Changeset 3269 for trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3

Timestamp:

04/05/10 18:52:23 (14 years ago)

Author:

gkronber

Message:

Implemented initialization of Variable and Constant terminal nodes. #938 (Data types and operators for regression problems)

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic

Files:

• ArithmeticExpressionGrammar.cs (modified) (1 diff)
• SimpleArithmeticExpressionEvaluator.cs (modified) (1 diff)
• SymbolicRegressionProblem.cs (modified) (3 diffs)
• Symbols/Constant.cs (modified) (1 diff)
• Symbols/ConstantTreeNode.cs (modified) (3 diffs)
• Symbols/Variable.cs (modified) (1 diff)
• Symbols/VariableTreeNode.cs (modified) (2 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/ArithmeticExpressionGrammar.cs

@@ -29 +29 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.GeneralSymbols;
 using HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols;
+using HeuristicLab.Data;
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
   [StorableClass]
-  public class ArithmeticExpressionGrammar : Item, ISymbolicExpressionGrammar {
+  public class ArithmeticExpressionGrammar : NamedItemCollection<Symbol>, ISymbolicExpressionGrammar {
+
+    private List<string> variableNames = new List<string>();
+    public IEnumerable<string> VariableNames {
+      get { return variableNames; }
+      set {
+        variableNames = new List<string>(value);
+        var variable = (HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols.Variable)allSymbols[5];
+        variable.VariableNames = new ItemList<HeuristicLab.Data.StringValue>(variableNames.Select(x => new StringValue(x)));
+      }
+    }
 
     public ArithmeticExpressionGrammar()
-      : base() {
+      : this(allSymbols) {
     }
+
+    public ArithmeticExpressionGrammar(IEnumerable<Symbol> symbols)
+      : base(symbols) {
+      allSymbols = new List<Symbol>(symbols);
+    }
+
     #region ISymbolicExpressionGrammar Members
     [Storable]

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SimpleArithmeticExpressionEvaluator.cs

@@ -53 +53 @@
       if (node.Symbol is HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols.Variable) {
         var variableTreeNode = node as VariableTreeNode;
-        return dataset[row, 1 /*dataset.VariableIndex(variableTreeNode.VariableName)*/] * 1.0; //variableTreeNode.Weight;
+        return dataset[row, dataset.VariableIndex(variableTreeNode.VariableName)] * variableTreeNode.Weight;
       } else if (node.Symbol is Constant) {
         return ((ConstantTreeNode)node).Value;

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/SymbolicRegressionProblem.cs

@@ -111 +111 @@
       get { return EvaluatorParameter.Value; }
     }
-    public ISymbolicExpressionGrammar FunctionTreeGrammar {
-      get { return FunctionTreeGrammarParameter.Value; }
+    public ArithmeticExpressionGrammar FunctionTreeGrammar {
+      get { return (ArithmeticExpressionGrammar)FunctionTreeGrammarParameter.Value; }
     }
     public ISingleObjectiveSolutionsVisualizer Visualizer {
@@ -147 +147 @@
       creator.SymbolicExpressionTreeParameter.ActualName = "SymbolicRegressionModel";
       evaluator.QualityParameter.ActualName = "TrainingMeanSquaredError";
+      InputVariablesParameter.ValueChanged += new EventHandler(InputVariablesParameter_ValueChanged);
       ParameterizeSolutionCreator();
       ParameterizeEvaluator();
@@ -152 +153 @@
 
       Initialize();
+    }
+
+    void InputVariablesParameter_ValueChanged(object sender, EventArgs e) {
+      FunctionTreeGrammar.VariableNames = InputVariablesParameter.Value.Select(x => x.Value);
     }
 

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Symbols/Constant.cs

@@ -21 +21 @@
 
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Core;
+using HeuristicLab.Operators;
+using HeuristicLab.Random;
+using HeuristicLab.Data;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Parameters;
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols {
+  [StorableClass]
+  [Item("Constant", "Represents a constant value.")]
   public sealed class Constant : Symbol {
+    #region Parameter Properties
+    public IValueParameter<DoubleValue> MinValueParameter {
+      get { return (IValueParameter<DoubleValue>)Parameters["MinValue"]; }
+    }
+    public IValueParameter<DoubleValue> MaxValueParameter {
+      get { return (IValueParameter<DoubleValue>)Parameters["MaxValue"]; }
+    }
+    #endregion
+    #region Propeties
+    public DoubleValue MinValue {
+      get { return MinValueParameter.Value; }
+      set { MinValueParameter.Value = value; }
+    }
+    public DoubleValue MaxValue {
+      get { return MaxValueParameter.Value; }
+      set { MaxValueParameter.Value = value; }
+    }
+    #endregion
+    public Constant()
+      : base() {
+      Parameters.Add(new ValueParameter<DoubleValue>("MinValue", "The minimal value of the constant.", new DoubleValue(-20.0)));
+      Parameters.Add(new ValueParameter<DoubleValue>("MaxValue", "The maximal value of the constant.", new DoubleValue(20.0)));
+    }
+
     public override SymbolicExpressionTreeNode CreateTreeNode() {
       return new ConstantTreeNode(this);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Symbols/ConstantTreeNode.cs

