_vector.size() << " points.\n"; - std::cout << "Ambient dimension is " << point_vector[0].size() << ".\n"; - - // Choose landmarks - start = clock(); - // 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.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 << "Number of simplices is: " << simplex_tree.num_simplices() << "\n"; - l_time.push_back(std::make_pair(nbP, time)); - } - write_data(l_time, "w_time.dat"); -} diff --git a/example/Witness_complex/generators.h b/example/Witness_complex/generators.h deleted file mode 100644 index 4b755daa..00000000 --- a/example/Witness_complex/generators.h +++ /dev/null @@ -1,166 +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) 2015 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 GENERATORS_H_ -#define GENERATORS_H_ - -#include <CGAL/Epick_d.h> -#include <CGAL/point_generators_d.h> -#include <CGAL/Random.h> - -#include <fstream> -#include <string> -#include <vector> -#include <cmath> - -using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>; -using FT = K::FT; -using Point_d = K::Point_d; -using Point_Vector = std::vector<Point_d>; -using Random_cube_iterator = CGAL::Random_points_in_cube_d<Point_d>; -using Random_point_iterator = CGAL::Random_points_in_ball_d<Point_d>; - -/** - * \brief Rock age method of reading off file - * - */ -inline void -off_reader_cust(std::string file_name, std::vector<Point_d> & points) { - std::ifstream in_file(file_name.c_str(), std::ios::in); - if (!in_file.is_open()) { - std::cerr << "Unable to open file " << file_name << std::endl; - return; - } - std::string line; - double x; - // Line OFF. No need in it - if (!getline(in_file, line)) { - std::cerr << "No line OFF\n"; - return; - } - // Line with 3 numbers. No need - if (!getline(in_file, line)) { - std::cerr << "No line with 3 numbers\n"; - return; - } - // Reading points - while (getline(in_file, line)) { - std::vector< double > point; - std::istringstream iss(line); - while (iss >> x) { - point.push_back(x); - } - points.push_back(Point_d(point)); - } - in_file.close(); -} - -/** - * \brief Customized version of read_points - * which takes into account a possible nbP first line - * - */ -inline void -read_points_cust(std::string file_name, Point_Vector & points) { - std::ifstream in_file(file_name.c_str(), std::ios::in); - if (!in_file.is_open()) { - std::cerr << "Unable to open file " << file_name << std::endl; - return; - } - std::string line; - double x; - while (getline(in_file, line)) { - std::vector< double > point; - std::istringstream iss(line); - while (iss >> x) { - point.push_back(x); - } - Point_d p(point.begin(), point.end()); - if (point.size() != 1) - points.push_back(p); - } - in_file.close(); -} - -/** \brief Generate points on a grid in a cube of side 2 - * having {+-1}^D as vertices and insert them in W. - * The grid has "width" points on each side. - * If torus is true then it is supposed that the cube represents - * a flat torus, hence the opposite borders are associated. - * The points on border in this case are not placed twice. - */ -void generate_points_grid(Point_Vector& W, int width, int D, bool torus) { - int nb_points = 1; - for (int i = 0; i < D; ++i) - nb_points *= width; - for (int i = 0; i < nb_points; ++i) { - std::vector<double> point; - int cell_i = i; - for (int l = 0; l < D; ++l) { - if (torus) - point.push_back(-1 + (2.0 / (width - 1))*(cell_i % width)); - else - point.push_back(-1 + (2.0 / width)*(cell_i % width)); - // attention: the bottom and the right are covered too! - cell_i /= width; - } - W.push_back(point); - } -} - -/** \brief Generate nbP points uniformly in a cube of side 2 - * having {+-1}^dim as its vertices and insert them in W. - */ -void generate_points_random_box(Point_Vector& W, int nbP, int dim) { - Random_cube_iterator rp(dim, 1.0); - for (int i = 0; i < nbP; i++) { - W.push_back(*rp++); - } -} - -/** \brief Generate nbP points uniformly on a (dim-1)-sphere - * and