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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='Functional GIC '
'from points read in a OFF file.',
epilog='Example: '
'example/functional_graph_induced_complex.py '
'-o ../data/points/COIL_database/lucky_cat.off '
'-f ../data/points/COIL_database/lucky_cat_PCA1'
'- Constructs the functional GIC with the '
'points from the given OFF and function files.')
parser.add_argument("-o", "--off-file", type=str, required=True)
parser.add_argument("-f", "--function-file", type=str, required=True)
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.off_file)):
nerve_complex.set_type('GIC')
nerve_complex.set_color_from_file(args.function_file)
nerve_complex.set_function_from_file(args.function_file)
nerve_complex.set_graph_from_automatic_rips()
nerve_complex.set_automatic_resolution()
nerve_complex.set_gain()
nerve_complex.set_cover_from_function()
nerve_complex.find_simplices()
nerve_complex.plot_dot()
simplex_tree = nerve_complex.create_simplex_tree()
nerve_complex.compute_PD()
if (args.verbose):
print('Iterator on functional GIC simplices')
result_str = 'Functional GIC 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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