Changeset 17134 for branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMAlgorithm/EMMBaseAlgorithm.cs

Timestamp:

07/11/19 16:30:22 (5 years ago)

Author:

msemenki

Message:

#2988:

1. The file system was changed, folders was added and part of files was transferred in these folders.
2. HelpFunctions class was divided on 2 parts: HelpFuctions for common purposes static functions and SelfConfiguration that include functions for self-configuration mechanism realization (is used in EMMSucsessMap).
3. Parts of self-configuration mechanism was transferred from EMMSucsessMap.cs to SelfConfiguration.cs. Now EMMSucsessMap used SelfConfiguration like one of data member. Other parts of project was adopted for this changing.
4. FileComunication class was added. It include the majority of functions for printing to files or reading from files. Here were realized possibility to write and read to hl files.
5. ModelTreeNode.cs has additional possibility - to write sub-model in string (then it is possible to write it in file).
6. InfixExpressionFormatter.cs can work with TreeModelNode.
7. Possibility for different map types to be readable from files was extended and cheeked.
8. Such parameters like - ClusterNumbers, ClusterNumbersShow, NegbourNumber, NegbourType (that is used only in several maps) was transferred from EMMAlgorithm to Map Parameters. Now EMMBaseMap class inherited from ParameterizedNamedItem (not from Item). And EMMIslandMap and EMMNetworkMap contains their parameters (constructors was modified). CreationMap calls functions were simplified.
9. Functions for different distance metric calculation was added. Now, it is possible to calculate different types of distances between models (with different random values of constants).
10. DistanceParametr was added. Now maps can be created according different types of distance calculations.
11. The class EMMClustering has new name KMeansClusterizationAlgorithm. On KMeansClusterizationAlgorithm bug with bloating of centroids list was fixed. Algorithm was adopted for working with different type of distance metric and get maximum number of iterations.
12. Possibilities for constants optimization in sub-models an whole tree was added. EMMAlgorithm get new function for evaluation of individuals (and some additional technical stuff for that). Function for trees with model in usual tree transformation and back was added.
13. EMMAlgorithm was divided on 2 parts:

• EMMAlgorithm, that contain evolutionary algorithm working with sub-models, and use ready to use maps;
• ModelSetPreparation, that contain distance calculation, model set simplification and map creation.

Location:

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMAlgorithm

Files:

• . (added)
• EMMBaseAlgorithm.cs (moved) (moved from branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMBaseAlgorithm.cs) (10 diffs)

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMAlgorithm/EMMBaseAlgorithm.cs

