1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
|
#!/usr/bin/env python
import gudhi
import argparse
import math
""" 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) 2016 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 Inria"
__license__ = "MIT"
parser = argparse.ArgumentParser(description='AlphaComplex and RipsComplex '
'persistence creation from points read in '
'a OFF file. Bottleneck distance computation'
' on each dimension',
epilog='Example: '
'example/alpha_rips_persistence_bottleneck_distance.py '
'-f ../data/points/tore3D_1307.off -t 0.15 -d 3')
parser.add_argument("-f", "--file", type=str, required=True)
parser.add_argument("-t", "--threshold", type=float, default=0.5)
parser.add_argument("-d", "--max_dimension", type=int, default=1)
args = parser.parse_args()
with open(args.file, 'r') as f:
first_line = f.readline()
if (first_line == 'OFF\n') or (first_line == 'nOFF\n'):
point_cloud = gudhi.read_off(off_file=args.file)
print("#####################################################################")
print("RipsComplex creation from points read in a OFF file")
message = "RipsComplex with max_edge_length=" + repr(args.threshold)
print(message)
rips_complex = gudhi.RipsComplex(points=point_cloud,
max_edge_length=args.threshold)
rips_stree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension)
message = "Number of simplices=" + repr(rips_stree.num_simplices())
print(message)
rips_diag = rips_stree.persistence()
print("#####################################################################")
print("AlphaComplex creation from points read in a OFF file")
message = "AlphaComplex with max_edge_length=" + repr(args.threshold)
print(message)
alpha_complex = gudhi.AlphaComplex(points=point_cloud)
alpha_stree = alpha_complex.create_simplex_tree(max_alpha_square=(args.threshold * args.threshold))
message = "Number of simplices=" + repr(alpha_stree.num_simplices())
print(message)
alpha_diag = alpha_stree.persistence()
max_b_distance = 0.0
for dim in range(args.max_dimension):
# Alpha persistence values needs to be transform because filtration
# values are alpha square values
funcs = [math.sqrt, math.sqrt]
alpha_intervals = []
for interval in alpha_stree.persistence_intervals_in_dimension(dim):
alpha_intervals.append(map(lambda func,value: func(value), funcs, interval))
rips_intervals = rips_stree.persistence_intervals_in_dimension(dim)
bottleneck_distance = gudhi.bottleneck_distance(rips_intervals, alpha_intervals)
message = "In dimension " + repr(dim) + ", bottleneck distance = " + repr(bottleneck_distance)
print(message)
max_b_distance = max(bottleneck_distance, max_b_distance)
print("================================================================================")
message = "Bottleneck distance is " + repr(max_b_distance)
print(message)
else:
print(args.file, "is not a valid OFF file")
f.close()
|
