1 files changed, 58 insertions, 0 deletions
diff --git a/cython/example/random_cubical_complex_persistence_example.py b/cython/example/random_cubical_complex_persistence_example.py
new file mode 100755
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--- /dev/null
+++ b/cython/example/random_cubical_complex_persistence_example.py
@@ -0,0 +1,58 @@
+#!/usr/bin/env python
+
+import gudhi
+import numpy
+from functools import reduce
+import argparse
+import operator
+
+
+"""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
+
+   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"
+__license__ = "GPL v3"
+
+parser = argparse.ArgumentParser(description='Random cubical complex.',
+                                 epilog='Example: '
+                                 './random_cubical_complex_persistence_example.py'
+                                 ' 10 10 10 - Constructs a random cubical '
+                                 'complex in a dimension [10, 10, 10] (aka. '
+                                 '1000 random top dimensional cells).')
+parser.add_argument('dimension', type=int, nargs="*",
+                    help='Cubical complex dimensions')
+
+args = parser.parse_args()
+dimension_multiplication = reduce(operator.mul, args.dimension, 1)
+
+if dimension_multiplication > 1: 
+    print("#####################################################################")
+    print("CubicalComplex creation")
+    cubical_complex = gudhi.CubicalComplex(dimensions=args.dimension,
+                                           top_dimensional_cells = numpy.random.rand(dimension_multiplication))
+
+    print("persistence(homology_coeff_field=2, min_persistence=0)=")
+    print(cubical_complex.persistence(homology_coeff_field=2, min_persistence=0))
+
+    print("betti_numbers()=")
+    print(cubical_complex.betti_numbers())