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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 (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/>.
*/
#ifndef PERMUTATION_TEST_H
#define PERMUTATION_TEST_H
//concretizations
#include <vector>
#include <iostream>
#include <cstdlib>
#include <algorithm>
#include <gudhi/read_persistence_from_file.h>
namespace Gudhi
{
namespace Gudhi_stat
{
//TODO change the reading procedures so that they accept the dimension value (by default std::nnumeric_limits<unsigned>::max().
template <typename Representation_of_persistence>
double permutation_test( const std::vector<Representation_of_persistence*>& data_1 , const std::vector<Representation_of_persistence*>& data_2 , size_t number_of_permutations , double exponent = 1 )
{
bool dbg = false;
try
{
Representation_of_persistence av_1;// = new Representation_of_persistence;
av_1.compute_average( data_1 );
Representation_of_persistence av_2;// = new Representation_of_persistence;
av_2.compute_average( data_2 );
double initial_distance = av_1.distance( av_2 , exponent );
double counter = 0;
//TODO -- TBB. QUestion, why it uses memory. Where is the leak??
for ( size_t i = 0 ; i != number_of_permutations ; ++i )
{
std::vector<Representation_of_persistence*> all_data;
all_data.insert(all_data.end() , data_1.begin() , data_1.end() );
all_data.insert(all_data.end() , data_2.begin() , data_2.end() );
std::random_shuffle( all_data.begin() , all_data.end() );
std::vector<Representation_of_persistence*> first_part(&all_data[0],&all_data[data_1.size()]);
std::vector<Representation_of_persistence*> second_part(&all_data[data_1.size()],&all_data[all_data.size()]);
Representation_of_persistence av_1;// = new Representation_of_persistence;
Representation_of_persistence av_2;// = new Representation_of_persistence;
av_1.compute_average( first_part );
av_2.compute_average( second_part );
double distance_after_permutations = av_1.distance( av_2 , exponent );
//delete av_1;
//delete av_2;
if ( distance_after_permutations > initial_distance )++counter;
if ( dbg )
{
std::cerr << "Permutation number : " << i << std::endl;
std::cerr << "distance_after_permutations : " << distance_after_permutations << std::endl;
std::cerr << "initial_distance : " << initial_distance << std::endl;
std::cerr << "counter : " << counter << std::endl;
}
}
return counter / (double)number_of_permutations;
}
catch (...)
{
std::cout << "The data structure do not support the operations that are neccessay for a permutation test (averaging, distances) \n";
}
return 0;
}//permutation_test
}//Gudhi_stat
}//Gudhi
#endif
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