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
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
/* This file is part of the Gudhi Library. The Gudhi library
* (Geometric Understanding in Higher Dimensions) is a generic C++
* library for computational topology.
*
* Author(s): Pawel Dlotko
*
* Copyright (C) 2015 INRIA (France)
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include <gudhi/reader_utils.h>
#include <gudhi/persistence_representations/Persistence_intervals.h>
#include <iostream>
using namespace Gudhi;
using namespace Gudhi::Gudhi_stat;
int main( int argc , char** argv )
{
if ( argc != 2 )
{
std::cout << "To run this program, please provide the name of a file with persistence diagram \n";
return 1;
}
Persistence_intervals p( argv[1] );
std::pair<double,double> min_max_ = p.min_max();
std::cout << "Birth-death range : " << min_max_.first << " " << min_max_.second << std::endl;
std::vector<double> dominant_ten_intervals_length = p.length_of_dominant_intervals(10);
std::cout << "Lendth of ten dominant intervals : " <<std::endl;
for ( size_t i = 0 ; i != dominant_ten_intervals_length.size() ; ++i )
{
std::cout << dominant_ten_intervals_length[i] <<std::endl;
}
std::vector< std::pair<double,double> > ten_dominant_intervals = p.dominant_intervals( 10 );
std::cout << "Here are the dominant intervals : " <<std::endl;
for ( size_t i = 0 ; i != ten_dominant_intervals.size() ; ++i )
{
std::cout << "( " << ten_dominant_intervals[i].first<< "," << ten_dominant_intervals[i].second <<std::endl;
}
std::vector< size_t > histogram = p.histogram_of_lengths( 10 );
std::cout << "Here is the histogram of barcode's length : " <<std::endl;
for ( size_t i = 0 ; i != histogram.size() ; ++i )
{
std::cout << histogram[i] << " ";
}
std::cout <<std::endl;
std::vector< size_t > cumulative_histogram = p.cumulative_histogram_of_lengths( 10 );
std::cout<< "Cumuative histogram : " <<std::endl;
for ( size_t i = 0 ; i != cumulative_histogram.size() ; ++i )
{
std::cout << cumulative_histogram[i] << " ";
}
std::cout <<std::endl;
std::vector< double > char_funct_diag = p.characteristic_function_of_diagram( min_max_.first , min_max_.second );
std::cout << "Characteristic function of diagram : " <<std::endl;
for ( size_t i = 0 ; i != char_funct_diag.size() ; ++i )
{
std::cout << char_funct_diag[i] << " ";
}
std::cout <<std::endl;
std::vector< double > cumul_char_funct_diag = p.cumulative_characteristic_function_of_diagram( min_max_.first , min_max_.second );
std::cout << "Cumulative characteristic function of diagram : " <<std::endl;
for ( size_t i = 0 ; i != cumul_char_funct_diag.size() ; ++i )
{
std::cout << cumul_char_funct_diag[i] << " ";
}
std::cout <<std::endl;
std::cout << "Persistence Betti numbers \n";
std::vector< std::pair< double , size_t > > pbns = p.compute_persistent_betti_numbers();
for ( size_t i = 0 ; i != pbns.size() ; ++i )
{
std::cout << pbns[i].first << " " << pbns[i].second <<std::endl;
}
return 0;
}
|