Changeset 5275 for branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3

Timestamp:

01/11/11 15:03:46 (13 years ago)

Author:

gkronber

Message:

Merged changes from trunk to data analysis exploration branch and added fractional distance metric evaluator. #1142

Location:

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3

Files:

• HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis-3.3.csproj (modified) (2 diffs)
• Symbolic/Analyzer/ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs (modified) (2 diffs)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisEvaluator.cs (modified) (2 diffs)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisMahalanobisEvaluator.cs (modified) (1 diff)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisScaledNormalizedFractionalDistanceEvaluator.cs (added)
• Symbolic/Evaluators/SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.cs (modified) (1 diff)
• Symbolic/SingleObjectiveSymbolicTimeSeriesPrognosisProblem.cs (modified) (2 diffs)
• Symbolic/SymbolicTimeSeriesExpressionInterpreter.cs (modified) (1 diff)
• Symbolic/SymbolicTimeSeriesPrognosisGrammar.cs (modified) (2 diffs)
• Symbolic/SymbolicTimeSeriesPrognosisModel.cs (modified) (2 diffs)
• Symbolic/SymbolicTimeSeriesPrognosisProblem.cs (modified) (3 diffs)
• Symbolic/SymbolicTimeSeriesPrognosisSolution.cs (modified) (3 diffs)
• Symbolic/Symbols/DerivativeVariable.cs (modified) (2 diffs)
• Symbolic/Symbols/DerivativeVariableTreeNode.cs (modified) (2 diffs)
• Symbolic/Symbols/IntegratedVariable.cs (modified) (2 diffs)
• Symbolic/Symbols/IntegratedVariableTreeNode.cs (modified) (2 diffs)
• Symbolic/Symbols/MovingAverage.cs (modified) (2 diffs)
• Symbolic/Symbols/MovingAverageTreeNode.cs (modified) (2 diffs)

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis-3.3.csproj

@@ -92 +92 @@
   </PropertyGroup>
   <ItemGroup>
+    <Reference Include="HeuristicLab.Analysis-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Analysis-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Collections-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Collections-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Common-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Common-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Common.Resources-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Common.Resources-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Core-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Core-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Data-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Data-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Encodings.SymbolicExpressionTreeEncoding-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Encodings.SymbolicExpressionTreeEncoding-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Operators-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Operators-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Optimization-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Optimization-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Parameters-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Parameters-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Persistence-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Persistence-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.PluginInfrastructure-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.PluginInfrastructure-3.3.dll</HintPath>
+    </Reference>
+    <Reference Include="HeuristicLab.Random-3.3">
+      <HintPath>..\..\..\..\..\..\Program Files\HeuristicLab 3.3\HeuristicLab.Random-3.3.dll</HintPath>
+    </Reference>
     <Reference Include="System" />
     <Reference Include="System.Core">
@@ -109 +148 @@
     <Compile Include="HeuristicLabProblemsDataAnalysisMultiVariateTimeSeriesPrognosisPlugin.cs" />
     <Compile Include="Symbolic\Analyzer\ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs" />
+    <Compile Include="Symbolic\Evaluators\SymbolicTimeSeriesPrognosisScaledNormalizedFractionalDistanceEvaluator.cs" />
     <Compile Include="Symbolic\Evaluators\SymbolicTimeSeriesPrognosisEvaluator.cs" />
     <Compile Include="Symbolic\Evaluators\SymbolicTimeSeriesPrognosisMahalanobisEvaluator.cs">

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Analyzer/ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer.cs

@@ -222 +222 @@
     #endregion
 
+    [StorableConstructor]
+    protected ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer(bool deserializing) : base(deserializing) { }
+    protected ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer(ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer()
       : base() {
@@ -245 +250 @@
     }
 
