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#!/usr/bin/env python
import gudhi
import argparse
"""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) 2017 Swansea University
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/>.
"""
__author__ = "Pawel Dlotko"
__copyright__ = "Copyright (C) 2017 Swansea University"
__license__ = "GPL v3"
print("#####################################################################")
print("Persistence representations diagrams example")
parser = argparse.ArgumentParser(description='Statistics of persistence diagrams from file ',
epilog='Example: '
'example/persistence_representations_diagrams_example.py '
'-f file_with_diagram -d 1')
parser.add_argument("-f", "--file", type=str, required=True)
parser.add_argument("-d", "--dimension", type=int, default=0)
args = parser.parse_args()
print "Here are the parameters of the program: ",args.file," , " ,args.dimension
p = gudhi.PersistenceIntervals(None,args.dimension,args.file);
min_max_ = p.get_x_range();
print "Birth-death range : ", min_max_
dominant_ten_intervals_length = p.length_of_dominant_intervals(10)
print "Length of ten dominant intervals : ", dominant_ten_intervals_length
ten_dominant_intervals = p.dominant_intervals(10);
print "Here are the dominant intervals : " , ten_dominant_intervals
histogram = p.histogram_of_lengths(10);
print "Here is the histogram of barcode's length : ", histogram
cumulative_histogram = p.cumulative_histogram_of_lengths(10)
print "Cumulative histogram : " ,cumulative_histogram
char_funct_diag = p.characteristic_function_of_diagram(min_max_[0], min_max_[1],None)
print "Characteristic function of diagram : ",char_funct_diag
cumul_char_funct_diag = p.cumulative_characteristic_function_of_diagram(min_max_[0], min_max_[1],None)
print "Cumulative characteristic function of diagram : ",cumul_char_funct_diag
pbns = p.compute_persistent_betti_numbers()
print "Persistence Betti numbers ", pbns
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