insert them in W. - */ -void generate_points_sphere(Point_Vector& W, int nbP, int dim) { - CGAL::Random_points_on_sphere_d<Point_d> rp(dim, 1); - for (int i = 0; i < nbP; i++) - W.push_back(*rp++); -} - -/** \brief Generate nbP points on a (flat) d-torus embedded in R^{2d} - * - */ -void generate_points_torus(Point_Vector& W, int nbP, int dim) { - CGAL::Random rand; - const double pi = std::acos(-1); - for (int i = 0; i < nbP; i++) { - std::vector<FT> point; - for (int j = 0; j < dim; j++) { - double alpha = rand.uniform_real(static_cast<double>(0), 2*pi); - point.push_back(sin(alpha)); - point.push_back(cos(alpha)); - } - W.push_back(Point_d(point)); - } -} - -#endif // GENERATORS_H_ diff --git a/example/common/CMakeLists.txt b/example/common/CMakeLists.txt deleted file mode 100644 index 04015cdc..00000000 --- a/example/common/CMakeLists.txt +++ /dev/null @@ -1,36 +0,0 @@ -project(Common_examples) - -add_executable ( vector_double_off_reader example_vector_double_points_off_reader.cpp ) -target_link_libraries(vector_double_off_reader ${CGAL_LIBRARY}) -file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) -add_test(NAME Common_example_vector_double_off_reader COMMAND $<TARGET_FILE:vector_double_off_reader> - "alphacomplexdoc.off") - -install(TARGETS vector_double_off_reader DESTINATION bin) - -if (DIFF_PATH) - # Do not forget to copy test results files in current binary dir - file(COPY "vectordoubleoffreader_result.txt" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) - - add_test(Common_example_vector_double_off_reader_diff_files ${DIFF_PATH} - ${CMAKE_CURRENT_BINARY_DIR}/vectordoubleoffreader_result.txt ${CMAKE_CURRENT_BINARY_DIR}/alphacomplexdoc.off.txt) -endif() - -if(CGAL_FOUND) - add_executable ( cgal_3D_off_reader example_CGAL_3D_points_off_reader.cpp ) - target_link_libraries(cgal_3D_off_reader ${CGAL_LIBRARY}) - add_test(NAME Common_example_vector_cgal_3D_off_reader COMMAND $<TARGET_FILE:cgal_3D_off_reader> - "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off") - - install(TARGETS cgal_3D_off_reader DESTINATION bin) - - # need CGAL 4.7 and Eigen3 - if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) - add_executable ( cgal_off_reader example_CGAL_points_off_reader.cpp ) - target_link_libraries(cgal_off_reader ${CGAL_LIBRARY}) - add_test(NAME Common_example_vector_cgal_off_reader COMMAND $<TARGET_FILE:cgal_off_reader> - "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off") - install(TARGETS cgal_off_reader DESTINATION bin) - endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.7.0) - -endif() diff --git a/example/common/cgal3Doffreader_result.txt b/example/common/cgal3Doffreader_result.txt deleted file mode 100644 index f992c8e3..00000000 --- a/example/common/cgal3Doffreader_result.txt +++ /dev/null @@ -1,8 +0,0 @@ -Point[1] = (0.959535, -0.418347, 0.302237) -Point[2] = (2.16795, 1.85348, -0.52312) -Point[3] = (-2.38753, -1.50911, -0.565889) -Point[4] = (-2.70428, -1.25688, 0.188394) -Point[5] = (-1.22932, -1.64337, -0.998632) -... -Point[300] = (-0.56244, 2.6018, -0.749591) - diff --git a/example/common/example_CGAL_3D_points_off_reader.cpp b/example/common/example_CGAL_3D_points_off_reader.cpp deleted file mode 100644 index 4658d8d5..00000000 --- a/example/common/example_CGAL_3D_points_off_reader.cpp +++ /dev/null @@ -1,41 +0,0 @@ -#include <gudhi/Points_3D_off_io.h> - -#include <CGAL/Exact_predicates_inexact_constructions_kernel.h> - -#include <iostream> -#include <string> -#include <vector> - -using Kernel = CGAL::Exact_predicates_inexact_constructions_kernel; -using Point_3 = Kernel::Point_3; - -void usage(char * const progName) { - std::cerr << "Usage: " << progName << " inputFile.off" << std::endl; - exit(-1); -} - -int main(int argc, char **argv) { - if (argc != 2) { - std::cerr << "Error: Number of arguments (" << argc << ") is not correct" << std::endl; - usage(argv[0]); - } - - std::string off_input_file(argv[1]); - // Read