-    [StorableConstructor]
-    private ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer(bool deserializing) : base(deserializing) { }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new ValidationBestScaledSymbolicTimeSeriesPrognosisSolutionAnalyzer(this, cloner);
+    }
     [StorableHook(Persistence.Default.CompositeSerializers.Storable.HookType.AfterDeserialization)]
-    private void Initialize() {
+    private void AfterDeserialization() {
       //if (!Parameters.ContainsKey("Evaluator")) {
       //  Parameters.Add(new LookupParameter<ISingleObjectiveSymbolicTimeSeriesPrognosisEvaluator>("Evaluator", ""));

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisEvaluator.cs

@@ -93 +93 @@
     }
     #endregion
-    #region
+    #region properties
     public IRandom Random {
       get { return RandomParameter.ActualValue; }
@@ -128 +128 @@
     }
     #endregion
-
+    [StorableConstructor]
+    protected SymbolicTimeSeriesPrognosisEvaluator(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesPrognosisEvaluator(SymbolicTimeSeriesPrognosisEvaluator original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public SymbolicTimeSeriesPrognosisEvaluator()
       : base() {

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisMahalanobisEvaluator.cs

@@ -45 +45 @@
   public class SymbolicTimeSeriesPrognosisMahalanobisEvaluator : SymbolicTimeSeriesPrognosisEvaluator {
 
+    [StorableConstructor]
+    protected SymbolicTimeSeriesPrognosisMahalanobisEvaluator(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesPrognosisMahalanobisEvaluator(SymbolicTimeSeriesPrognosisMahalanobisEvaluator original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public SymbolicTimeSeriesPrognosisMahalanobisEvaluator()
       : base() {
     }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesPrognosisMahalanobisEvaluator(this, cloner);
+    }
     public override double Evaluate(SymbolicExpressionTree tree, MultiVariateDataAnalysisProblemData problemData, ISymbolicTimeSeriesExpressionInterpreter interpreter, IEnumerable<int> rows, int predictionHorizon, DoubleArray lowerEstimationLimit, DoubleArray upperEstimationLimit) {
       return Calculate(tree, problemData, interpreter, rows, predictionHorizon, lowerEstimationLimit, upperEstimationLimit);

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Evaluators/SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator.cs

@@ -44 +44 @@
   public class SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator : SymbolicTimeSeriesPrognosisEvaluator {
 
+    [StorableConstructor]
+    protected SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator(SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator()
       : base() {
     }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesPrognosisScaledNormalizedMseEvaluator(this, cloner);
+    }
     public override double Evaluate(SymbolicExpressionTree tree, MultiVariateDataAnalysisProblemData problemData, ISymbolicTimeSeriesExpressionInterpreter interpreter, IEnumerable<int> rows, int predictionHorizon, DoubleArray lowerEstimationLimit, DoubleArray upperEstimationLimit) {
       return Calculate(tree, problemData, interpreter, rows, predictionHorizon, lowerEstimationLimit, upperEstimationLimit);

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SingleObjectiveSymbolicTimeSeriesPrognosisProblem.cs

@@ -87 +87 @@
     [StorableConstructor]
     protected SingleObjectiveSymbolicTimeSeriesPrognosisProblem(bool deserializing) : base(deserializing) { }
+    protected SingleObjectiveSymbolicTimeSeriesPrognosisProblem(SingleObjectiveSymbolicTimeSeriesPrognosisProblem original, Cloner cloner)
+      : base(original, cloner) {
+        AttachEventHandlers();
+    }
     public SingleObjectiveSymbolicTimeSeriesPrognosisProblem()
       : base() {
@@ -102 +106 @@
 
     [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserializationHook() {
+    private void AfterDeserialization() {
       AttachEventHandlers();
     }
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      SingleObjectiveSymbolicTimeSeriesPrognosisProblem clone = (SingleObjectiveSymbolicTimeSeriesPrognosisProblem)base.Clone(cloner);
-      clone.AttachEventHandlers();
-      return clone;
+      return new SingleObjectiveSymbolicTimeSeriesPrognosisProblem(this, cloner);
     }
 

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SymbolicTimeSeriesExpressionInterpreter.cs

