//private static Mutex sendMessageMutex = new Mutex();
public DifferentCarbox(GlobalSettings settings) : base(settings)
{
RequireSeed = true;
RequiredNumRuleSets = 1;
AutoPlay = true;
Seed = new candidate(OBFunctions.tagconvexhullpoints(settings.seed), settings.numOfRuleSets);
_runDirectory = Path.Combine(settings.OutputDirAbs, "RandomRuleApplication", CARBOXTYPE);
if (Directory.Exists(_runDirectory))
{
Directory.Delete(_runDirectory, true);
}
Directory.CreateDirectory(_runDirectory);
jobBuffer = new JobBuffer(_runDirectory);
var learnDirectory = Path.Combine(settings.OutputDirAbs, "morfLearn");
computation = new Computation(_runDirectory, learnDirectory, "point", "stiff");
writer = new StreamWriter(Path.Combine(_runDirectory, CARBOXTYPE + ".txt"));
System.Random rnd = new System.Random();
var port = rnd.Next(1, 65535);
//port = 9999;
server = new LearningServer(learnDirectory, port, _runDirectory);
client = new MessageClient(port);
}
/// <summary>
/// Clean way to minimize a graph.
/// </summary>
private designGraph Minimize(designGraph graph)
{
var mol = QuickMinimization(OBFunctions.designgraphtomol(graph), IODir + "rank" + ".lmpdat",
IODir + "rank" + ".coeff", false, 0);
OBFunctions.updatepositions(graph, mol);
return(OBFunctions.tagconvexhullpoints(graph));
}
/// <summary>
/// Apply the option to the candidate and store the agent's evaluation.
/// </summary>
public void ApplyOption(option opt, candidate cand, bool doMinimize)
{
cand.graph.globalVariables.Add(cand.f0); // track fitness values of previous states
opt.apply(cand.graph, null);
cand.addToRecipe(opt);
if (doMinimize)
{
cand.graph = Minimize(cand.graph);
}
cand.graph = OBFunctions.tagconvexhullpoints(cand.graph);
}
public RandomBaseline(GlobalSettings settings) : base(settings)
{
RequireSeed = true;
RequiredNumRuleSets = 1;
AutoPlay = true;
Seed = new candidate(OBFunctions.tagconvexhullpoints(settings.seed), settings.numOfRuleSets);
_runDirectory = Path.Combine(settings.OutputDirAbs, "RandomBaseline");
if (Directory.Exists(_runDirectory))
{
Directory.Delete(_runDirectory, true);
}
Directory.CreateDirectory(_runDirectory);
var learnDirectory = Path.Combine(settings.OutputDirAbs, "morfLearn");
computation = new Computation(_runDirectory, learnDirectory, "point", "stiff");
writer = new StreamWriter(Path.Combine(_runDirectory, "RandomBaseline.txt"));
jobBuffer = new JobBuffer(_runDirectory);
agent = new Algorithms.Random(settings);
}
/// <inheritdoc />
/// <summary>
/// Initializes SearchProcess properties.
/// </summary>
public Bfs(GlobalSettings settings) : base(settings)
{
RequireSeed = true;
RequiredNumRuleSets = 1;
AutoPlay = true;
_runDirectory = Path.Combine(settings.OutputDirAbs, "BFS");
if (!Directory.Exists(_runDirectory))
{
Directory.CreateDirectory(_runDirectory);
}
Seed = new candidate(OBFunctions.tagconvexhullpoints(settings.seed), settings.numOfRuleSets);
QueueBFS = new Queue <BFSNode>();
allNode = new HashSet <string>();
allFinalCand = new HashSet <string>();
nodeCnt = 0;
candCnt = 0;
nodeInfoWriter = new StreamWriter(_runDirectory + "/nodeInfo.txt");
nodeInfoWriter.WriteLine("SMILE,Depth");
candInfoWriter = new StreamWriter(_runDirectory + "/candInfo.txt");
candInfoWriter.WriteLine("SMILE,Depth");
}