Changeset 9152

Timestamp:

01/14/13 13:14:22 (12 years ago)

Author:

mkommend

Message:

#2004: Add an update flag to the best solution symbolic data analysis analyzers (single- and multi objective).

Location:

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers

Files:

• SymbolicDataAnalysisMultiObjectiveTrainingBestSolutionAnalyzer.cs (modified) (8 diffs)
• SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer.cs (modified) (5 diffs)
• SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer.cs (modified) (7 diffs)
• SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer.cs (modified) (5 diffs)

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisMultiObjectiveTrainingBestSolutionAnalyzer.cs

@@ -20 +20 @@
 #endregion
 
+using System;
 using System.Collections.Generic;
 using System.Linq;
@@ -26 +27 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Operators;
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using System;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
@@ -42 +41 @@
     private const string TrainingBestSolutionsParameterName = "Best training solutions";
     private const string TrainingBestSolutionQualitiesParameterName = "Best training solution qualities";
+    private const string UpdateAlwaysParameterName = "Always update best solutions";
 
     #region parameter properties
@@ -49 +49 @@
     public ILookupParameter<ItemList<DoubleArray>> TrainingBestSolutionQualitiesParameter {
       get { return (ILookupParameter<ItemList<DoubleArray>>)Parameters[TrainingBestSolutionQualitiesParameterName]; }
+    }
+    public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
     }
     #endregion
@@ -60 +63 @@
       set { TrainingBestSolutionQualitiesParameter.ActualValue = value; }
     }
+    public BoolValue UpdateAlways {
+      get { return UpdateAlwaysParameter.Value; }
+    }
     #endregion
 
@@ -69 +75 @@
       Parameters.Add(new LookupParameter<ItemList<T>>(TrainingBestSolutionsParameterName, "The training best (Pareto-optimal) symbolic data analysis solutions."));
       Parameters.Add(new LookupParameter<ItemList<DoubleArray>>(TrainingBestSolutionQualitiesParameterName, "The qualities of the training best (Pareto-optimal) solutions."));
+      Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solutions should always be updated regardless of its quality.", new BoolValue(false)));
+      UpdateAlwaysParameter.Hidden = true;
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
+        Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solutions should always be updated regardless of its quality.", new BoolValue(false)));
+        UpdateAlwaysParameter.Hidden = true;
+      }
     }
 
@@ -81 +97 @@
       }
 
-      IList<double[]> trainingBestQualities = TrainingBestSolutionQualities
-        .Select(x => x.ToArray())
-        .ToList();
+      //if the pareto front of best solutions shall be updated regardless of the quality, the list initialized empty to discard old solutions
+      IList<double[]> trainingBestQualities;
+      if (UpdateAlways.Value) {
+        trainingBestQualities = new List<double[]>();
+      } else {
+        trainingBestQualities = TrainingBestSolutionQualities.Select(x => x.ToArray()).ToList();
+      }
 
       #region find best trees
@@ -131 +151 @@
       public bool Equals(double[] x, double[] y) {
         if (y.Length != x.Length) throw new ArgumentException();
-        for (int i = 0; i < x.Length;i++ ) {
+        for (int i = 0; i < x.Length; i++) {
           if (!x[i].IsAlmost(y[i])) return false;
         }

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer.cs

@@ -44 +44 @@
     private const string ValidationBestSolutionsParameterName = "Best validation solutions";
     private const string ValidationBestSolutionQualitiesParameterName = "Best validation solution qualities";
+    private const string UpdateAlwaysParameterName = "Always update best solutions";
 
     #region parameter properties
@@ -51 +52 @@
     public ILookupParameter<ItemList<DoubleArray>> ValidationBestSolutionQualitiesParameter {
       get { return (ILookupParameter<ItemList<DoubleArray>>)Parameters[ValidationBestSolutionQualitiesParameterName]; }
+    }
+    public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
     }
     #endregion
@@ -62 +66 @@
       set { ValidationBestSolutionQualitiesParameter.ActualValue = value; }
     }
+    public BoolValue UpdateAlways {
+      get { return UpdateAlwaysParameter.Value; }
+    }
     #endregion
 
@@ -71 +78 @@
       Parameters.Add(new LookupParameter<ItemList<S>>(ValidationBestSolutionsParameterName, "The validation best (Pareto-optimal) symbolic data analysis solutions."));
       Parameters.Add(new LookupParameter<ItemList<DoubleArray>>(ValidationBestSolutionQualitiesParameterName, "The qualities of the validation best (Pareto-optimal) solutions."));
+      Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best validation solutions should always be updated regardless of its quality.", new BoolValue(false)));
+      UpdateAlwaysParameter.Hidden = true;
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
+        Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solutions should always be updated regardless of its quality.", new BoolValue(false)));
+        UpdateAlwaysParameter.Hidden = true;
+      }
     }
 