@@ -116 +116 @@
       get { return false; }
     }
-
+    [StorableConstructor]
+    protected SymbolicTimeSeriesExpressionInterpreter(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesExpressionInterpreter(SymbolicTimeSeriesExpressionInterpreter original, Cloner cloner)
+      : base(original, cloner) {
+    }
     public SymbolicTimeSeriesExpressionInterpreter()
       : base() {
+    }
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesExpressionInterpreter(this, cloner);
     }
     #region ITimeSeriesExpressionInterpreter Members

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SymbolicTimeSeriesPrognosisGrammar.cs

@@ -38 +38 @@
     // for persistence
     private SymbolicTimeSeriesPrognosisGrammar() : this(1) { }
-
+    [StorableConstructor]
+    protected SymbolicTimeSeriesPrognosisGrammar(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesPrognosisGrammar(SymbolicTimeSeriesPrognosisGrammar original, Cloner cloner)
+      : base(original, cloner) {
+        dimension = original.dimension;
+    }
     public SymbolicTimeSeriesPrognosisGrammar(int dimension)
       : base() {
       this.dimension = dimension;
       Initialize();
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesPrognosisGrammar(this, cloner);
     }
 
@@ -129 +138 @@
           }
       }
-    }
-
-    public override IDeepCloneable Clone(Cloner cloner) {
-      SymbolicTimeSeriesPrognosisGrammar clone = (SymbolicTimeSeriesPrognosisGrammar)base.Clone(cloner);
-      clone.dimension = this.dimension;
-      return clone;
-    }
+    }   
   }
 }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SymbolicTimeSeriesPrognosisModel.cs

@@ -47 +47 @@
     [StorableConstructor]
     protected SymbolicTimeSeriesPrognosisModel(bool deserializing) : base(deserializing) { }
-
+    protected SymbolicTimeSeriesPrognosisModel(SymbolicTimeSeriesPrognosisModel original, Cloner cloner)
+      : base(original, cloner) {
+        tree = cloner.Clone(original.tree);
+        interpreter = cloner.Clone(original.interpreter);
+    }
     public SymbolicTimeSeriesPrognosisModel() { }
-
     public SymbolicTimeSeriesPrognosisModel(ISymbolicTimeSeriesExpressionInterpreter interpreter, SymbolicExpressionTree tree) {
       this.tree = tree;
       this.interpreter = interpreter;
 
+    }
+
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesPrognosisModel(this, cloner);
     }
 
@@ -70 +77 @@
     #endregion
 
-    public override IDeepCloneable Clone(Cloner cloner) {
-      SymbolicTimeSeriesPrognosisModel clone = (SymbolicTimeSeriesPrognosisModel)base.Clone(cloner);
-      clone.tree = (SymbolicExpressionTree)cloner.Clone(tree);
-      clone.interpreter = (ISymbolicTimeSeriesExpressionInterpreter)cloner.Clone(interpreter);
-      return clone;
-    }
   }
 }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SymbolicTimeSeriesPrognosisProblem.cs

@@ -161 +161 @@
     [StorableConstructor]
     protected SymbolicTimeSeriesPrognosisProblem(bool deserializing) : base(deserializing) { }
+    protected SymbolicTimeSeriesPrognosisProblem(SymbolicTimeSeriesPrognosisProblem original, Cloner cloner)
+      : base(original, cloner) {
+      operators = original.operators.Select(x => (IOperator)cloner.Clone(x)).ToList();
+      grammar = (SymbolicTimeSeriesPrognosisGrammar)cloner.Clone(original.grammar);
+      RegisterParameterEvents();
+      RegisterParameterValueEvents();
+    }
     public SymbolicTimeSeriesPrognosisProblem()
       : base() {
@@ -188 +195 @@
 
