bool NeuralGas::trainOneEpoch(const std::vector<std::shared_ptr<wv::Point>>& points, double epsilon)
{
//create vector with order of iterating by points
std::vector<uint32_t> order;
for (uint32_t i = 0; i < points.size(); i++)
order.push_back(i);
std::random_shuffle(order.begin(), order.end());
uint32_t iteration = 1;
alr::AdaptLearnRateNeuralGas alrn(0, m_AdaptLearnRateWinner, m_AdaptLearnRateNotWinner);
double error_before = getErrorOnNeuron();
for (uint32_t i = 0; i < order.size(); i++)
{
findWinners(points[order[i]].get());
updateWeights(points[order[i]].get(), &alrn);
incrementEdgeAgeFromWinner();
updateEdgeWinSecWin();
deleteOldEdges();
if (iteration % m_Lambda == 0)
{
insertNode();
}
decreaseAllErrors();
iteration++;
}
double error_after = getErrorOnNeuron();
log_netw->info((boost::format("Error before %g. Error after %g") % error_before % error_after).str());
log_netw->info((boost::format("Network size: %d neurons") % m_Neurons.size()).str());
return (error_before - getErrorOnNeuron() > epsilon);
}
void GraphDrawingScene::notify(Subject *subject)
{
_graph = (Graph*)subject;
// get the last added nodes, only these nodes have to be linked with observers
addNewNodes(_graph->getLastAddedNodes());
// add all the new edges and link these with observers
addNewEdges(_graph->getLastAddedEdges());
// remove old nodes and edges
deleteOldNodes();
deleteOldEdges();
_cachedNode = NULL;
}
