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/* 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 Saclay (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/>.
*/
// for persistence algorithm
#include <gudhi/reader_utils.h>
#include <gudhi/Bitmap_cubical_complex.h>
#include <gudhi/Persistent_cohomology.h>
#include <boost/program_options.hpp>
// standard stuff
#include <iostream>
#include <sstream>
#include <vector>
#include <cstdlib>
#include <ctime>
using namespace Gudhi;
using namespace Gudhi::persistent_cohomology;
using namespace std;
int main(int argc, char** argv) {
srand(time(0));
cout << "This program computes persistent homology, by using Bitmap_cubical_complex class, of cubical complexes. "
"The first parameter of the program is the dimension D of the cubical complex. The next D parameters are number "
"of top dimensional cubes in each dimension of the cubical complex. The program will create random cubical "
"complex of that sizes and compute persistent homology of it." << endl;
int p = 2;
double min_persistence = 0;
size_t dimensionOfBitmap = (size_t) atoi(argv[1]);
std::vector< unsigned > sizes;
size_t multipliers = 1;
for (size_t dim = 0; dim != dimensionOfBitmap; ++dim) {
unsigned sizeInThisDimension = (unsigned) atoi(argv[2 + dim]);
sizes.push_back(sizeInThisDimension);
multipliers *= sizeInThisDimension;
}
std::vector< double > data;
for (size_t i = 0; i != multipliers; ++i) {
data.push_back(rand() / (double) RAND_MAX);
}
Bitmap_cubical_complex<double> b(sizes, data);
// Compute the persistence diagram of the complex
persistent_cohomology::Persistent_cohomology< Bitmap_cubical_complex<double>, Field_Zp > pcoh(b);
pcoh.init_coefficients(p); // initializes the coefficient field for homology
pcoh.compute_persistent_cohomology(min_persistence);
stringstream ss;
ss << "randomComplex_persistence";
std::ofstream out((char*) ss.str().c_str());
pcoh.output_diagram(out);
out.close();
return 0;
}
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