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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): Siargey Kachanovich
*
* 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/>.
*/
// #ifdef _DEBUG
// # define TBB_USE_THREADING_TOOL
// #endif
// #define BOOST_TEST_DYN_LINK
// #define BOOST_TEST_MODULE "test_choose_farthest_point"
//#include <boost/test/unit_test.hpp>
//#include <boost/mpl/list.hpp>
#include <gudhi/choose_by_farthest_point.h>
#include <vector>
#include <iterator>
#include <gudhi/Clock.h>
#include <CGAL/Epick_d.h>
typedef CGAL::Epick_d<CGAL::Dynamic_dimension_tag> K;
typedef typename K::FT FT;
typedef typename K::Point_d Point_d;
//BOOST_AUTO_TEST_CASE(test_choose_farthest_point)
int main() {
std::vector< Point_d > points, results, results2;
K k;
Clock t;
// Add grid points (810000 points)
for (FT i = 0; i < 30; i += 1.0)
for (FT j = 0; j < 30; j += 1.0)
for (FT k = 0; k < 30; k += 1.0)
for (FT l = 0; l < 30; l += 1.0)
points.push_back(Point_d(std::vector<FT>({i, j, k, l})));
unsigned final_size = 100, numeral = 1;
std::cout << "Test New Old\n";
while (final_size < 100001) {
std::cout << final_size << ": ";
results.clear();
t.begin();
Gudhi::subsampling::choose_by_farthest_point(k, points, final_size, 0, std::back_inserter(results));
t.end();
std::cout << t.num_seconds() << " s, ";
// std::cout << "New algorithm result:\n";
// for (auto p: results)
// std::cout << p << std::endl;
results2.clear();
t.begin();
Gudhi::subsampling::choose_by_farthest_point_old(k, points, final_size, 0, std::back_inserter(results2));
t.end();
std::cout << t.num_seconds() << " s" << std::endl;
// std::cout << "Old algorithm result:\n";
// for (auto p: results2)
// std::cout << p << std::endl;
assert(results.size() == final_size);
assert(results2.size() == final_size);
assert(results == results2);
switch (numeral) {
case 1: numeral = 2; final_size *= 2; break;
case 2: numeral = 5; final_size = final_size/2*5; break;
case 5: numeral = 1; final_size *= 2; break;
default: assert(false);
}
}
}
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