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diff --git a/src/cython/example/alpha_complex_from_file_example.py b/src/cython/example/alpha_complex_from_file_example.py
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+#!/usr/bin/env python
+
+import gudhi
+import pandas
+import argparse
+
+"""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): Vincent Rouvreau
+
+ Copyright (C) 2016 INRIA Saclay (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/>.
+"""
+
+__author__ = "Vincent Rouvreau"
+__copyright__ = "Copyright (C) 2016 INRIA Saclay (France)"
+__license__ = "GPL v3"
+
+print("#####################################################################")
+print("AlphaComplex creation from points read in a file")
+
+parser = argparse.ArgumentParser(description='AlphaComplex creation from '
+ 'points read in a file.',
+ epilog='Example: '
+ 'example/alpha_complex_from_file_example.py '
+ 'data/500_random_points_on_3D_Torus.csv '
+ '- Constructs a alpha complex with the '
+ 'points from the given file. File format '
+ 'is X1, X2, ..., Xn')
+parser.add_argument('file', type=argparse.FileType('r'))
+args = parser.parse_args()
+
+points = pandas.read_csv(args.file, header=None)
+
+alpha_complex = gudhi.AlphaComplex(points=points.values,
+ max_alpha_square=0.5)
+
+print("dimension=", alpha_complex.dimension())
+print("point[0]=", alpha_complex.get_point(0))
+print("point[5]=", alpha_complex.get_point(5))
+
+alpha_complex.initialize_filtration()
+diag = alpha_complex.persistence(homology_coeff_field=2, min_persistence=0.1)
+
+print("betti_numbers()=")
+print(alpha_complex.betti_numbers())
+
+print("star([0])=", alpha_complex.get_star_tree([0]))
+print("coface([0], 1)=", alpha_complex.get_coface_tree([0], 1))