#!/usr/bin/env python

import gudhi
import numpy
import argparse
import operator


"""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):       Vincent Rouvreau

   Copyright (C) 2016 INRIA

   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__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 INRIA"
__license__ = "GPL v3"

parser = argparse.ArgumentParser(description='Random cubical complex.',
                                 epilog='Example: '
                                 './random_cubical_complex_persistence_example.py'
                                 ' 10 10 10 - Constructs a random cubical '
                                 'complex in a dimension [10, 10, 10] (aka. '
                                 '1000 random top dimensional cells).')
parser.add_argument('dimension', type=int, nargs="*",
                    help='Cubical complex dimensions')

args = parser.parse_args()
dimension_multiplication = reduce(operator.mul, args.dimension, 1)

if dimension_multiplication > 1: 
    print("#####################################################################")
    print("CubicalComplex creation")
    cubical_complex = gudhi.CubicalComplex(dimensions=args.dimension,
                                           top_dimensional_cells = numpy.random.rand(dimension_multiplication))

    print("persistence(homology_coeff_field=2, min_persistence=0)=")
    print(cubical_complex.persistence(homology_coeff_field=2, min_persistence=0))

    print("betti_numbers()=")
    print(cubical_complex.betti_numbers())