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random_selection.hpp
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random_selection.hpp
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//| This file is a part of the ERC ResiBots project.
//| Copyright 2015, ISIR / Universite Pierre et Marie Curie (UPMC)
//| Main contributor(s): Jean-Baptiste Mouret, [email protected]
//| Antoine Cully, [email protected]
//|
//| This software is governed by the CeCILL license under French law
//| and abiding by the rules of distribution of free software. You
//| can use, modify and/ or redistribute the software under the terms
//| of the CeCILL license as circulated by CEA, CNRS and INRIA at the
//| following URL "http://www.cecill.info".
//|
//| As a counterpart to the access to the source code and rights to
//| copy, modify and redistribute granted by the license, users are
//| provided only with a limited warranty and the software's author,
//| the holder of the economic rights, and the successive licensors
//| have only limited liability.
//|
//| In this respect, the user's attention is drawn to the risks
//| associated with loading, using, modifying and/or developing or
//| reproducing the software by the user in light of its specific
//| status of free software, that may mean that it is complicated to
//| manipulate, and that also therefore means that it is reserved for
//| developers and experienced professionals having in-depth computer
//| knowledge. Users are therefore encouraged to load and test the
//| software's suitability as regards their requirements in conditions
//| enabling the security of their systems and/or data to be ensured
//| and, more generally, to use and operate it in the same conditions
//| as regards security.
//|
//| The fact that you are presently reading this means that you have
//| had knowledge of the CeCILL license and that you accept its terms.
#ifndef RANDOM_SELECTION_HPP_
#define RANDOM_SELECTION_HPP_
#include <tbb/blocked_range.h>
#include <tbb/parallel_reduce.h>
#include <bayesian_optimization/misc/rand.hpp>
namespace limbo {
namespace inner_optimization {
template <typename Params>
struct RandomSelection {
RandomSelection() {}
template <typename AcquisitionFunction>
float operator()(const AcquisitionFunction& acqui, Eigen::VectorXd& result) const
{
int indiv = misc::rand(Params::archiveparams::archive.size() - 1);
typedef typename Params::archiveparams::archive_t::const_iterator archive_it_t;
archive_it_t it = Params::archiveparams::archive.begin();
std::advance(it, indiv);
if (result.size() != it->first.size())
result = Eigen::VectorXd(it->first.size());
for (int i = 0; i < it->first.size(); i++)
result[i] = it->first[i];
return it->second.fit;
}
private:
};
}
}
#endif