public candidate ChooseAndApplyCarboxOptionUsingEstimator(candidate cand, Computation cpt, MessageClient clt, string runDir, int epoch)
{
option bestOpt = null;
var bestProperty = Double.NegativeInfinity;
var options = GetCarboxylOptions(cand);
foreach (var opt in options)
{
var evalcand = CopyAndApplyOption(opt, cand, true);
var mol = OBFunctions.designgraphtomol(evalcand.graph);
var linkerName = AbstractAlgorithm.GetLinkerName(evalcand) + "-E" + epoch.ToString();
var coeff = Path.Combine(runDir, "data", "linker" + linkerName + ".coeff");
var lmpdat = Path.Combine(runDir, "data", "linker" + linkerName + ".lmpdat");
Converter.moltoUFF(OBFunctions.designgraphtomol(evalcand.graph), coeff, lmpdat, false, 100);
cpt.CalculateFeature(linkerName);
var properpty = Convert.ToDouble(clt.SendMessage("[Predict]" + " " + linkerName));
if (properpty > bestProperty)
{
bestProperty = properpty;
bestOpt = opt;
}
}
Console.WriteLine("Best {0}", bestProperty);
return(bestOpt == null ? null : CopyAndApplyOption(bestOpt, cand, true));
}
public BanditNode(Mcts parent, candidate cand, double transitionReward)
{
_parent = parent; // TODO transfer old tree
Cand = cand;
TransitionReward = transitionReward;
// AbsoluteReward = _parent.Evaluate(cand);
AbsoluteReward = 0;
Options = AbstractAlgorithm.GetAvailableOptions(cand);
Children = new Dictionary <candidate, NodeCountTuple> [Options.Count];
for (var i = 0; i < Children.Length; i++)
{
Children[i] = new Dictionary <candidate, NodeCountTuple>();
}
// Bandit = new EGreedyBandit(Options.Count, .5); // TODO only track best and how to get there? credit
Bandit = new UCTBandit(Options.Count);
}