1 files changed, 0 insertions, 79 deletions
diff --git a/src/Witness_complex/example/example_strong_witness_complex_off.cpp b/src/Witness_complex/example/example_strong_witness_complex_off.cpp
deleted file mode 100644
index 0ee9ee90..00000000
--- a/src/Witness_complex/example/example_strong_witness_complex_off.cpp
+++ /dev/null
@@ -1,79 +0,0 @@
-/*    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/Euclidean_strong_witness_complex.h>
-#include <gudhi/pick_n_random_points.h>
-#include <gudhi/Points_off_io.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;
-
-  // Read the point file
-  Point_vector point_vector, landmarks;
-  Gudhi::Points_off_reader<Point_d> off_reader(file_name);
-  if (!off_reader.is_valid()) {
-      std::cerr << "Strong witness complex - Unable to read file " << file_name << "\n";
-      exit(-1);  // ----- >>
-    }
-  point_vector = Point_vector(off_reader.get_point_cloud());
-
-  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() << "\n";
-}