@@ -41 +41 @@
 
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
-  [Item("MOEADAlgorithmBase", "Base class for all MOEA/D algorithm variants.")]
+  [Item("EMMAlgorithmBase", "Base class for all EMM algorithm variants.")]
   [StorableType("A56A396B-965A-4ADE-8A2B-AE3A45F9C239")]
   public abstract class EvolvmentModelsOfModelsAlgorithmBase : FixedDataAnalysisAlgorithm<ISymbolicDataAnalysisSingleObjectiveProblem> {
@@ -78 +78 @@
     private const string AnalyzerParameterName = "Analyzer";
     private const string InputFileParameterName = "InputFile";
-    private const string ClusterNumbersParameterName = "ClusterNumbers";
-    private const string ClusterNumbersShowParameterName = "ClusterNumbersShow";
     private const string AlgorithmImplementationTypeParameterName = "AlgorithmImplementationType";
+    private const string DistanceTypeParameterName = "DistanceType";
     private const string MapParameterName = "Map";
-    private const string NegbourTypeParameterName = "NegbourType";
-    private const string NegbourNumberParameterName = "NegbourNumber";
     public IValueParameter<MultiAnalyzer> AnalyzerParameter {
       get { return (ValueParameter<MultiAnalyzer>)Parameters[AnalyzerParameterName]; }
@@ -90 +87 @@
       get { return (IFixedValueParameter<IntValue>)Parameters[SeedParameterName]; }
     }
-    public IValueParameter<IntValue> ClusterNumbersParameter {
-      get { return (IValueParameter<IntValue>)Parameters[ClusterNumbersParameterName]; }
-    }
-    public IValueParameter<IntValue> ClusterNumbersShowParameter {
-      get { return (IValueParameter<IntValue>)Parameters[ClusterNumbersShowParameterName]; }
-    }
     public IConstrainedValueParameter<StringValue> AlgorithmImplementationTypeParameter {
       get { return (IConstrainedValueParameter<StringValue>)Parameters[AlgorithmImplementationTypeParameterName]; }
     }
+    public IConstrainedValueParameter<StringValue> DistanceTypeParameter {
+      get { return (IConstrainedValueParameter<StringValue>)Parameters[DistanceTypeParameterName]; }
+    }
     public IConstrainedValueParameter<EMMMapBase<ISymbolicExpressionTree>> MapParameter {
       get { return (IConstrainedValueParameter<EMMMapBase<ISymbolicExpressionTree>>)Parameters[MapParameterName]; }
     }
-    public IFixedValueParameter<StringValue> NegbourTypeParameter {
-      get { return (IFixedValueParameter<StringValue>)Parameters[NegbourTypeParameterName]; }
-    }
-    public IFixedValueParameter<IntValue> NegbourNumberParameter {
-      get { return (IFixedValueParameter<IntValue>)Parameters[NegbourNumberParameterName]; }
-    }
+
     public IFixedValueParameter<StringValue> InputFileParameter {
       get { return (IFixedValueParameter<StringValue>)Parameters[InputFileParameterName]; }
@@ -151 +140 @@
       set { SeedParameter.Value.Value = value; }
     }
-    public IntValue ClusterNumbers {
-      get { return ClusterNumbersParameter.Value; }
-      set { ClusterNumbersParameter.Value = value; }
-    }
-    public IntValue ClusterNumbersShow {
-      get { return ClusterNumbersShowParameter.Value; }
-      set { ClusterNumbersShowParameter.Value = value; }
-    }
     public StringValue AlgorithmImplemetationType {
       get { return AlgorithmImplementationTypeParameter.Value; }
       set { AlgorithmImplementationTypeParameter.Value.Value = value.Value; }
     }
+    public StringValue DistanceType {
+      get { return DistanceTypeParameter.Value; }
+      set { DistanceTypeParameter.Value.Value = value.Value; }
+    }
     public EMMMapBase<ISymbolicExpressionTree> Map {
       get { return MapParameter.Value; }
       set { MapParameter.Value = value; }
     }
-    public StringValue NegbourType {
-      get { return NegbourTypeParameter.Value; }
-      set { NegbourTypeParameter.Value.Value = value.Value; }
-    }
-    public IntValue NegbourNumber {
-      get { return NegbourNumberParameter.Value; }
-      set { NegbourNumberParameter.Value.Value = value.Value; }
-    }
     public StringValue InputFile {
       get { return InputFileParameter.Value; }
@@ -229 +206 @@
       Parameters.Add(new FixedValueParameter<IntValue>(SeedParameterName, "The random seed used to initialize the new pseudo random number generator.", new IntValue(0)));
       Parameters.Add(new FixedValueParameter<StringValue>(InputFileParameterName, "The file with set of models that will be.", new StringValue("input.txt")));
-      Parameters.Add(new ConstrainedValueParameter<StringValue>(AlgorithmImplementationTypeParameterName, "The Type of possible algorith, implemetation, choose one: OnlyMap, Full, Read."));
-      Parameters.Add(new ConstrainedValueParameter<EMMMapBase<ISymbolicExpressionTree>>(MapParameterName, "The type of map crearion algorithm. Use one from: IslandMap, NetworkMap."));
-      Parameters.Add(new FixedValueParameter<IntValue>(NegbourNumberParameterName, "The parametr for FullMap type of map crearion algorithm. Use one from: 10, 20.", new IntValue(10)));
