void kmeans::update_clusters(const dataset & p_centers, cluster_sequence & p_clusters) {
const dataset & data = *m_ptr_data;
p_clusters.clear();
p_clusters.resize(p_centers.size());
/* fill clusters again in line with centers. */
if (m_ptr_indexes->empty()) {
std::vector<std::size_t> winners(data.size(), 0);
parallel_for(std::size_t(0), data.size(), [this, &p_centers, &winners](std::size_t p_index) {
assign_point_to_cluster(p_index, p_centers, winners);
});
for (std::size_t index_point = 0; index_point < winners.size(); index_point++) {
const std::size_t suitable_index_cluster = winners[index_point];
p_clusters[suitable_index_cluster].push_back(index_point);
}
}
else {
/* This part of code is used by X-Means and in case of parallel implementation of this part in scope of X-Means
performance is slightly reduced. Experiments has been performed our implementation and Intel TBB library.
But in K-Means case only - it works perfectly and increase performance. */
std::vector<std::size_t> winners(data.size(), 0);
parallel_for_each(*m_ptr_indexes, [this, &p_centers, &winners](std::size_t p_index) {
assign_point_to_cluster(p_index, p_centers, winners);
});
for (std::size_t index_point : *m_ptr_indexes) {
const std::size_t suitable_index_cluster = winners[index_point];
p_clusters[suitable_index_cluster].push_back(index_point);
}
}
erase_empty_clusters(p_clusters);
}
void testAdvanceToEnd(Quackle::Game &game)
{
UVcout << "now advancing to end..." << endl;
game.advanceToNoncomputerPlayer();
UVcout << game.currentPosition();
Quackle::PlayerList winners(game.currentPosition().leadingPlayers());
for (Quackle::PlayerList::const_iterator it = winners.begin(); it != winners.end(); ++it)
UVcout << *it << " wins!!" << endl;
}
/** Creates 2 groups: one from winners and one from loosers
*/
QList< Group* > SwissGroup::split( ) const
{
if ( _matches.count() < 2 ) { // nothing to split
return QList< Group* >();
}
QList< Group* > ret;
PlayerList w = winners(), l = loosers();
// number of winnders and loosers can be non-even, when group consists,
// for example, from 6 persons. We need to add 'bye' players
if ( w.count() & 1 ) w << byePlayer;
if ( l.count() & 1 ) l << byePlayer;
qDebug() << "Winners:";
for ( int i = 0; i < w.count(); i ++ ) {
qDebug() << w.at( i ).name();
}
qDebug() << "Loosers:";
for ( int i = 0; i < l.count(); i ++ ) {
qDebug() << l.at( i ).name();
}
// winners group
if ( !isPlayerListByed( w ) ) {
ret << new SwissGroup( _fromPlace, _stage + 1, w );
}
// loosers group
if ( !isPlayerListByed( l ) ) {
ret << new SwissGroup( _fromPlace + _players.count() / 2,
_stage + 1, l );
}
foreach( Group *g, ret ) {
const TournAlgo *a = _tournData->algo();
Q_CHECK_PTR( a );
g->setTournData( _tournData );
g->setQualif( isQualif() );
dynamic_cast<SwissGroup*>(g)->permuteMatches( a->breakAlgo() );
// if there is at least one bye player, we should notify that
// at least one game is fakely played.
if ( g->const_players().contains( byePlayer ) ) {
_tournData->groupChanged( g );
}
}
return ret;
}