@@ -24 +24 @@
 using System.Collections.Generic;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Random;
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols {
   [StorableClass]
   public sealed class ConstantTreeNode : SymbolicExpressionTreeTerminalNode {
+    public new Constant Symbol {
+      get { return (Constant)base.Symbol; }
+    }
     public override bool HasLocalParameters {
       get {
@@ -39 +45 @@
       set { constantValue = value; }
     }
-
     // copy constructor
     private ConstantTreeNode(ConstantTreeNode original)
@@ -48 +53 @@
     public ConstantTreeNode(Constant constantSymbol) : base(constantSymbol) { }
 
+    public override void ResetLocalParameters(IRandom random) {
+      base.ResetLocalParameters(random);
+      var range = Symbol.MaxValue.Value - Symbol.MaxValue.Value;
+      Value = random.NextDouble() * range - Symbol.MinValue.Value;
+    }
+
     public override object Clone() {
       return new ConstantTreeNode(this);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Symbols/Variable.cs

@@ -21 +21 @@
 
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
+using HeuristicLab.Core;
+using HeuristicLab.Operators;
+using HeuristicLab.Random;
+using HeuristicLab.Data;
+using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Parameters;
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols {
+  [StorableClass]
+  [Item("Variable", "Represents a variable value.")]
   public sealed class Variable : Symbol {
+    #region Parameter Properties
+    public IValueParameter<DoubleValue> WeightNuParameter {
+      get { return (IValueParameter<DoubleValue>)Parameters["WeightNu"]; }
+    }
+    public IValueParameter<DoubleValue> WeightSigmaParameter {
+      get { return (IValueParameter<DoubleValue>)Parameters["WeightSigma"]; }
+    }
+    public IValueParameter<ItemList<StringValue>> VariableNamesParameter {
+      get { return (IValueParameter<ItemList<StringValue>>)Parameters["VariableNames"]; }
+    }
+    #endregion
+    #region Properties
+    public DoubleValue WeightNu {
+      get { return WeightNuParameter.Value; }
+      set { WeightNuParameter.Value = value; }
+    }
+    public DoubleValue WeightSigma {
+      get { return WeightSigmaParameter.Value; }
+      set { WeightSigmaParameter.Value = value; }
+    }
+    public ItemList<StringValue> VariableNames {
+      get { return VariableNamesParameter.Value; }
+      set { VariableNamesParameter.Value = value; }
+    }
+    #endregion
+    public Variable()
+      : base() {
+      Parameters.Add(new ValueParameter<DoubleValue>("WeightNu", "The mean value for the initialization of weight ((N(nu, sigma)).", new DoubleValue(1.0)));
+      Parameters.Add(new ValueParameter<DoubleValue>("WeightSigma", "The sigma value for the initialization of weight (N(nu, sigma))", new DoubleValue(1.0)));
+      Parameters.Add(new ValueParameter<ItemList<StringValue>>("VariableNames", "The list of possible variable names for initialization."));
+    }
+
     public override SymbolicExpressionTreeNode CreateTreeNode() {
       return new VariableTreeNode(this);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Regression/3.3/Symbolic/Symbols/VariableTreeNode.cs

@@ -24 +24 @@
 using System.Collections.Generic;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Core;
+using HeuristicLab.Data;
+using HeuristicLab.Random;
 namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Symbols {
   [StorableClass]
   public sealed class VariableTreeNode : SymbolicExpressionTreeTerminalNode {
-    
+    public new Variable Symbol {
+      get { return (Variable)base.Symbol; }
+    }
     private double weight;
     [Storable]
@@ -50 +55 @@
     public VariableTreeNode(Variable variableSymbol) : base(variableSymbol) { }
 
+    public override void ResetLocalParameters(IRandom random) {
+      base.ResetLocalParameters(random);
+      var normalDistributedRNG = new NormalDistributedRandom(random, Symbol.WeightNu.Value, Symbol.WeightSigma.Value);
+      weight = normalDistributedRNG.NextDouble();
+      int variableIndex = random.Next(0, Symbol.VariableNames.Count);
+      variableName = Symbol.VariableNames[variableIndex].Value;
+    }
+
     public override object Clone() {
       return new VariableTreeNode(this);