#include <gudhi/Flag_complex_edge_collapser.h>
#include <gudhi/Simplex_tree.h>
#include <gudhi/Persistent_cohomology.h>
#include <gudhi/Points_off_io.h>
 
#include <boost/range/adaptor/transformed.hpp>
 
#include<utility>  
#include<vector>
#include<tuple>
 
 
using Point = std::vector<Filtration_value>;
using Vector_of_points = std::vector<Point>;
 
 
 
using Persistence_interval = std::tuple<int, Filtration_value, Filtration_value>;
struct cmp_intervals_by_length {
      : sc_(sc) { }
 
  template<typename Persistent_interval>
  bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) {
    return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1))
            > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2)));
  }
};
 
std::vector<Persistence_interval> get_persistence_intervals(
Simplex_tree& st, 
int ambient_dim) {
  std::vector<Persistence_interval> persistence_intervals;
  
  
  
  
  int p = 11;
  pcoh.init_coefficients(p);
 
  
  pcoh.compute_persistent_cohomology();
  
  cmp_intervals_by_length cmp(&st);
  auto persistent_pairs = pcoh.get_persistent_pairs();
  std::sort(std::begin(persistent_pairs), std::end(persistent_pairs), cmp);
  for (auto pair : persistent_pairs) {
    persistence_intervals.emplace_back(st.
dimension(get<0>(pair)),
  }
  return persistence_intervals;
}
 
int main(int argc, char* argv[]) {
  if (argc != 3) {
    std::cerr << "This program requires an OFF file and minimal threshold value as parameter\n";
    std::cerr << "For instance: ./Edge_collapse_conserve_persistence ../../data/points/tore3D_300.off 1.\n";
    exit(-1);  
  }
 
  std::string off_file_points {argv[1]};
  double threshold {atof(argv[2])};
 
  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);  
  }
 
  Proximity_graph proximity_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(),
                                                                                 threshold,
 
  if (num_edges(proximity_graph) <= 0) {
    std::cerr << "Total number of edges is zero." << std::endl;
    exit(-1);
  }
 
  int ambient_dim = point_vector[0].size();
 
  
  auto remaining_edges = Gudhi::collapse::flag_complex_collapse_edges(
    boost::adaptors::transform(edges(proximity_graph), [&](auto&&edge){
      return std::make_tuple(
static_cast<Vertex_handle>(source(edge, proximity_graph)),
 
                             get(Gudhi::edge_filtration_t(), proximity_graph, edge));
      })
  );
 
  for (
Vertex_handle vertex = 0; 
static_cast<std::size_t
>(vertex) < point_vector.size(); vertex++) {
 
    
  }
  for (auto remaining_edge : remaining_edges) {
    stree_from_collapse.
insert_simplex({std::get<0>(remaining_edge), std::get<1>(remaining_edge)},
                                       std::get<2>(remaining_edge));
  }
 
  std::vector<Persistence_interval> persistence_intervals_from_collapse = get_persistence_intervals(stree_from_collapse, ambient_dim);
 
  
 
  std::vector<Persistence_interval> persistence_intervals_wo_collapse = get_persistence_intervals(stree_wo_collapse, ambient_dim);
 
  
  if (persistence_intervals_wo_collapse.size() != persistence_intervals_from_collapse.size()) {
    std::cerr << "Number of persistence pairs with    collapse is " << persistence_intervals_from_collapse.size() << std::endl;
    std::cerr << "Number of persistence pairs without collapse is " << persistence_intervals_wo_collapse.size()   << std::endl;
    exit(-1);
  }
 
  int return_value = 0;
  auto ppwoc_ptr = persistence_intervals_wo_collapse.begin();
  for (auto ppfc: persistence_intervals_from_collapse) {
    if (ppfc != *ppwoc_ptr) {
      return_value++;
      std::cerr << "Without collapse: "
                << std::get<0>(*ppwoc_ptr) << " " << std::get<1>(*ppwoc_ptr) << " " << std::get<2>(*ppwoc_ptr)
                << " - With collapse: "
                << std::get<0>(ppfc) << " " << std::get<1>(ppfc) << " " << std::get<2>(ppfc) << std::endl;
    }
    ppwoc_ptr++;
  }
  return return_value;
}
Compute the Euclidean distance between two Points given by a range of coordinates....
Definition: distance_functions.h:32
OFF file reader implementation in order to read points from an OFF file.
Definition: Points_off_io.h:122
Options::Filtration_value Filtration_value
Type for the value of the filtration function.
Definition: Simplex_tree.h:88
std::pair< Simplex_handle, bool > insert_simplex(const InputVertexRange &simplex, Filtration_value filtration=0)
Insert a simplex, represented by a range of Vertex_handles, in the simplicial complex.
Definition: Simplex_tree.h:782
static Filtration_value filtration(Simplex_handle sh)
Returns the filtration value of a simplex.
Definition: Simplex_tree.h:537
void initialize_filtration()
Initializes the filtration cache, i.e. sorts the simplices according to their order in the filtration...
Definition: Simplex_tree.h:916
Options::Vertex_handle Vertex_handle
Type for the vertex handle.
Definition: Simplex_tree.h:96
void expansion(int max_dim)
Expands the Simplex_tree containing only its one skeleton until dimension max_dim.
Definition: Simplex_tree.h:1185
int dimension(Simplex_handle sh)
Returns the dimension of a simplex.
Definition: Simplex_tree.h:602
void insert_graph(const OneSkeletonGraph &skel_graph)
Inserts a 1-skeleton in an empty Simplex_tree.
Definition: Simplex_tree.h:1110
Structure representing the coefficient field .
Definition: Field_Zp.h:27
Computes the persistent cohomology of a filtered complex.
Definition: Persistent_cohomology.h:52
Global distance functions.
Graph simplicial complex methods.
typename boost::adjacency_list< boost::vecS, boost::vecS, boost::directedS, boost::property< vertex_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value >, boost::property< edge_filtration_t, typename SimplicialComplexForProximityGraph::Filtration_value > > Proximity_graph
Proximity_graph contains the vertices and edges with their filtration values in order to store the re...
Definition: graph_simplicial_complex.h:45
Value type for a filtration function on a cell complex.
Definition: FiltrationValue.h:20
Handle type for the vertices of a cell complex.
Definition: VertexHandle.h:15