@@ -86 +103 @@
       }
 
-      IList<double[]> trainingBestQualities = ValidationBestSolutionQualities
-        .Select(x => x.ToArray())
-        .ToList();
+      //if the pareto front of best solutions shall be updated regardless of the quality, the list initialized empty to discard old solutions
+      IList<double[]> trainingBestQualities;
+      if (UpdateAlways.Value) {
+        trainingBestQualities = new List<double[]>();
+      } else {
+        trainingBestQualities = ValidationBestSolutionQualities.Select(x => x.ToArray()).ToList();
+      }
 
       #region find best trees

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer.cs

@@ -20 +20 @@
 #endregion
 
-using System.Collections.Generic;
 using System.Linq;
 using HeuristicLab.Common;
@@ -26 +25 @@
 using HeuristicLab.Data;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HeuristicLab.Operators;
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
@@ -41 +39 @@
     private const string TrainingBestSolutionParameterName = "Best training solution";
     private const string TrainingBestSolutionQualityParameterName = "Best training solution quality";
+    private const string UpdateAlwaysParameterName = "Always update best solution";
 
     #region parameter properties
@@ -48 +47 @@
     public ILookupParameter<DoubleValue> TrainingBestSolutionQualityParameter {
       get { return (ILookupParameter<DoubleValue>)Parameters[TrainingBestSolutionQualityParameterName]; }
+    }
+    public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
     }
     #endregion
@@ -59 +61 @@
       set { TrainingBestSolutionQualityParameter.ActualValue = value; }
     }
+    public BoolValue UpdateAlways {
+      get { return UpdateAlwaysParameter.Value; }
+    }
     #endregion
 
@@ -68 +73 @@
       Parameters.Add(new LookupParameter<T>(TrainingBestSolutionParameterName, "The training best symbolic data analyis solution."));
       Parameters.Add(new LookupParameter<DoubleValue>(TrainingBestSolutionQualityParameterName, "The quality of the training best symbolic data analysis solution."));
+      Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solution should always be updated regardless of its quality.", new BoolValue(false)));
+      UpdateAlwaysParameter.Hidden = true;
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
+        Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solution should always be updated regardless of its quality.", new BoolValue(false)));
+        UpdateAlwaysParameter.Hidden = true;
+      }
     }
 
@@ -85 +100 @@
 
       var results = ResultCollection;
-      if (bestTree != null && (TrainingBestSolutionQuality == null ||
+      if (bestTree != null && (UpdateAlways.Value || TrainingBestSolutionQuality == null ||
         IsBetter(bestQuality, TrainingBestSolutionQuality.Value, Maximization.Value))) {
         TrainingBestSolution = CreateSolution(bestTree, bestQuality);

trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisSingleObjectiveValidationBestSolutionAnalyzer.cs

@@ -43 +43 @@
     private const string ValidationBestSolutionParameterName = "Best validation solution";
     private const string ValidationBestSolutionQualityParameterName = "Best validation solution quality";
+    private const string UpdateAlwaysParameterName = "Always update best solution";
 
     #region parameter properties
@@ -50 +51 @@
     public ILookupParameter<DoubleValue> ValidationBestSolutionQualityParameter {
       get { return (ILookupParameter<DoubleValue>)Parameters[ValidationBestSolutionQualityParameterName]; }
+    }
+    public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
+      get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
     }
     #endregion
@@ -61 +65 @@
       set { ValidationBestSolutionQualityParameter.ActualValue = value; }
     }
+    public BoolValue UpdateAlways {
+      get { return UpdateAlwaysParameter.Value; }
+    }
     #endregion
 
@@ -70 +77 @@
       Parameters.Add(new LookupParameter<S>(ValidationBestSolutionParameterName, "The validation best symbolic data analyis solution."));
       Parameters.Add(new LookupParameter<DoubleValue>(ValidationBestSolutionQualityParameterName, "The quality of the validation best symbolic data analysis solution."));
+      Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best validation solution should always be updated regardless of its quality.", new BoolValue(false)));
+      UpdateAlwaysParameter.Hidden = true;
+    }
+
+    [StorableHook(HookType.AfterDeserialization)]
+    private void AfterDeserialization() {
+      if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
+        Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solution should always be updated regardless of its quality.", new BoolValue(false)));
+        UpdateAlwaysParameter.Hidden = true;
+      }
     }
 
@@ -117 +134 @@
 
       var results = ResultCollection;
-      if (ValidationBestSolutionQuality == null ||
+      if (UpdateAlways.Value || ValidationBestSolutionQuality == null ||
         IsBetter(bestValidationQuality, ValidationBestSolutionQuality.Value, Maximization.Value)) {
         ValidationBestSolution = CreateSolution(bestTree, bestValidationQuality);