Changeset 6090 for branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Evaluators

Timestamp:

05/01/11 22:02:28 (14 years ago)

Author:

cneumuel

Message:

#1215

• added weight parameters for quality, stddev and evaluated solutions
• lots of fixes

Location:

branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Evaluators

Files:

• AlgorithmEvaluator.cs (modified) (5 diffs)
• AlgorithmRunsAnalyzer.cs (modified) (5 diffs)

branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Evaluators/AlgorithmEvaluator.cs

@@ -1 @@
-using System;
-using System.Diagnostics;
-using System.Linq;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -10 +8 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
 
 namespace HeuristicLab.Problems.MetaOptimization {
@@ -33 +30 @@
       get { return (ILookupParameter<ParameterConfigurationTree>)Parameters["ParameterConfigurationTree"]; }
     }
-    public IValueParameter<IItemList<IRun>> RunsParameter {
-      get { return (IValueParameter<IItemList<IRun>>)Parameters["Runs"]; }
+    //public IValueParameter<IItemList<IRun>> RunsParameter {
+    //  get { return (IValueParameter<IItemList<IRun>>)Parameters["Runs"]; }
+    //}
+    public LookupParameter<ResultCollection> ResultsParameter {
+      get { return (LookupParameter<ResultCollection>)Parameters["Results"]; }
     }
     #endregion
@@ -47 +47 @@
       Parameters.Add(new LookupParameter<IntValue>("RepetitionIndex", ""));
       Parameters.Add(new LookupParameter<ParameterConfigurationTree>("ParameterConfigurationTree", ""));
-      Parameters.Add(new ValueParameter<IItemList<IRun>>("Runs", ""));
+      Parameters.Add(new LookupParameter<ResultCollection>("Results", ""));
     }
     protected AlgorithmEvaluator(AlgorithmEvaluator original, Cloner cloner) : base(original, cloner) { }
@@ -55 +55 @@
 
     public override IOperation Apply() {
+      ItemDictionary<StringValue, RunCollection> solutionCache = ResultsParameter.ActualValue.ContainsKey("SolutionCache") ? (ItemDictionary<StringValue, RunCollection>)ResultsParameter.ActualValue["SolutionCache"].Value : null;
+      ParameterConfigurationTree parameterConfiguration = ParameterConfigurationParameter.ActualValue;
       IAlgorithm algorithm = AlgorithmParameter.ActualValue;
+      int repetitionIndex = RepetitionIndexParameter.ActualValue.Value;
 
-      #region Debug Code for SymbolicRegressionGrammar
-      var srp = (SymbolicRegressionSingleObjectiveProblem)algorithm.Problem;
-      //Console.WriteLine("Evaluating Grammar: " + PrintGrammar(srp.SymbolicExpressionTreeGrammar));
-      #endregion
-
-      var sw = new Stopwatch();
-      sw.Start();
-      //// prepare and clear is needed, if the algorithm has been started and stopped before (this happens when meta level algorithm is paused)
-      //algorithm.Prepare(); // <--- SHOULD NOT HAPPEN!
-      //algorithm.Runs.Clear();
-
-      algorithm.StartSync(CancellationToken);
-      sw.Stop();
-      Console.WriteLine("{0},{1}: {2} (Grammar: {3})", ProblemIndexParameter.ActualValue.Value, RepetitionIndexParameter.ActualValue.Value, sw.Elapsed, PrintGrammar(srp.SymbolicExpressionTreeGrammar));
-
-      RunsParameter.Value = new ItemList<IRun>(algorithm.Runs);
-
+      if (solutionCache != null && solutionCache.Count(x => x.Key.Value == parameterConfiguration.ParameterInfoString) > 0) {
+        algorithm.Runs.Add(solutionCache.Single(x => x.Key.Value == parameterConfiguration.ParameterInfoString).Value.ElementAt(repetitionIndex));
+      } else {
+        algorithm.StartSync(CancellationToken);
+      }
       return base.Apply();
-    }
-
-    /// <summary>
-    /// This method should repair an invalid parameterConfiguration.
-    /// The strategy is to just randomize parameter settings. It's not guaranteed to be a vaild setting
-    /// </summary>
-    private void Repair(ParameterConfigurationTree parameterConfiguration, IRandom random) {
-      parameterConfiguration.Randomize(random);
     }
 

branches/HeuristicLab.MetaOptimization/HeuristicLab.Problems.MetaOptimization/3.3/Evaluators/AlgorithmRunsAnalyzer.cs

