1 files changed, 94 insertions, 0 deletions
diff --git a/src/Collapse/test/collapse_unit_test.cpp b/src/Collapse/test/collapse_unit_test.cpp
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+++ b/src/Collapse/test/collapse_unit_test.cpp
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+/*    This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ *    See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ *    Author(s):       Vincent Rouvreau
+ *
+ *    Copyright (C) 2020 Inria
+ *
+ *    Modification(s):
+ *      - YYYY/MM Author: Description of the modification
+ */
+
+#include <iostream>
+#include <fstream>
+#include <string>
+#include <algorithm>
+#include <utility>  // std::pair, std::make_pair
+#include <cmath>  // float comparison
+#include <limits>
+#include <functional>  // greater
+#include <tuple>  // std::tie
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE "collapse"
+#include <boost/test/unit_test.hpp>
+#include <boost/mpl/list.hpp>
+
+//  ^
+// /!\ Nothing else from Simplex_tree shall be included to test includes are well defined.
+#include "gudhi/FlagComplexSpMatrix.h"
+#include "gudhi/Rips_edge_list.h"
+
+using namespace Gudhi;
+
+// Types definition
+using Vector_of_points = std::vector<std::vector<double>>;
+
+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>>;
+
+
+BOOST_AUTO_TEST_CASE(collapse) {
+  typedef size_t Vertex_handle;
+  typedef std::vector<std::tuple<Filtration_value, Vertex_handle, Vertex_handle>> Filtered_sorted_edge_list;
+
+  std::size_t number_of_points;
+  std::string off_file_points;
+  std::string filediag;
+  int dim_max;
+  int p;
+  double min_persistence;
+
+  Map map_empty;
+
+  Distance_matrix sparse_distances;
+
+
+  Vector_of_points point_vector {{0., 0.},{0., 1.},{1., 0.},{1., 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;
+
+  double threshold = 1.;
+  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();
+ 
+}
+
+