Changeset 15142 for stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators

Timestamp:

07/06/17 11:12:18 (7 years ago)

Author:

gkronber

Message:

#2697: merged r14843 (resolving conflicts in csproj file for HL.Algorithms.DataAnalysis because MCTS has been removed)

File:

• stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs (modified) (5 diffs)

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/Evaluators/SymbolicRegressionConstantOptimizationEvaluator.cs

@@ -164 +164 @@
       // A dictionary is used to find parameters
       double[] initialConstants;
-      var parameters = new List<TreeToAutoDiffTermTransformator.DataForVariable>();
-
-      TreeToAutoDiffTermTransformator.ParametricFunction func;
-      TreeToAutoDiffTermTransformator.ParametricFunctionGradient func_grad;
-      if (!TreeToAutoDiffTermTransformator.TryTransformToAutoDiff(tree, updateVariableWeights, out parameters, out initialConstants, out func, out func_grad))
+      var parameters = new List<TreeToAutoDiffTermConverter.DataForVariable>();
+
+      TreeToAutoDiffTermConverter.ParametricFunction func;
+      TreeToAutoDiffTermConverter.ParametricFunctionGradient func_grad;
+      if (!TreeToAutoDiffTermConverter.TryConvertToAutoDiff(tree, updateVariableWeights, out parameters, out initialConstants, out func, out func_grad))
         throw new NotSupportedException("Could not optimize constants of symbolic expression tree due to not supported symbols used in the tree.");
       if (parameters.Count == 0) return 0.0; // gkronber: constant expressions always have a R² of 0.0 
@@ -175 +175 @@
 
       //extract inital constants
-      double[] c = new double[initialConstants.Length];
+      double[] c = new double[initialConstants.Length + 2];
       {
         c[0] = 0.0;
@@ -254 +254 @@
     }
 
-    private static alglib.ndimensional_pfunc CreatePFunc(TreeToAutoDiffTermTransformator.ParametricFunction func) {
+    private static alglib.ndimensional_pfunc CreatePFunc(TreeToAutoDiffTermConverter.ParametricFunction func) {
       return (double[] c, double[] x, ref double fx, object o) => {
         fx = func(c, x);
@@ -260 +260 @@
     }
 
-    private static alglib.ndimensional_pgrad CreatePGrad(TreeToAutoDiffTermTransformator.ParametricFunctionGradient func_grad) {
+    private static alglib.ndimensional_pgrad CreatePGrad(TreeToAutoDiffTermConverter.ParametricFunctionGradient func_grad) {
       return (double[] c, double[] x, ref double fx, double[] grad, object o) => {
         var tupel = func_grad(c, x);
@@ -268 +268 @@
     }
     public static bool CanOptimizeConstants(ISymbolicExpressionTree tree) {
-      return TreeToAutoDiffTermTransformator.IsCompatible(tree);
+      return TreeToAutoDiffTermConverter.IsCompatible(tree);
     }
   }