Add utilities

3 files changed, 394 insertions, 0 deletions

diff --git a/src/Collapse/utilities/CMakeLists.txt b/src/Collapse/utilities/CMakeLists.txt
new file mode 100644
index 00000000..bc241bf2
--- /dev/null
+++ b/src/Collapse/utilities/CMakeLists.txt
@@ -0,0 +1,21 @@
+project(Collapse_utilities)
+
+# From a point cloud
+add_executable ( point_cloud_edge_collapse_rips_persistence point_cloud_edge_collapse_rips_persistence.cpp )
+target_link_libraries(point_cloud_edge_collapse_rips_persistence Boost::program_options)
+
+if (TBB_FOUND)
+  target_link_libraries(point_cloud_edge_collapse_rips_persistence ${TBB_LIBRARIES})
+endif()
+add_test(NAME point_cloud_edge_collapse_rips_persistence COMMAND $<TARGET_FILE:point_cloud_edge_collapse_rips_persistence>
+         "-i" "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" "-e" "1e40" "-o" "result.pers")
+
+# From a distance matrix
+add_executable ( distance_matrix_edge_collapse_rips_persistence distance_matrix_edge_collapse_rips_persistence.cpp )
+target_link_libraries(distance_matrix_edge_collapse_rips_persistence Boost::program_options)
+
+if (TBB_FOUND)
+  target_link_libraries(distance_matrix_edge_collapse_rips_persistence ${TBB_LIBRARIES})
+endif()
+#add_test(NAME distance_matrix_edge_collapse_rips_persistence COMMAND $<TARGET_FILE:distance_matrix_edge_collapse_rips_persistence>
+#         "-m" "f" "-i" "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" "-e" "1e40")
diff --git a/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp b/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp
new file mode 100644
index 00000000..a2bc1c93
--- /dev/null
+++ b/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp
@@ -0,0 +1,181 @@
+#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>>;
+
+void program_options(int argc, char* const argv[], double& min_persistence, double& end_thresold,
+                     int& dimension, int& dim_max, std::string& in_file_name, std::string& out_file_name) {
+  namespace po = boost::program_options;
+  po::options_description visible("Allowed options", 100);
+      visible.add_options()
+        ("help,h", "produce help message")
+      	("min_persistence,m", po::value<double>(&min_persistence)->default_value(0.1),
+         "Minimum persistence interval length")
+        ("end_thresold,e", po::value<double>(&end_thresold)->default_value(1),
+         "Final threshold for rips complex.")
+        ("dimensions,D", po::value<int>(&dimension)->default_value(2),
+         "Dimension of the manifold.")
+        ("dim_max,k ", po::value<int>(&dim_max)->default_value(2),
+         "Maximum allowed dimension of the Rips complex.")
+        ("input_file_name,i", po::value<std::string>(&in_file_name),
+         "The input file.")
+        ("out_file_name,o", po::value<std::string>(&out_file_name),
+         "The output file.");
+
+  po::options_description all;
+  all.add(visible);
+  po::variables_map vm;
+  po::store(po::command_line_parser(argc, argv).options(all).run(), vm);
+  po::notify(vm);
+  if (vm.count("help")) {
+    std::cout << std::endl;
+    std::cout << "Computes rips complexes of different threshold values, to 'end_thresold' from a n random uniform "
+                 "point_vector on a selected manifold, . \n";
+    std::cout << "Strongly collapses all the rips complexes and output the results in out_file. \n";
+    std::cout << "The experiments are repeted 'repete' num of times for each threshold value. \n";
+    std::cout << "type -m for manifold options, 's' for uni sphere, 'b' for unit ball, 'f' for file. \n";
+    std::cout << "type -i 'filename' for Input file option for exported point sample. \n";
+    std::cout << std::endl << std::endl;
+    std::cout << "Usage: " << argv[0] << " [options]" << std::endl << std::endl;
+    std::cout << visible << std::endl;
+    std::abort();
+  }
+}
+
+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);
+    }
+  }
+};
+
+int main(int argc, char* const argv[]) {
+  auto the_begin = std::chrono::high_resolution_clock::now();
+  std::string out_file_name;
+  std::string in_file_name;
+  std::size_t number_of_points;
+
+  typedef size_t Vertex_handle;
+  typedef std::vector<std::tuple<Filtration_value, Vertex_handle, Vertex_handle>> Filtered_sorted_edge_list;
+
+  int dimension;
+  double end_threshold;
+  double min_persistence;
+  int dim_max = 2;
+
+  program_options(argc, argv, min_persistence, end_threshold, dimension, dim_max, in_file_name,
+                  out_file_name);
+
+  std::cout << "The current input values to run the program is: " << std::endl;
+  std::cout << "min_persistence, end_threshold, dimension, max_complex_dimension, in_file_name, out_file_name"
+            << std::endl;
+  std::cout << min_persistence << ", " << end_threshold << ", " << dimension << ", " << dim_max
+            << ", " << in_file_name << ", " << out_file_name << std::endl;
+
+  Map map_empty;
+
+  Distance_matrix distances;
+  Distance_matrix sparse_distances;
+
+  distances = Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(in_file_name);
+  number_of_points = distances.size();
