Changeset 18220 for trunk/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters

Timestamp:

02/24/22 20:33:45 (2 years ago)

Author:

gkronber

Message:

#3136: reintegrated structure-template GP branch into trunk

Location:

trunk

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/DerivativeCalculator.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToAutoDiffTermConverter.cs (modified) (7 diffs)

trunk/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/DerivativeCalculator.cs

@@ -199 +199 @@
         var tanh = (ISymbolicExpressionTreeNode)branch.Clone();
         return Product(fxp, Subtract(CreateNumber(1.0), Square(tanh)));
+      }
+      if (branch.Symbol is SubFunctionSymbol) {
+        return Derive(branch.GetSubtree(0), variableName);
       }
       throw new NotSupportedException(string.Format("Symbol {0} is not supported.", branch.Symbol));
@@ -285 +288 @@
           !(n.Symbol is Cosine) &&
           !(n.Symbol is Tangent) &&
-          !(n.Symbol is StartSymbol)
+          !(n.Symbol is StartSymbol) &&
+          !(n.Symbol is SubFunctionSymbol)
         select n).Any();
       return !containsUnknownSymbol;

trunk/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/TreeToAutoDiffTermConverter.cs

@@ -106 +106 @@
       out ParametricFunctionGradient func_grad) {
 
+      return TryConvertToAutoDiff(tree, makeVariableWeightsVariable, addLinearScalingTerms, Enumerable.Empty<ISymbolicExpressionTreeNode>(),
+        out parameters, out initialParamValues, out func, out func_grad);
+    }
+
+    public static bool TryConvertToAutoDiff(ISymbolicExpressionTree tree, bool makeVariableWeightsVariable, bool addLinearScalingTerms, IEnumerable<ISymbolicExpressionTreeNode> excludedNodes,
+      out List<DataForVariable> parameters, out double[] initialParamValues,
+      out ParametricFunction func,
+      out ParametricFunctionGradient func_grad) {
+
       // use a transformator object which holds the state (variable list, parameter list, ...) for recursive transformation of the tree
-      var transformator = new TreeToAutoDiffTermConverter(makeVariableWeightsVariable, addLinearScalingTerms);
+      var transformator = new TreeToAutoDiffTermConverter(makeVariableWeightsVariable, addLinearScalingTerms, excludedNodes);
       AutoDiff.Term term;
       try {
@@ -134 +143 @@
     private readonly bool makeVariableWeightsVariable;
     private readonly bool addLinearScalingTerms;
-
-    private TreeToAutoDiffTermConverter(bool makeVariableWeightsVariable, bool addLinearScalingTerms) {
+    private readonly HashSet<ISymbolicExpressionTreeNode> excludedNodes;
+
+    private TreeToAutoDiffTermConverter(bool makeVariableWeightsVariable, bool addLinearScalingTerms, IEnumerable<ISymbolicExpressionTreeNode> excludedNodes) {
       this.makeVariableWeightsVariable = makeVariableWeightsVariable;
       this.addLinearScalingTerms = addLinearScalingTerms;
+      this.excludedNodes = new HashSet<ISymbolicExpressionTreeNode>(excludedNodes);
+
       this.initialParamValues = new List<double>();
       this.parameters = new Dictionary<DataForVariable, AutoDiff.Variable>();
@@ -161 +173 @@
         var par = FindOrCreateParameter(parameters, varNode.VariableName, varValue);
 
-        if (makeVariableWeightsVariable) {
+        if (makeVariableWeightsVariable && !excludedNodes.Contains(node)) {
           initialParamValues.Add(varNode.Weight);
           var w = new AutoDiff.Variable();
@@ -176 +188 @@
           var par = FindOrCreateParameter(parameters, factorVarNode.VariableName, variableValue);
 
-          initialParamValues.Add(factorVarNode.GetValue(variableValue));
-          var wVar = new AutoDiff.Variable();
-          variables.Add(wVar);
-
-          products.Add(AutoDiff.TermBuilder.Product(wVar, par));
+          if (makeVariableWeightsVariable && !excludedNodes.Contains(node)) {
+            initialParamValues.Add(factorVarNode.GetValue(variableValue));
+            var wVar = new AutoDiff.Variable();
+            variables.Add(wVar);
+
+            products.Add(AutoDiff.TermBuilder.Product(wVar, par));
+          } else {
+            var weight = factorVarNode.GetValue(variableValue);
+            products.Add(weight * par);
+          }
+
         }
         return AutoDiff.TermBuilder.Sum(products);
@@ -188 +206 @@
         var par = FindOrCreateParameter(parameters, varNode.VariableName, string.Empty, varNode.Lag);
 
-        if (makeVariableWeightsVariable) {
+        if (makeVariableWeightsVariable && !excludedNodes.Contains(node)) {
           initialParamValues.Add(varNode.Weight);
           var w = new AutoDiff.Variable();
@@ -305 +323 @@
           return t * alpha + beta;
         } else return ConvertToAutoDiff(node.GetSubtree(0));
+      }
+      if (node.Symbol is SubFunctionSymbol) {
+        return ConvertToAutoDiff(node.GetSubtree(0));
       }
       throw new ConversionException();
@@ -353 +374 @@
           !(n.Symbol is Cube) &&
           !(n.Symbol is CubeRoot) &&
-          !(n.Symbol is Power)
+          !(n.Symbol is Power) &&
+          !(n.Symbol is SubFunctionSymbol)
         select n).Any();
       return !containsUnknownSymbol;