the OFF file (input file name given as parameter) and triangulate points - Gudhi::Points_3D_off_reader<Point_3> off_reader(off_input_file); - // Check the read operation was correct - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file " << off_input_file << std::endl; - usage(argv[0]); - } - - // Retrieve the triangulation - std::vector<Point_3> point_cloud = off_reader.get_point_cloud(); - - int n {}; - for (auto point : point_cloud) { - ++n; - std::cout << "Point[" << n << "] = (" << point[0] << ", " << point[1] << ", " << point[2] << ")\n"; - } - return 0; -} diff --git a/example/common/example_CGAL_points_off_reader.cpp b/example/common/example_CGAL_points_off_reader.cpp deleted file mode 100644 index f45683a5..00000000 --- a/example/common/example_CGAL_points_off_reader.cpp +++ /dev/null @@ -1,46 +0,0 @@ -#include <gudhi/Points_off_io.h> - -// For CGAL points type in dimension d -// cf. http://doc.cgal.org/latest/Kernel_d/classCGAL_1_1Point__d.html -#include <CGAL/Epick_d.h> - -#include <iostream> -#include <string> -#include <vector> - -using Kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >; -using Point_d = Kernel::Point_d; - -void usage(char * const progName) { - std::cerr << "Usage: " << progName << " inputFile.off" << std::endl; - exit(-1); -} - -int main(int argc, char **argv) { - if (argc != 2) { - std::cerr << "Error: Number of arguments (" << argc << ") is not correct" << std::endl; - usage(argv[0]); - } - - std::string off_input_file(argv[1]); - // Read the OFF file (input file name given as parameter) and triangulate points - Gudhi::Points_off_reader<Point_d> off_reader(off_input_file); - // Check the read operation was correct - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file " << off_input_file << std::endl; - usage(argv[0]); - } - - // Retrieve the triangulation - std::vector<Point_d> point_cloud = off_reader.get_point_cloud(); - - int n {}; - for (auto point : point_cloud) { - std::cout << "Point[" << n << "] = "; - for (std::size_t i {0}; i < point.size(); i++) - std::cout << point[i] << " "; - std::cout << "\n"; - ++n; - } - return 0; -} diff --git a/example/common/example_vector_double_points_off_reader.cpp b/example/common/example_vector_double_points_off_reader.cpp deleted file mode 100644 index 5093da85..00000000 --- a/example/common/example_vector_double_points_off_reader.cpp +++ /dev/null @@ -1,43 +0,0 @@ -#include <gudhi/Points_off_io.h> - -#include <iostream> -#include <string> -#include <vector> - -using Point_d = std::vector<double>; - -void usage(char * const progName) { - std::cerr << "Usage: " << progName << " inputFile.off" << std::endl; - exit(-1); -} - -int main(int argc, char **argv) { - if (argc != 2) { - std::cerr << "Error: Number of arguments (" << argc << ") is not correct" << std::endl; - usage(argv[0]); - } - - std::string off_input_file(argv[1]); - // Read the OFF file (input file name given as parameter) and triangulate points - Gudhi::Points_off_reader<Point_d> off_reader(off_input_file); - // Check the read operation was correct - if (!off_reader.is_valid()) { - std::cerr << "Unable to read file " << off_input_file << std::endl; - usage(argv[0]); - } - - // Retrieve the triangulation - std::vector<Point_d> point_cloud = off_reader.get_point_cloud(); - - std::ofstream output_file(off_input_file + ".txt"); - int n {0}; - for (auto point : point_cloud) { - output_file << "Point[" << n << "] = "; - for (std::size_t i {0}; i < point.size(); i++) - output_file << point[i] << " "; - output_file << "\n"; - ++n; - } - output_file.close(); - return 0; -} diff --git a/example/common/vectordoubleoffreader_result.txt b/example/common/vectordoubleoffreader_result.txt deleted file mode 100644 index 1deb8dbd..00000000 --- a/example/common/vectordoubleoffreader_result.txt +++ /dev/null @@ -1,7 +0,0 @@ -Point[0] = 1 1 -Point[1] = 7 0 -Point[2] = 4 6 -Point[3] = 9 6 -Point[4] = 0 14 -Point[5] = 2 19 -Point[6] = 9 17 |