Changeset 16126 for branches/2925_AutoDiffForDynamicalModels

Timestamp:

09/06/18 13:27:50 (6 years ago)

Author:

lkammere

Message:

#2925: added constants values to tree in result view and minor bugfix when initializing problem.

Location:

branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Problems.DynamicalSystemsModelling/3.3

Files:

• HeuristicLab.Problems.DynamicalSystemsModelling-3.3.csproj (modified) (1 diff)
• Problem.cs (modified) (7 diffs)

branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Problems.DynamicalSystemsModelling/3.3/HeuristicLab.Problems.DynamicalSystemsModelling-3.3.csproj

@@ -180 +180 @@
       <Private>False</Private>
     </ProjectReference>
+    <ProjectReference Include="..\..\HeuristicLab.Problems.DataAnalysis.Symbolic\3.4\HeuristicLab.Problems.DataAnalysis.Symbolic-3.4.csproj">
+      <Project>{3D28463F-EC96-4D82-AFEE-38BE91A0CA00}</Project>
+      <Name>HeuristicLab.Problems.DataAnalysis.Symbolic-3.4</Name>
+    </ProjectReference>
     <ProjectReference Include="..\..\HeuristicLab.Problems.DataAnalysis\3.4\HeuristicLab.Problems.DataAnalysis-3.4.csproj">
       <Project>{DF87C13E-A889-46FF-8153-66DCAA8C5674}</Project>

branches/2925_AutoDiffForDynamicalModels/HeuristicLab.Problems.DynamicalSystemsModelling/3.3/Problem.cs

@@ -34 +34 @@
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
 using HeuristicLab.Problems.DataAnalysis;
+using HeuristicLab.Problems.DataAnalysis.Symbolic;
 using HeuristicLab.Problems.Instances;
 
@@ -248 +249 @@
         alglib.minlbfgscreate(Math.Min(theta.Length, 5), theta, out state);
         alglib.minlbfgssetcond(state, 0.0, 0.0, 0.0, MaximumParameterOptimizationIterations);
-        alglib.minlbfgsoptimize(state, EvaluateObjectiveAndGradient, null, 
+        alglib.minlbfgsoptimize(state, EvaluateObjectiveAndGradient, null,
           new object[] { trees, targetVars, problemData, nodeIdx, targetValues, rows, NumericIntegrationSteps, latentVariables }); //TODO: create a type
         alglib.minlbfgsresults(state, out optTheta, out report);
@@ -284 +285 @@
       double[] grad = new double[optTheta.Length];
       double optQuality = double.NaN;
-      EvaluateObjectiveAndGradient(optTheta, ref optQuality, grad, 
+      EvaluateObjectiveAndGradient(optTheta, ref optQuality, grad,
         new object[] { trees, targetVars, problemData, nodeIdx, targetValues, rows, NumericIntegrationSteps, latentVariables });
       if (double.IsNaN(optQuality) || double.IsInfinity(optQuality)) return 10E6; // return a large value (TODO: be consistent by using NMSE)
@@ -383 +384 @@
        trainingRows,
        nodeIdx,
-       optTheta, 
+       optTheta,
        NumericIntegrationSteps).ToArray();
 
@@ -407 +408 @@
        testRows,
        nodeIdx,
-       optTheta, 
+       optTheta,
        NumericIntegrationSteps).ToArray();
 
@@ -422 +423 @@
       results["Prediction (training)"].Value = trainingList.AsReadOnly();
       results["Prediction (test)"].Value = testList.AsReadOnly();
-      results["Models"].Value = new ItemList<ISymbolicExpressionTree>(trees).AsReadOnly(); // TODO: simplify trees 
+
+      var modelList = new ItemList<ISymbolicExpressionTree>();
+      foreach (var tree in trees) {
+        var shownTree = (ISymbolicExpressionTree)tree.Clone();
+        var constantsNodeOrig = tree.IterateNodesPrefix().Where(IsConstantNode);
+        var constantsNodeShown = shownTree.IterateNodesPrefix().Where(IsConstantNode);
+
+        foreach (var n in constantsNodeOrig.Zip(constantsNodeShown, (original, shown) => new { original, shown })) {
+          double constantsVal = optTheta[nodeIdx[n.original]];
+
+          ConstantTreeNode replacementNode = new ConstantTreeNode(new Constant()) { Value = constantsVal };
+
+          var parentNode = n.shown.Parent;
+          int replacementIndex = parentNode.IndexOfSubtree(n.shown);
+          parentNode.RemoveSubtree(replacementIndex);
+          parentNode.InsertSubtree(replacementIndex, replacementNode);
+        }
+        // TODO: simplify trees
+
+        modelList.Add(shownTree);
+      }
+      results["Models"].Value = modelList.AsReadOnly();
     }
 
@@ -613 +635 @@
     private void OnProblemDataChanged() {
       UpdateTargetVariables();        // implicitly updates other dependent parameters
-
+      UpdateGrammarAndEncoding();
       var handler = ProblemDataChanged;
       if (handler != null) handler(this, EventArgs.Empty);