#include <gudhi/Flag_complex_sparse_matrix.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 <gudhi/graph_simplicial_complex.h>

#include <boost/graph/adjacency_list.hpp>
#include <boost/program_options.hpp>

// Types definition

using Simplex_tree = Gudhi::Simplex_tree<>;
using Filtration_value = Simplex_tree::Filtration_value;
using Point = std::vector<Filtration_value>;
using Vector_of_points = std::vector<Point>;


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>>;

using Adjacency_list = boost::adjacency_list<boost::vecS, boost::vecS, boost::directedS,
                                             boost::property<Gudhi::vertex_filtration_t, double>,
                                             boost::property<Gudhi::edge_filtration_t, double>>;


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 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;

  Adjacency_list proximity_graph = Gudhi::compute_proximity_graph<Simplex_tree>(off_reader.get_point_cloud(),
                                                                                threshold,
                                                                                Gudhi::Euclidean_distance());

  if (num_edges(proximity_graph) <= 0) {
    std::cerr << "Total number of egdes are zero." << std::endl;
    exit(-1);
  }

  std::cout << "Filtered edge collapse begins" << std::endl;
  Flag_complex_sparse_matrix mat_filt_edge_coll(proximity_graph);

  std::cout << "Computing the one-skeleton for threshold: " << threshold << std::endl;

  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);
  }
}