     [StorableHook(HookType.AfterDeserialization)]
-    private void AfterDeserializationHook() {
+    private void AfterDeserialization() {
       // BackwardsCompatibility3.3
       #region Backwards compatible code (remove with 3.4)
@@ -198 +205 @@
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      SymbolicTimeSeriesPrognosisProblem clone = (SymbolicTimeSeriesPrognosisProblem)base.Clone(cloner);
-      clone.operators = operators.Select(x => (IOperator)cloner.Clone(x)).ToList();
-      clone.grammar = (SymbolicTimeSeriesPrognosisGrammar)cloner.Clone(grammar);
-      clone.RegisterParameterEvents();
-      clone.RegisterParameterValueEvents();
-      return clone;
+      return new SymbolicTimeSeriesPrognosisProblem(this, cloner);
     }
 

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/SymbolicTimeSeriesPrognosisSolution.cs

@@ -54 +54 @@
     [StorableConstructor]
     protected SymbolicTimeSeriesPrognosisSolution(bool deserializing) : base(deserializing) { }
-
+    protected SymbolicTimeSeriesPrognosisSolution(SymbolicTimeSeriesPrognosisSolution original, Cloner cloner)
+      : base(original, cloner) {
+      problemData = (MultiVariateDataAnalysisProblemData)cloner.Clone(original.problemData);
+      model = (SymbolicTimeSeriesPrognosisModel)cloner.Clone(original.model);
+      horizon = original.horizon;
+      conditionalEvaluationVariable = original.conditionalEvaluationVariable;
+      lowerEstimationLimit = (double[])original.lowerEstimationLimit.Clone();
+      upperEstimationLimit = (double[])original.upperEstimationLimit.Clone();
+    }
     public SymbolicTimeSeriesPrognosisSolution() {
       horizon = 1;
@@ -68 +76 @@
       this.upperEstimationLimit = (double[])upperEstimationLimit.Clone();
     }
-
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new SymbolicTimeSeriesPrognosisSolution(this, cloner);
+    }
     [StorableHook(HookType.AfterDeserialization)]
-    private void Initialize() {
+    private void AfterDeserialization() {
       if (problemData != null)
         RegisterProblemDataEvents();
@@ -206 +216 @@
 
 
-    public override IDeepCloneable Clone(Cloner cloner) {
-      SymbolicTimeSeriesPrognosisSolution clone = (SymbolicTimeSeriesPrognosisSolution)base.Clone(cloner);
-      clone.problemData = (MultiVariateDataAnalysisProblemData)cloner.Clone(problemData);
-      clone.model = (SymbolicTimeSeriesPrognosisModel)cloner.Clone(model);
-      clone.horizon = horizon;
-      clone.conditionalEvaluationVariable = conditionalEvaluationVariable;
-      clone.lowerEstimationLimit = (double[])lowerEstimationLimit.Clone();
-      clone.upperEstimationLimit = (double[])upperEstimationLimit.Clone();
-      return clone;
-    }
 
     private IEnumerable<double[]> ApplyEstimationLimits(IEnumerable<double[]> values) {

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/DerivativeVariable.cs

@@ -47 +47 @@
       set { maxLag = value; }
     }
+    [StorableConstructor]
+    protected DerivativeVariable(bool deserializing) : base(deserializing) { }
+    protected DerivativeVariable(DerivativeVariable original, Cloner cloner)
+      : base(original, cloner) {
+        minLag = original.minLag;
+        maxLag = original.maxLag;
+    }
     public DerivativeVariable()
       : base("DerivativeVariable", "Represents an differentiated variable value with a time offset.") {
@@ -57 +64 @@
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      DerivativeVariable clone = (DerivativeVariable)base.Clone(cloner);
-      clone.minLag = minLag;
-      clone.maxLag = maxLag;
-      return clone;
+      return new DerivativeVariable(this, cloner);
     }
   }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/DerivativeVariableTreeNode.cs

@@ -44 +44 @@
     private DerivativeVariableTreeNode() { }
 
-    // copy constructor
-    private DerivativeVariableTreeNode(DerivativeVariableTreeNode original)
-      : base(original) {
-      lag = original.lag;
+    [StorableConstructor]
+    protected DerivativeVariableTreeNode(bool deserializing) : base(deserializing) { }
+    protected DerivativeVariableTreeNode(DerivativeVariableTreeNode original, Cloner cloner)
+      : base(original, cloner) {
+        lag = original.lag;
     }
 