-      Parameters.Add(new FixedValueParameter<StringValue>(NegbourTypeParameterName, "The parametr for FullMap type of map crearion algorithm. Use one from: Percent, Number.", new StringValue("Number")));
+      Parameters.Add(new ConstrainedValueParameter<StringValue>(AlgorithmImplementationTypeParameterName, "The Type of possible algorithm, implementation, choose one: OnlyMap, Full, Read."));
+      Parameters.Add(new ConstrainedValueParameter<StringValue>(DistanceTypeParameterName, "The Type of possible distance calculator for case of only distance calculation."));
+      Parameters.Add(new ConstrainedValueParameter<EMMMapBase<ISymbolicExpressionTree>>(MapParameterName, "The type of map creation algorithm. Use one from: IslandMap, NetworkMap."));
       Parameters.Add(new FixedValueParameter<BoolValue>(SetSeedRandomlyParameterName, "True if the random seed should be set to a random value, otherwise false.", new BoolValue(true)));
       Parameters.Add(new ValueParameter<IntValue>(PopulationSizeParameterName, "The size of the population of Solutions.", new IntValue(100)));
-      Parameters.Add(new ConstrainedValueParameter<ISelector>(SelectorParameterName, "The operator used to sellect parents."));
+      Parameters.Add(new ConstrainedValueParameter<ISelector>(SelectorParameterName, "The operator used to select parents."));
       Parameters.Add(new ValueParameter<PercentValue>(CrossoverProbabilityParameterName, "The probability that the crossover operator is applied.", new PercentValue(0.9)));
       Parameters.Add(new ValueParameter<IntValue>(GroupSizeParameterName, "The GoupSize that the Selector operator is applied.", new IntValue(3)));
@@ -244 +220 @@
       Parameters.Add(new ValueParameter<IntValue>(MaximumEvaluatedSolutionsParameterName, "The maximum number of evaluated Solutions (approximately).", new IntValue(100_000)));
       Parameters.Add(new ValueParameter<IRandom>(RandomParameterName, new MersenneTwister()));
-      Parameters.Add(new ValueParameter<IntValue>("Elites", "The numer of elite Solutions which are kept in each generation.", new IntValue(1)));
-      Parameters.Add(new ValueParameter<IntValue>(ClusterNumbersParameterName, "The number of clusters for model Map.", new IntValue(10)));
-      Parameters.Add(new ValueParameter<IntValue>(ClusterNumbersShowParameterName, "The number of clusters for model Map.", new IntValue(10)));
+      Parameters.Add(new ValueParameter<IntValue>("Elites", "The number of elite Solutions which are kept in each generation.", new IntValue(1)));
       foreach (ISelector selector in ApplicationManager.Manager.GetInstances<ISelector>().Where(x => !(x is IMultiObjectiveSelector)).OrderBy(x => x.Name))
         SelectorParameter.ValidValues.Add(selector);
@@ -274 +248 @@
       if (Problem != null) {
         Problem.SymbolicExpressionTreeInterpreter = new SymbolicDataAnalysisExpressionTreeBatchInterpreter();
-        //Problem.SymbolicExpressionTreeGrammar = new EMMGrammar();
       }
     }
     protected void MapParameterUpdate() {
-      int neghboorNumber = 10;
-
-      switch (NegbourType.Value) {
-        case "Percent": neghboorNumber = Convert.ToInt32((Convert.ToDouble(ClusterNumbersParameter.Value.Value)) * (Convert.ToDouble(NegbourNumber.Value)) / 100.0); break;
-        case "Number": neghboorNumber = NegbourNumber.Value; break;
-        default: neghboorNumber = NegbourNumber.Value; break;
-      }
       var mapTypes = new EMMMapBase<ISymbolicExpressionTree>[]
       {
         new EMMIslandMap(),
-        new EMMNetworkMap(neghboorNumber),
+        new EMMNetworkMap(),
         new EMMDisatanceMap(),
         new EMMRankMap(),
@@ -301 +267 @@
           new StringValue("Full"),
           new StringValue("Read"),
-          new StringValue ("OnlyMap")
         };
       foreach (var t in algorithmType) {
         AlgorithmImplementationTypeParameter.ValidValues.Add(t);
       }
+      var distanceType = new StringValue[]
+        {
+          new StringValue("MSE"),
+          new StringValue("PearsonsRSquared"),
+          new StringValue ("Covariance"),
+          new StringValue ("MaxAbsoluteError"),
+          new StringValue ("MeanAbsoluteError"),
+          new StringValue ("Symbolic")
+        };
+      foreach (var t in distanceType) {
+        DistanceTypeParameter.ValidValues.Add(t);
+      }
     }
 
@@ -320 +297 @@
       }
 
-      //if (original.offspringPopulation != null) {
-      //  offspringPopulation = original.offspringPopulation.Select(cloner.Clone).ToList();
-      //}
-
-      //if (original.jointPopulation != null) {
-      //  jointPopulation = original.jointPopulation.Select(x => cloner.Clone(x)).ToList();
-      //}
-
       if (original.executionContext != null) {
         executionContext = cloner.Clone(original.executionContext);
@@ -335 +304 @@
         globalScope = cloner.Clone(original.globalScope);
       }
-
-      // hack
-      trees = original.trees.Select(x => cloner.Clone(x)).ToArray();
+      // hack 
+      if (original.trees != null) {
+        trees = original.trees.Select(x => cloner.Clone(x)).ToArray();
+      }
     }