Changeset 1216 for branches/CEDMA-Refactoring-Ticket419/HeuristicLab.CEDMA.Server/Dispatcher.cs

Timestamp:

02/12/09 14:05:33 (15 years ago)

Author:

gkronber

Message:

Improved dispatching mechanism. #419 (Refactor CEDMA plugins).

File:

• branches/CEDMA-Refactoring-Ticket419/HeuristicLab.CEDMA.Server/Dispatcher.cs (modified) (4 diffs)

branches/CEDMA-Refactoring-Ticket419/HeuristicLab.CEDMA.Server/Dispatcher.cs

@@ -57 +57 @@
       };
 
-      var dataSetBindings = store.Query("?DataSet <"+Ontology.PredicateInstanceOf.Uri+"> <"+Ontology.TypeDataSet.Uri+"> .");
+      var dataSetBindings = store.Query("?DataSet <" + Ontology.PredicateInstanceOf.Uri + "> <" + Ontology.TypeDataSet.Uri + "> .");
 
       // no datasets => do nothing
@@ -65 +65 @@
       // find and select all results for this dataset
       var dataSetEntity = (Entity)dataSetBindings.Last().Get("DataSet");
-      var targetVar = new HeuristicLab.CEDMA.DB.Interfaces.Variable("TargetVariable");
-      var modelVar = new HeuristicLab.CEDMA.DB.Interfaces.Variable("Model");
-      var modelMAPE = new HeuristicLab.CEDMA.DB.Interfaces.Variable("ModelMAPE");
-
-      var query = "<" + dataSetEntity.Uri + "> <" + Ontology.PredicateHasModel.Uri + "> ?Model ." + Environment.NewLine +
-        "?Model <" + Ontology.TargetVariable.Uri + "> ?TargetVariable ." + Environment.NewLine +
-        "?Model <" + Ontology.ValidationMeanAbsolutePercentageError.Uri + "> ?ModelMAPE .";
-
-
-
-      var bindings = store.Query(query);
       DataSet dataSet = new DataSet(store, dataSetEntity);
-      double[] utilization = new double[dataSet.Problem.AllowedTargetVariables.Count];
-      int i = 0;
-      int totalN = bindings.Count();
-      foreach (int targetVariable in dataSet.Problem.AllowedTargetVariables) {
-        var targetVarBindings = bindings.Where(x => (int)((Literal)x.Get("TargetVariable")).Value == targetVariable);
-        if (targetVarBindings.Count() == 0) {
-          utilization[i++] = double.PositiveInfinity;
-        } else {
-          double averageMape = targetVarBindings.Average(x => (double)((Literal)x.Get("ModelMAPE")).Value);
-          double n = targetVarBindings.Count();
-          utilization[i++] = -averageMape + Math.Sqrt(Math.Log(totalN) / n) * 0.1;
-        }
-      }
-      int[] idx = Enumerable.Range(0, utilization.Length).ToArray();
-      Array.Sort(utilization, idx);
-      int nConfigurations = utilization.Length;
-      for (int j = nConfigurations - 1; j > nConfigurations * 0.8; j--) {
-        int targetVariable = dataSet.Problem.AllowedTargetVariables[idx[j]];
-        IEngine engine = CreateEngine(dataSet.Problem, targetVariable);
-        if (engine != null) {
-          QueueJob(new Execution(dataSetEntity, engine, targetVariable));
-        }
+      Random random = new Random();
+      int targetVariable = dataSet.Problem.AllowedInputVariables[random.Next(0, dataSet.Problem.AllowedInputVariables.Count)];
+      string targetVariableName = dataSet.Problem.GetVariableName(targetVariable);
+      Execution exec = CreateExecution(dataSet.Problem, targetVariable);
+      if (exec != null) {
+        exec.DataSetEntity = dataSetEntity;
+        exec.TargetVariable = targetVariableName;
+        QueueJob(exec);
       }
     }
@@ -122 +97 @@
     }
 
-    private IEngine CreateEngine(Problem problem, int targetVariable) {
+    private Execution CreateExecution(Problem problem, int targetVariable) {
       switch (problem.LearningTask) {
         case LearningTask.Classification: return null;
         case LearningTask.Regression: {
-            return CreateStandardGp(problem, targetVariable).Engine;
+            return CreateStandardGpExecution(problem, targetVariable, 100, 10);
           }
         case LearningTask.TimeSeries: return null;
@@ -134 +109 @@
     }
 
-    private StandardGP CreateStandardGp(Problem problem, int targetVariable) {
+    private Execution CreateStandardGpExecution(Problem problem, int targetVariable, int maxTreeSize, int maxTreeHeight) {
       ProblemInjector probInjector = new ProblemInjector(problem);
       probInjector.TargetVariable = targetVariable;
       StandardGP sgp = new StandardGP();
       sgp.SetSeedRandomly = true;
-      sgp.MaxGenerations = 300;
-      sgp.PopulationSize = 10000;
+      sgp.MaxGenerations = 2;
+      sgp.PopulationSize = 100;
       sgp.Elites = 1;
       sgp.ProblemInjector = probInjector;
-      return sgp;
+      sgp.MaxTreeHeight = maxTreeHeight;
+      sgp.MaxTreeSize = maxTreeSize;
+      Execution exec = new Execution(sgp.Engine);
+      exec.Description = "StandardGP - Medium Complexity";
+      return exec;
     }
   }