@@ -69 +70 @@
 
 
-    public override object Clone() {
-      return new DerivativeVariableTreeNode(this);
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new DerivativeVariableTreeNode(this, cloner);
     }
 

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/IntegratedVariable.cs

@@ -47 +47 @@
       set { maxLag = value; }
     }
+    [StorableConstructor]
+    protected IntegratedVariable(bool deserializing) : base(deserializing) { }
+    protected IntegratedVariable(IntegratedVariable original, Cloner cloner)
+      : base(original, cloner) {
+        minLag = original.minLag;
+        maxLag = original.maxLag;
+    }
     public IntegratedVariable()
       : base("IntegratedVariable", "Represents an integrated variable value with a time offset.") {
@@ -57 +64 @@
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      IntegratedVariable clone = (IntegratedVariable)base.Clone(cloner);
-      clone.minLag = minLag;
-      clone.maxLag = maxLag;
-      return clone;
+      return new IntegratedVariable(this, cloner);
     }
   }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/IntegratedVariableTreeNode.cs

@@ -50 +50 @@
 
     private IntegratedVariableTreeNode() { }
-
-    // copy constructor
-    private IntegratedVariableTreeNode(IntegratedVariableTreeNode original)
-      : base(original) {
+    [StorableConstructor]
+    protected IntegratedVariableTreeNode(bool deserializing) : base(deserializing) { }
+    protected IntegratedVariableTreeNode(IntegratedVariableTreeNode original, Cloner cloner)
+      : base(original, cloner) {
       minTimeOffset = original.minTimeOffset;
       maxTimeOffset = original.maxTimeOffset;
@@ -77 +77 @@
       maxTimeOffset = Math.Min(Symbol.MaxLag, Math.Max(minTimeOffset, maxTimeOffset + random.Next(-1, 2)));
     }
-
-
-    public override object Clone() {
-      return new IntegratedVariableTreeNode(this);
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new IntegratedVariableTreeNode(this, cloner);
     }
-
     public override string ToString() {
       return Weight.ToString("E4") + " I(" + VariableName +

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/MovingAverage.cs

@@ -47 +47 @@
       set { maxLag = value; }
     }
+    [StorableConstructor]
+    protected MovingAverage(bool deserializing) : base(deserializing) { }
+    protected MovingAverage(MovingAverage original, Cloner cloner)
+      : base(original, cloner) {
+      minLag = original.minLag;
+      maxLag = original.maxLag;
+    }
     public MovingAverage()
       : base("MovingAverage", "Represents a moving average of a variable value with a time offset.") {
@@ -57 +64 @@
 
     public override IDeepCloneable Clone(Cloner cloner) {
-      MovingAverage clone = (MovingAverage)base.Clone(cloner);
-      clone.minLag = minLag;
-      clone.maxLag = maxLag;
-      return clone;
+      return new MovingAverage(this, cloner);
     }
   }

branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis.MultiVariate.TimeSeriesPrognosis/3.3/Symbolic/Symbols/MovingAverageTreeNode.cs

@@ -50 +50 @@
 
     private MovingAverageTreeNode() { }
-
-    // copy constructor
-    private MovingAverageTreeNode(MovingAverageTreeNode original)
-      : base(original) {
+    [StorableConstructor]
+    protected MovingAverageTreeNode(bool deserializing) : base(deserializing) { }
+    protected MovingAverageTreeNode(MovingAverageTreeNode original, Cloner cloner)
+      : base(original, cloner) {
       minTimeOffset = original.minTimeOffset;
       maxTimeOffset = original.maxTimeOffset;
@@ -79 +79 @@
 
 
-    public override object Clone() {
-      return new MovingAverageTreeNode(this);
+    public override IDeepCloneable Clone(Cloner cloner) {
+      return new MovingAverageTreeNode(this, cloner);
     }
-
     public override string ToString() {
       return Weight.ToString("E4") + " MA(" + VariableName +