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
|
from cython cimport numeric
from libcpp.vector cimport vector
from libcpp.string cimport string
from libcpp.map cimport map
from libcpp.pair cimport pair
from os import path
from numpy import array as np_array
""" 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) 2017 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2017 Inria"
__license__ = "MIT"
cdef extern from "Reader_utils_interface.h" namespace "Gudhi":
vector[vector[double]] read_matrix_from_csv_file(string off_file, char separator)
map[int, vector[pair[double, double]]] read_pers_intervals_grouped_by_dimension(string filename)
vector[pair[double, double]] read_pers_intervals_in_dimension(string filename, int only_this_dim)
def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'):
"""Read lower triangular matrix from a CSV style file.
:param csv_file: A CSV file style name.
:type csv_file: string
:param separator: The value separator in the CSV file. Default value is ';'
:type separator: char
:returns: The lower triangular matrix.
:rtype: vector[vector[double]]
"""
if csv_file:
if path.isfile(csv_file):
return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0]))
print("file " + csv_file + " not set or not found.")
return []
def read_persistence_intervals_grouped_by_dimension(persistence_file=''):
"""Reads a file containing persistence intervals.
Each line might contain 2, 3 or 4 values: [[field] dimension] birth death
The return value is an `map[dim, vector[pair[birth, death]]]`
where `dim` is an `int`, `birth` a `double`, and `death` a `double`.
Note: the function does not check that birth <= death.
:param persistence_file: A persistence file style name.
:type persistence_file: string
:returns: The persistence pairs grouped by dimension.
:rtype: map[int, vector[pair[double, double]]]
"""
if persistence_file:
if path.isfile(persistence_file):
return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file))
print("file " + persistence_file + " not set or not found.")
return []
def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=-1):
"""Reads a file containing persistence intervals.
Each line of persistence_file might contain 2, 3 or 4 values:
[[field] dimension] birth death
Note: the function does not check that birth <= death.
:param persistence_file: A persistence file style name.
:type persistence_file: string
:param only_this_dim: The specific dimension. Default value is -1.
If `only_this_dim` = -1, dimension is ignored and all lines are returned.
If `only_this_dim` is >= 0, only the lines where dimension =
`only_this_dim` (or where dimension is not specified) are returned.
:type only_this_dim: int.
:returns: The persistence intervals.
:rtype: numpy array of dimension 2
"""
if persistence_file:
if path.isfile(persistence_file):
return np_array(read_pers_intervals_in_dimension(str.encode(
persistence_file), only_this_dim))
print("file " + persistence_file + " not set or not found.")
return []
|