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Diffstat (limited to 'trunk/src/cython/example/random_cubical_complex_persistence_example.py')
-rwxr-xr-x | trunk/src/cython/example/random_cubical_complex_persistence_example.py | 58 |
1 files changed, 58 insertions, 0 deletions
diff --git a/trunk/src/cython/example/random_cubical_complex_persistence_example.py b/trunk/src/cython/example/random_cubical_complex_persistence_example.py new file mode 100755 index 00000000..c832d6bf --- /dev/null +++ b/trunk/src/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()) |