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#include <gudhi/FlagComplexSpMatrix.h>
#include <gudhi/Rips_complex.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/Persistent_cohomology.h>
#include <gudhi/Rips_edge_list.h>
#include <gudhi/distance_functions.h>
#include <gudhi/reader_utils.h>
#include <gudhi/Points_off_io.h>
#include <CGAL/Epick_d.h>
#include <boost/program_options.hpp>
// Types definition
using Point = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>::Point_d;
using Vector_of_points = std::vector<Point>;
using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>;
using Filtration_value = double;
using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>;
using Rips_edge_list = Gudhi::rips_edge_list::Rips_edge_list<Filtration_value>;
using Field_Zp = Gudhi::persistent_cohomology::Field_Zp;
using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>;
using Distance_matrix = std::vector<std::vector<Filtration_value>>;
class filt_edge_to_dist_matrix {
public:
template <class Distance_matrix, class Filtered_sorted_edge_list>
filt_edge_to_dist_matrix(Distance_matrix& distance_mat, Filtered_sorted_edge_list& edge_filt,
std::size_t number_of_points) {
double inf = std::numeric_limits<double>::max();
doubleVector distances;
std::pair<std::size_t, std::size_t> e;
for (std::size_t indx = 0; indx < number_of_points; indx++) {
for (std::size_t j = 0; j <= indx; j++) {
if (j == indx)
distances.push_back(0);
else
distances.push_back(inf);
}
distance_mat.push_back(distances);
distances.clear();
}
for (auto edIt = edge_filt.begin(); edIt != edge_filt.end(); edIt++) {
e = std::minmax(std::get<1>(*edIt), std::get<2>(*edIt));
distance_mat.at(std::get<1>(e)).at(std::get<0>(e)) = std::get<0>(*edIt);
}
}
};
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[]) {
typedef size_t Vertex_handle;
typedef std::vector<std::tuple<Filtration_value, Vertex_handle, Vertex_handle>> Filtered_sorted_edge_list;
auto the_begin = std::chrono::high_resolution_clock::now();
std::size_t number_of_points;
std::string off_file_points;
std::string filediag;
double threshold;
int dim_max;
int p;
double min_persistence;
program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence);
std::cout << "The current input values to run the program is: " << std::endl;
std::cout << "min_persistence, threshold, max_complex_dimension, off_file_points, filediag"
<< std::endl;
std::cout << min_persistence << ", " << threshold << ", " << dim_max
<< ", " << off_file_points << ", " << filediag << std::endl;
Map map_empty;
Distance_matrix distances;
Distance_matrix sparse_distances;
Gudhi::Points_off_reader<Point> off_reader(off_file_points);
if (!off_reader.is_valid()) {
std::cerr << "Unable to read file " << off_file_points << "\n";
exit(-1); // ----- >>
}
Vector_of_points point_vector = off_reader.get_point_cloud();
if (point_vector.size() <= 0) {
std::cerr << "Empty point cloud." << std::endl;
exit(-1); // ----- >>
}
int dimension = point_vector[0].dimension();
number_of_points = point_vector.size();
std::cout << "Successfully read " << number_of_points << " point_vector.\n";
std::cout << "Ambient dimension is " << dimension << ".\n";
std::cout << "Point Set Generated." << std::endl;
Filtered_sorted_edge_list edge_t;
std::cout << "Computing the one-skeleton for threshold: " << threshold << std::endl;
Rips_edge_list Rips_edge_list_from_file(point_vector, threshold, Gudhi::Euclidean_distance());
Rips_edge_list_from_file.create_edges(edge_t);
std::cout << "Sorted edge list computed" << std::endl;
std::cout << "Total number of edges before collapse are: " << edge_t.size() << std::endl;
if (edge_t.size() <= 0) {
std::cerr << "Total number of egdes are zero." << std::endl;
exit(-1);
}
// Now we will perform filtered edge collapse to sparsify the edge list edge_t.
std::cout << "Filtered edge collapse begins" << std::endl;
FlagComplexSpMatrix mat_filt_edge_coll(number_of_points, edge_t);
std::cout << "Matrix instansiated" << std::endl;
Filtered_sorted_edge_list collapse_edges;
collapse_edges = mat_filt_edge_coll.filtered_edge_collapse();
filt_edge_to_dist_matrix(sparse_distances, collapse_edges, number_of_points);
std::cout << "Total number of vertices after collapse in the sparse matrix are: " << mat_filt_edge_coll.num_vertices()
<< std::endl;
// Rips_complex rips_complex_before_collapse(distances, threshold);
Rips_complex rips_complex_after_collapse(sparse_distances, threshold);
Simplex_tree stree;
rips_complex_after_collapse.create_complex(stree, dim_max);
std::cout << "The complex contains " << stree.num_simplices() << " simplices after collapse. \n";
std::cout << " and has dimension " << stree.dimension() << " \n";
// Sort the simplices in the order of the filtration
stree.initialize_filtration();
// Compute the persistence diagram of the complex
Persistent_cohomology pcoh(stree);
// initializes the coefficient field for homology
pcoh.init_coefficients(p);
pcoh.compute_persistent_cohomology(min_persistence);
if (filediag.empty()) {
pcoh.output_diagram();
} else {
std::ofstream out(filediag);
pcoh.output_diagram(out);
out.close();
}
auto the_end = std::chrono::high_resolution_clock::now();
std::cout << "Total computation time : " << std::chrono::duration<double, std::milli>(the_end - the_begin).count()
<< " ms\n"
<< std::endl;
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, after edge collapse, 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);
}
}
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