@@ -54 +54 @@
     public LookupParameter<BoolValue> MaximizationParameter {
       get { return (LookupParameter<BoolValue>)Parameters["Maximization"]; }
+    }
+    public LookupParameter<DoubleValue> QualityWeightParameter {
+      get { return (LookupParameter<DoubleValue>)Parameters[MetaOptimizationProblem.QualityWeightParameterName]; }
+    }
+    public LookupParameter<DoubleValue> StandardDeviationWeightParameter {
+      get { return (LookupParameter<DoubleValue>)Parameters[MetaOptimizationProblem.StandardDeviationWeightParameterName]; }
+    }
+    public LookupParameter<DoubleValue> EvaluatedSolutionsWeightParameter {
+      get { return (LookupParameter<DoubleValue>)Parameters[MetaOptimizationProblem.EvaluatedSolutionsWeightParameterName]; }
     }
     #endregion
@@ -75 +84 @@
       Parameters.Add(new ScopeTreeLookupParameter<IntValue>("RepetitionIndex", "The index of the repetition"));
       Parameters.Add(new LookupParameter<BoolValue>("Maximization", "Set to false if the problem should be minimized."));
+      Parameters.Add(new LookupParameter<DoubleValue>(MetaOptimizationProblem.QualityWeightParameterName));
+      Parameters.Add(new LookupParameter<DoubleValue>(MetaOptimizationProblem.StandardDeviationWeightParameterName));
+      Parameters.Add(new LookupParameter<DoubleValue>(MetaOptimizationProblem.EvaluatedSolutionsWeightParameterName));
     }
     protected AlgorithmRunsAnalyzer(AlgorithmRunsAnalyzer original, Cloner cloner)
@@ -92 +104 @@
       bool maximization = MaximizationParameter.ActualValue.Value;
       int repetitions = RepetitionsParameter.ActualValue.Value;
+      double qualityWeight = QualityWeightParameter.ActualValue.Value;
+      double standardDeviationWeight = StandardDeviationWeightParameter.ActualValue.Value;
+      double evaluatedSolutionsWeight = EvaluatedSolutionsWeightParameter.ActualValue.Value;
       var resultNames = new List<string> { "BestQuality", "Execution Time", "EvaluatedSolutions" };
       int currentGeneration = GenerationsParameter.ActualValue != null ? GenerationsParameter.ActualValue.Value : 0;
@@ -149 +164 @@
         parameterConfiguration.Runs = runs;
 
-        this.QualityParameter.ActualValue = new DoubleValue(MetaOptimizationUtil.Normalize(parameterConfiguration, referenceQualityAverages, referenceQualityDeviations, referenceEvaluatedSolutionAverages, 1, 0.1, 1, maximization));
+        this.QualityParameter.ActualValue = new DoubleValue(MetaOptimizationUtil.Normalize(parameterConfiguration, referenceQualityAverages, referenceQualityDeviations, referenceEvaluatedSolutionAverages, qualityWeight, standardDeviationWeight, evaluatedSolutionsWeight, maximization));
       } else {
         // something terrible happened -> most probably due to invalid parameters.
@@ -155 +170 @@
         double penaltyValue;
         if (maximization)
-          penaltyValue = results.ContainsKey("CurrentWorstQuality") ? ((DoubleValue)results["CurrentWorstQuality"]).Value : referenceQualityAverages.Min();
+          penaltyValue = results.ContainsKey("CurrentWorstQuality") ? ((DoubleValue)results["CurrentWorstQuality"].Value).Value : referenceQualityAverages.Min();
         else
-          penaltyValue = results.ContainsKey("CurrentWorstQuality") ? ((DoubleValue)results["CurrentWorstQuality"]).Value : referenceQualityAverages.Max();
+          penaltyValue = results.ContainsKey("CurrentWorstQuality") ? ((DoubleValue)results["CurrentWorstQuality"].Value).Value : referenceQualityAverages.Max();
+        
         this.QualityParameter.ActualValue = new DoubleValue(penaltyValue);
+        parameterConfiguration.Quality = new DoubleValue(penaltyValue);
+
+        parameterConfiguration.AverageExecutionTimes = new ItemList<TimeSpanValue>(Enumerable.Repeat(new TimeSpanValue(TimeSpan.Zero), problems.Count));
+        parameterConfiguration.AverageEvaluatedSolutions = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.Repetitions = new IntValue(repetitions);
+        parameterConfiguration.AverageQualities = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.BestQualities = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.WorstQualities = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.QualityVariances = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.QualityStandardDeviations = new DoubleArray(Enumerable.Repeat(0.0, problems.Count).ToArray());
+        parameterConfiguration.Runs = null;
       }