diff options
Diffstat (limited to 'src/cython/example/nerve_of_a_covering.py')
| -rwxr-xr-x | src/cython/example/nerve_of_a_covering.py | 70 |
1 files changed, 35 insertions, 35 deletions
diff --git a/src/cython/example/nerve_of_a_covering.py b/src/cython/example/nerve_of_a_covering.py index c5577cb1..3c8e0f90 100755 --- a/src/cython/example/nerve_of_a_covering.py +++ b/src/cython/example/nerve_of_a_covering.py @@ -3,52 +3,47 @@ import gudhi 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. +""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. + See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. + Author(s): Vincent Rouvreau - Author(s): Vincent Rouvreau + Copyright (C) 2018 Inria - Copyright (C) 2018 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/>. + Modification(s): + - YYYY/MM Author: Description of the modification """ __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2018 Inria" -__license__ = "GPL v3" +__license__ = "MIT" -parser = argparse.ArgumentParser(description='Nerve of a covering creation ' - 'from points read in a OFF file.', - epilog='Example: ' - 'example/nerve_of_a_covering.py ' - '-f ../data/points/human.off -c 2 -r 10 -g 0.3' - '- Constructs Nerve of a covering with the ' - 'points from the given OFF file.') +parser = argparse.ArgumentParser( + description="Nerve of a covering creation " "from points read in a OFF file.", + epilog="Example: " + "example/nerve_of_a_covering.py " + "-f ../data/points/human.off -c 2 -r 10 -g 0.3" + "- Constructs Nerve of a covering with the " + "points from the given OFF file.", +) parser.add_argument("-f", "--file", type=str, required=True) parser.add_argument("-c", "--coordinate", type=int, default=0) parser.add_argument("-r", "--resolution", type=int, default=10) parser.add_argument("-g", "--gain", type=float, default=0.3) -parser.add_argument("-v", "--verbose", default=False, action='store_true' , help='Flag for program verbosity') +parser.add_argument( + "-v", + "--verbose", + default=False, + action="store_true", + help="Flag for program verbosity", +) args = parser.parse_args() nerve_complex = gudhi.CoverComplex() nerve_complex.set_verbose(args.verbose) -if (nerve_complex.read_point_cloud(args.file)): - nerve_complex.set_type('Nerve') +if nerve_complex.read_point_cloud(args.file): + nerve_complex.set_type("Nerve") nerve_complex.set_color_from_coordinate(args.coordinate) nerve_complex.set_function_from_coordinate(args.coordinate) nerve_complex.set_graph_from_OFF() @@ -59,12 +54,17 @@ if (nerve_complex.read_point_cloud(args.file)): nerve_complex.write_info() simplex_tree = nerve_complex.create_simplex_tree() nerve_complex.compute_PD() - if (args.verbose): - print('Iterator on graph induced complex simplices') - result_str = 'Nerve is of dimension ' + \ - repr(simplex_tree.dimension()) + ' - ' + \ - repr(simplex_tree.num_simplices()) + ' simplices - ' + \ - repr(simplex_tree.num_vertices()) + ' vertices.' + if args.verbose: + print("Iterator on graph induced complex simplices") + result_str = ( + "Nerve is of dimension " + + repr(simplex_tree.dimension()) + + " - " + + repr(simplex_tree.num_simplices()) + + " simplices - " + + repr(simplex_tree.num_vertices()) + + " vertices." + ) print(result_str) for filtered_value in simplex_tree.get_filtration(): print(filtered_value[0]) |