+  std::cout << "Read the distance matrix succesfully, of size: " << number_of_points << std::endl;
+
+
+  std::cout << "Successfully read " << number_of_points << " point_vector.\n";
+
+  std::cout << "Point Set Generated." << std::endl;
+
+  Filtered_sorted_edge_list edge_t;
+  std::cout << "Computing the one-skeleton for threshold: " << end_threshold << std::endl;
+
+  Rips_edge_list Rips_edge_list_from_file(distances, end_threshold);
+  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_after_collapse(sparse_distances, end_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(3);
+
+  pcoh.compute_persistent_cohomology(min_persistence);
+  if (out_file_name.empty()) {
+    pcoh.output_diagram();
+  } else {
+    std::ofstream out(out_file_name);
+    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;
+}
diff --git a/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp b/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp
new file mode 100644
index 00000000..abd4e862
--- /dev/null
+++ b/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp
@@ -0,0 +1,192 @@
+#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>>;
+
+void program_options(int argc, char* const argv[], double& min_persistence, double& end_thresold,
+                     int& dimension, int& dim_max, std::string& in_file_name, std::string& out_file_name) {
+  namespace po = boost::program_options;
+  po::options_description visible("Allowed options", 100);
+      visible.add_options()
+        ("help,h", "produce help message")
+      	("min_persistence,m", po::value<double>(&min_persistence)->default_value(0.1),
+         "Minimum persistence interval length")
+        ("end_thresold,e", po::value<double>(&end_thresold)->default_value(1),
+         "Final threshold for rips complex.")
+        ("dimensions,D", po::value<int>(&dimension)->default_value(2),
+         "Dimension of the manifold.")
+        ("dim_max,k ", po::value<int>(&dim_max)->default_value(2),
+         "Maximum allowed dimension of the Rips complex.")
+        ("input_file_name,i", po::value<std::string>(&in_file_name),
+         "The input file.")
+        ("out_file_name,o", po::value<std::string>(&out_file_name),
+         "The output file.");
+
+  po::options_description all;
+  all.add(visible);
+  po::variables_map vm;
+  po::store(po::command_line_parser(argc, argv).options(all).run(), vm);
+  po::notify(vm);
+  if (vm.count("help")) {
+    std::cout << std::endl;
+    std::cout << "Computes rips complexes of different threshold values, to 'end_thresold' from a n random uniform "
+                 "point_vector on a selected manifold, . \n";
+    std::cout << "Strongly collapses all the rips complexes and output the results in out_file. \n";
+    std::cout << "The experiments are repeted 'repete' num of times for each threshold value. \n";
+    std::cout << "type -m for manifold options, 's' for uni sphere, 'b' for unit ball, 'f' for file. \n";
+    std::cout << "type -i 'filename' for Input file option for exported point sample. \n";
+    std::cout << std::endl << std::endl;
+    std::cout << "Usage: " << argv[0] << " [options]" << std::endl << std::endl;
+    std::cout << visible << std::endl;
+    std::abort();
+  }
+}
+
+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);
+    }
+  }
+};
+
+int main(int argc, char* const argv[]) {
+  auto the_begin = std::chrono::high_resolution_clock::now();
+  std::string out_file_name;
+  std::string in_file_name;
+  std::size_t number_of_points;
+
+  typedef size_t Vertex_handle;
+  typedef std::vector<std::tuple<Filtration_value, Vertex_handle, Vertex_handle>> Filtered_sorted_edge_list;
+
+  int dimension;
+  double end_threshold;
+  double min_persistence;
+  int dim_max = 2;
+
+  program_options(argc, argv, min_persistence, end_threshold, dimension, dim_max, in_file_name,
+                  out_file_name);
+
+  std::cout << "The current input values to run the program is: " << std::endl;
+  std::cout << "min_persistence, end_threshold, dimension, max_complex_dimension, in_file_name, out_file_name"
+            << std::endl;
+  std::cout << min_persistence << ", " << end_threshold << ", " << dimension << ", " << dim_max
+            << ", " << in_file_name << ", " << out_file_name << std::endl;
+
+  Map map_empty;
+
+  Distance_matrix distances;
+  Distance_matrix sparse_distances;
+
+  Gudhi::Points_off_reader<Point> off_reader(in_file_name);
+  if (!off_reader.is_valid()) {
+    std::cerr << "Unable to read file " << in_file_name << "\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);  // ----- >>
+  }
+
+  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: " << end_threshold << std::endl;
+
+  Rips_edge_list Rips_edge_list_from_file(point_vector, end_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, end_threshold);
+  Rips_complex rips_complex_after_collapse(sparse_distances, end_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(3);
+
+  pcoh.compute_persistent_cohomology(min_persistence);
+  if (out_file_name.empty()) {
+    pcoh.output_diagram();
+  } else {
+    std::ofstream out(out_file_name);
+    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;
+}