#!/usr/bin/env python import gudhi import argparse """ 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 Copyright (C) 2018 Inria Modification(s): - YYYY/MM Author: Description of the modification """ __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2018 Inria" __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.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", ) 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") nerve_complex.set_color_from_coordinate(args.coordinate) nerve_complex.set_function_from_coordinate(args.coordinate) nerve_complex.set_graph_from_OFF() nerve_complex.set_resolution_with_interval_number(args.resolution) nerve_complex.set_gain(args.gain) nerve_complex.set_cover_from_function() nerve_complex.find_simplices() 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." ) print(result_str) for filtered_value in simplex_tree.get_filtration(): print(filtered_value[0])