#include <gudhi/Simplex_tree.h>
#include <gudhi/Euclidean_strong_witness_complex.h>
#include <gudhi/Persistent_cohomology.h>
#include <gudhi/Points_off_io.h>
#include <gudhi/pick_n_random_points.h>
#include <gudhi/choose_n_farthest_points.h>
 
#include <boost/program_options.hpp>
 
#include <CGAL/Epick_d.h>
 
#include <string>
#include <vector>
#include <limits>  
 
using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>;
using Point_d = K::Point_d;
 
using Point_vector = std::vector<Point_d>;
 
 
 
void program_options(int argc, char* argv[], int& nbL, std::string& file_name, std::string& filediag,
 
int main(int argc, char* argv[]) {
  std::string file_name;
  std::string filediag;
  int p, nbL, lim_d;
 
  program_options(argc, argv, nbL, file_name, filediag, max_squared_alpha, p, lim_d, min_persistence);
 
  
  Point_vector witnesses, landmarks;
  if (!off_reader.is_valid()) {
    std::cerr << "Witness complex - Unable to read file " << file_name << "\n";
    exit(-1);  
  }
  witnesses = Point_vector(off_reader.get_point_cloud());
  std::clog << "Successfully read " << witnesses.size() << " points.\n";
  std::clog << "Ambient dimension is " << witnesses[0].dimension() << ".\n";
 
  
  
                                               std::back_inserter(landmarks));
 
  
 
  strong_witness_complex.create_complex(simplex_tree, max_squared_alpha, lim_d);
 
  std::clog << 
"The complex contains " << simplex_tree.
num_simplices() << 
" simplices \n";
  std::clog << 
"   and has dimension " << simplex_tree.
dimension() << 
" \n";
 
  
 
  
  
  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();
  }
 
  return 0;
}
 
void program_options(int argc, char* argv[], int& nbL, std::string& file_name, std::string& filediag,
  namespace po = boost::program_options;
 
  po::options_description hidden("Hidden options");
  hidden.add_options()("input-file", po::value<std::string>(&file_name),
                       "Name of file containing a point set in off format.");
 
  po::options_description visible("Allowed options", 100);
  Filtration_value default_alpha = std::numeric_limits<Filtration_value>::infinity();
 
  visible.add_options()("help,h", "produce help message")("landmarks,l", po::value<int>(&nbL),
                                                          "Number of landmarks to choose from the point cloud.")(
      "output-file,o", po::value<std::string>(&filediag)->default_value(std::string()),
      "Name of file in which the persistence diagram is written. Default print in standard output")(
      "max-sq-alpha,a", po::value<Filtration_value>(&max_squared_alpha)->default_value(default_alpha),
      "Maximal squared relaxation parameter.")(
      "field-charac,p", po::value<int>(&p)->default_value(11),
      "Characteristic p of the coefficient field Z/pZ for computing homology.")(
      "min-persistence,m", po::value<Filtration_value>(&min_persistence)->default_value(0),
      "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length "
      "intervals")("cpx-dimension,d", po::value<int>(&dim_max)->default_value(std::numeric_limits<int>::max()),
                   "Maximal dimension of the strong witness complex we want to compute.");
 
  po::positional_options_description pos;
  pos.add("input-file", 1);
 
  po::options_description all;
  all.add(visible).add(hidden);
  po::variables_map vm;
 
  po::store(po::command_line_parser(argc, argv).options(all).positional(pos).run(), vm);
  po::notify(vm);
 
  if (vm.count("help") || !vm.count("input-file")) {
    std::clog << std::endl;
    std::clog << "Compute the persistent homology with coefficient field Z/pZ \n";
    std::clog << "of a Strong witness complex defined on a set of input points.\n \n";
    std::clog << "The output diagram contains one bar per line, written with the convention: \n";
    std::clog << "   p   dim b d \n";
    std::clog << "where dim is the dimension of the homological feature,\n";
    std::clog << "b and d are respectively the birth and death of the feature and \n";
    std::clog << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl;
 
    std::clog << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl;
    std::clog << visible << std::endl;
    exit(-1);
  }
}
OFF file reader implementation in order to read points from an OFF file.
Definition: Points_off_io.h:122
Simplex Tree data structure for representing simplicial complexes.
Definition: Simplex_tree.h:81
Options::Filtration_value Filtration_value
Type for the value of the filtration function.
Definition: Simplex_tree.h:88
void initialize_filtration()
Initializes the filtration cache, i.e. sorts the simplices according to their order in the filtration...
Definition: Simplex_tree.h:916
int dimension(Simplex_handle sh)
Returns the dimension of a simplex.
Definition: Simplex_tree.h:602
size_t num_simplices()
returns the number of simplices in the simplex_tree.
Definition: Simplex_tree.h:580
Structure representing the coefficient field .
Definition: Field_Zp.h:27
Computes the persistent cohomology of a filtered complex.
Definition: Persistent_cohomology.h:52
Constructs strong witness complex for given sets of witnesses and landmarks in Euclidean space.
Definition: Euclidean_strong_witness_complex.h:51
void choose_n_farthest_points(Distance dist, Point_range const &input_pts, std::size_t final_size, std::size_t starting_point, PointOutputIterator output_it, DistanceOutputIterator dist_it={})
Subsample by a greedy strategy of iteratively adding the farthest point from the current chosen point...
Definition: choose_n_farthest_points.h:69
@ random_starting_point
Definition: choose_n_farthest_points.h:34
Value type for a filtration function on a cell complex.
Definition: FiltrationValue.h:20