void apply(Ea& ea) {
size_t k = Params::nslc::k;
// merge the population and the archive in a single archive
pop_t archive = _archive;
archive.insert(archive.end(), ea.pop().begin(), ea.pop().end());
// compute the sparseness of each individual of the population
// and potentially add some of them to the archive
int added = 0;
for (size_t i = 0; i < ea.pop().size(); ++i) {
size_t nb_objs = ea.pop()[i]->fit().objs().size();
assert(nb_objs >= 2);
// sort
parallel::sort(archive.begin(), archive.end(),
nslc::_compare_dist_p<phen_t>(ea.pop()[i]));
// local competition score
int rank = k;
for (size_t j = 0; j < k; ++j)
if (ea.pop()[i]->fit().value() < archive[j]->fit().value())
rank--;
ea.pop()[i]->fit().set_obj(0, rank);
// novelty
double n = 0.0;
for (size_t j = 0; j < k; ++j)
n += ea.pop()[i]->fit().dist(*archive[j]);
ea.pop()[i]->fit().set_obj(1, n);
// add to the archive
if (n > _rho_min
|| misc::rand<float>() < Params::nslc::add_to_archive_prob) {
_archive.push_back(ea.pop()[i]);
_not_added = 0;
++added;
} else {
++_not_added;
}
} // end for all individuals
// update rho_min
if (_not_added > Params::nslc::stalled_tresh) { //2500
_rho_min *= 0.95;
_not_added = 0;
}
if (_archive.size() > Params::nslc::k
&& added > Params::nslc::adding_tresh) {//4
_rho_min *= 1.05f;
}
std::cout<<"archive size:"<<_archive.size()<<std::endl;
}
static void run_ea(int argc,
char **argv,
Ea& ea,
const typename Ea::phen_t::fit_t& fit_proto,
const boost::program_options::options_description& add_opts =
boost::program_options::options_description(),
bool init_rand = true) {
ea.set_fit_proto(fit_proto);
namespace po = boost::program_options;
std::cout<<"sferes2 version: "<<VERSION<<std::endl;
if (init_rand) {
time_t t = time(0) + ::getpid();
std::cout<<"seed: " << t << std::endl;
srand(t);
}
po::options_description desc("Allowed sferes2 options");
desc.add(add_opts);
desc.add_options()
("help,h", "produce help message")
("stat,s", po::value<int>(), "statistic number")
("out,o", po::value<std::string>(), "output file")
("number,n", po::value<int>(), "number in stat")
("load,l", po::value<std::string>(), "load a result file")
("verbose,v", po::value<std::vector<std::string> >()->multitoken(),
"verbose output, available default streams : all, ea, fit, phen, trace")
;
po::variables_map vm;
po::store(po::parse_command_line(argc, argv, desc), vm);
po::notify(vm);
if (vm.count("help")) {
std::cout << desc << std::endl;
return;
}
if (vm.count("verbose")) {
dbg::init();
std::vector<std::string> streams =
vm["verbose"].as<std::vector<std::string> >();
attach_ostream(dbg::warning, std::cout);
attach_ostream(dbg::error, std::cerr);
attach_ostream(dbg::info, std::cout);
bool all = std::find(streams.begin(), streams.end(), "all") != streams.end();
bool trace = std::find(streams.begin(), streams.end(), "trace") != streams.end();
if (all) {
streams.push_back("ea");
streams.push_back("fit");
streams.push_back("phen");
streams.push_back("eval");
}
BOOST_FOREACH(const std::string& s, streams) {
dbg::enable(dbg::all, s.c_str(), true);
dbg::attach_ostream(dbg::info, s.c_str(), std::cout);
if (trace)
dbg::attach_ostream(dbg::tracing, s.c_str(), std::cout);
}
void apply(Ea& ea)
{
//std::cout<<"insidenov"<<std::endl;
// parallel compute
parallel::init();
parallel::p_for(parallel::range_t(0, ea.pop().size()),
novelty::_parallel_behavior_nov<typename Ea::phen_t, archive_t, Params>(ea.pop(),_archive));
//std::cout<<"paralleldone"<<std::endl;
//Update archive
int obj_num = 1;
int bestindiv = -1;
float max_sparse = -1.0;
for(size_t i = 0; i < ea.pop().size(); ++i) {
float sparse = ea.pop()[i]->fit().obj(obj_num);
if(max_sparse < sparse) {
max_sparse = sparse;
bestindiv = i;
}
}
if(bestindiv!=-1)
_archive.push_back(ea.pop()[bestindiv]->fit().pos_bd);
}
void apply(Ea& ea)
{
// boost::accumulators::accumulator_set<double, boost::accumulators::stats<boost::accumulators::tag::max> > acc_max;
// boost::accumulators::accumulator_set<double, boost::accumulators::stats<boost::accumulators::tag::min> > acc_min;
SFERES_CONST size_t k = Params::novelty::k;
// merge the population and the archive in a single archive
pop_t archive = _archive;
archive.insert(archive.end(), ea.pop().begin(), ea.pop().end());
// we compute all the distances from pop(i) to archive(j) and store them
Eigen::MatrixXf distances(ea.pop().size(), archive.size());
novelty::_distance_f<Phen> f(ea.pop(), archive, distances);
parallel::init();
parallel::p_for(parallel::range_t(0, ea.pop().size()), f);
// compute the sparseness of each individual of the population
// and potentially add to the archive
int added = 0;
for (size_t i = 0; i < ea.pop().size(); ++i) {
size_t nb_objs = ea.pop()[i]->fit().objs().size();
Eigen::VectorXf vd = distances.row(i);
// Get the k-nearest neighbors
double n = 0.0;
std::partial_sort(vd.data(),
vd.data() + k,
vd.data() + vd.size());
// Sum up the total of distances from k-nearest neighbors
// This is the novelty score
n = vd.head<k>().sum() / k;
// Set the novelty score to the last objective in the array of objectives
ea.pop()[i]->fit().set_obj(nb_objs - 1, n);
// std::cout << "rho = " << _rho_min << "; n = " << n << "\n";
// acc_max(n);
// acc_min(n);
// Check if this individual is already in the archive
if (!in_archive_already(ea.pop()[i]->id()) &&
(n > _rho_min // Check if the novelty score passes the threshold
|| misc::rand<float>() < Params::novelty::add_to_archive_prob))
{
// Add this individual to the permanent archive
_archive.push_back(ea.pop()[i]);
// Print this indiv just added
// std::cout << "----> n = " << n << "; label = " << ea.pop()[i]->fit().label() << "; score = " << ea.pop()[i]->fit().score() << "; id = " << ea.pop()[i]->id() <<"\n";
// std::cout << "----> n = " << n << "; label = " << "; id = " << ea.pop()[i]->id() <<"\n";
_not_added = 0;
++added;
} else {
// Do not add this individual to the archive
++_not_added;
}
} // end for all individuals
// update rho_min
if (_not_added > Params::novelty::stalled_tresh)//2500
{
_rho_min *= 0.95; // Lower rho_min
_not_added = 0; // After lowering the stalled threshold, we need to reset the _not_added count
}
if (_archive.size() > Params::novelty::k && added > Params::novelty::adding_tresh)//4
{
_rho_min *= 1.05f; // Increase rho_min
}
std::cout<<"a size:"<<_archive.size()<<std::endl;
// DEBUG
// std::cout << "a size:"<<_archive.size()
// << "; max: " << boost::accumulators::max(acc_max)
// << "; min: " << boost::accumulators::min(acc_min)
// << std::endl;
}
