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#!/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="Voronoi GIC " "from points read in a OFF file.",
epilog="Example: "
"example/voronoi_graph_induced_complex.py "
"-f ../data/points/human.off -n 700 -v"
"- Constructs the Voronoi GIC with the "
"points from the given OFF file.",
)
parser.add_argument("-f", "--file", type=str, required=True)
parser.add_argument("-n", "--subsample-nb-points", type=int, default=100)
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("GIC")
nerve_complex.set_color_from_coordinate()
nerve_complex.set_graph_from_OFF()
nerve_complex.set_cover_from_Voronoi(args.subsample_nb_points)
nerve_complex.find_simplices()
nerve_complex.plot_off()
simplex_tree = nerve_complex.create_simplex_tree()
nerve_complex.compute_PD()
if args.verbose:
print("Iterator on graph induced complex simplices")
result_str = (
"Graph induced complex 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])
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