blob: 84e8e38e8005a2502019f7247ffd00ea025fb243 (
plain)
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
|
# 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): Raphaël Tinarrage and Yuichi Ike
#
# Copyright (C) 2020 Inria, Copyright (C) 2020 FUjitsu Laboratories Ltd.
#
# Modification(s):
# - YYYY/MM Author: Description of the modification
from gudhi import SimplexTree
class WeightedRipsComplex:
"""
class to generate a weighted Rips complex
from a distance matrix and filtration value
"""
def __init__(self,
distance_matrix=None,
filtration_values=None,
max_filtration=float('inf')):
"""
Parameters:
distance_matrix: list of list of float,
distance matrix (full square or lower triangular)
filtration_values: list of float,
flitration value for each index
max_filtration: float,
specifies the maximal filtration value to be considered
"""
self.distance_matrix = distance_matrix
self.filtration_values = filtration_values
self.max_filtration = max_filtration
def create_simplex_tree(self, max_dimension):
"""
Parameter:
max_dimension: int
graph expansion until this given dimension
"""
dist = self.distance_matrix
F = self.filtration_values
num_pts = len(dist)
st = SimplexTree()
for i in range(num_pts):
if F[i] < self.max_filtration:
st.insert([i], F[i])
for i in range(num_pts):
for j in range(num_pts):
value = (dist[i][j] + F[i] + F[j]) / 2
if value < self.max_filtration:
st.insert([i,j], filtration=value)
return st
|
