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git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/toplex_map@2891 636b058d-ea47-450e-bf9e-a15bfbe3eedb

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diff --git a/src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp b/src/Witness_complex/example/example_strong_witness_complex_fvecs.cpp
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+/*    This file is part of the Gudhi Library. The Gudhi library
+ *    (Geometric Understanding in Higher Dimensions) is a generic C++
+ *    library for computational topology.
+ *
+ *    Author(s):       Siargey Kachanovich
+ *
+ *    Copyright (C) 2016  INRIA (France)
+ *
+ *    This program is free software: you can redistribute it and/or modify
+ *    it under the terms of the GNU General Public License as published by
+ *    the Free Software Foundation, either version 3 of the License, or
+ *    (at your option) any later version.
+ *
+ *    This program is distributed in the hope that it will be useful,
+ *    but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ *    GNU General Public License for more details.
+ *
+ *    You should have received a copy of the GNU General Public License
+ *    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+
+#include <gudhi/Simplex_tree.h>
+#include <gudhi/Fake_simplex_tree.h>
+#include <gudhi/Euclidean_strong_witness_complex.h>
+#include <gudhi/pick_n_random_points.h>
+#include <gudhi/Points_fvecs_reader.h>
+
+#include <CGAL/Epick_d.h>
+
+#include <iostream>
+#include <fstream>
+#include <ctime>
+#include <string>
+#include <vector>
+
+using K = CGAL::Epick_d<CGAL::Dynamic_dimension_tag>;
+using Point_d = typename K::Point_d;
+using Witness_complex = Gudhi::witness_complex::Euclidean_strong_witness_complex<K>;
+using Point_vector = std::vector<Point_d>;
+
+int main(int argc, char * const argv[]) {
+  if (argc != 5) {
+    std::cerr << "Usage: " << argv[0]
+        << " path_to_point_file number_of_landmarks max_squared_alpha limit_dimension\n";
+    return 0;
+  }
+
+  std::string file_name = argv[1];
+  int nbL = atoi(argv[2]), lim_dim = atoi(argv[4]);
+  double alpha2 = atof(argv[3]);
+  clock_t start, end;
+  //Gudhi::Simplex_tree<> simplex_tree;
+  Gudhi::Fake_simplex_tree simplex_tree;
+
+  // Read the point file
+  Point_vector point_vector, landmarks;
+  Gudhi::load_points_from_fvecs_file<K>(file_name, std::back_insert_iterator< Point_vector >(point_vector));
+
+
+  std::cout << "Successfully read " << point_vector.size() << " points.\n";
+  std::cout << "Ambient dimension is " << point_vector[0].dimension() << ".\n";
+
+  // Choose landmarks
+  Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks));
+
+  // Compute witness complex
+  start = clock();
+  Witness_complex witness_complex(landmarks,
+                                  point_vector);
+
+  witness_complex.create_complex(simplex_tree, alpha2, lim_dim);
+  end = clock();
+  std::cout << "Strong witness complex took "
+      << static_cast<double>(end - start) / CLOCKS_PER_SEC << " s. \n";
+  std::cout << "Number of simplices is: " << simplex_tree.num_simplices() << std::endl;
+  std::cout << "Max dimension is : " << simplex_tree.dimension() << std::endl;
+
+}