Changeset 16734 for branches/2988_ModelsOfModels2

Timestamp:

04/01/19 13:03:13 (6 years ago)

Author:

msemenki

Message:

#2988: Add Model Symbol Frequency Analyzer and Model's Clusters Frequency Analyzer. Fix Bag's with Keys. Fix changing during mutation for Variables Types in SubModels .

Location:

branches/2988_ModelsOfModels2

Files:

• HeuristicLab.Algorithms.EMM/EMMAlgorithm.cs (modified) (3 diffs)
• HeuristicLab.Algorithms.EMM/EMMBaseAlgorithm.cs (modified) (1 diff)
• HeuristicLab.Algorithms.EMM/EMMMapBase.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.EMM/EMMMapTreeModel.cs (modified) (5 diffs)
• HeuristicLab.Algorithms.EMM/EMMMutators.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.EMM/EMMSolution.cs (modified) (3 diffs)
• HeuristicLab.Algorithms.EMM/Plugin.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/ModelClustersFrequencyAnalyzer.cs (added)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/ModelsFrequencyAnalyzer.cs (added)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisVariableFrequencyAnalyzer.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic-3.4.csproj (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/ModelTreeNode.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/TreeModel.cs (modified) (2 diffs)

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

@@ -37 +37 @@
   [Item("EvolvmentModelsOfModels Algorithm ", "EMM implementation")]
   [Creatable(CreatableAttribute.Categories.PopulationBasedAlgorithms, Priority = 125)]
-  [StorableType("D02C50E5-8325-496F-8DEA-C23651756846")]
+  [StorableType("AD23B21F-089A-4C6C-AD2E-1B01E7939CF5")]
   public class EMMAlgorithm : EvolvmentModelsOfModelsAlgorithmBase {
     public EMMMapTreeModel Map { get; private set; }
@@ -57 +57 @@
       InfixExpressionParser parser = new InfixExpressionParser();
       var trees = File.ReadAllLines(InputFileParameter.Value.Value).Select(parser.Parse);
-      Map = new EMMMapTreeModel(RandomParameter.Value, trees, ClusterNumbersParameter.Value.Value);
-      ClusterNumbersParameter.Value.Value = Map.K;
-      if (previousExecutionState != ExecutionState.Paused) {
-        InitializeAlgorithm(cancellationToken);
-      }
-      globalScope.Variables.Add(new Variable("TreeModelMap", Map));
-      EMMEvolutionaryAlgorithmRun(cancellationToken);
+      // this.Problem.SymbolicExpressionTreeGrammar;
+      /*   Problem.ProblemData.Dataset.ColumnNames.Take(2).ToList();
+         trees.First().Root.Grammar.ContainsSymbol((IVariable)a).
+           = this.Problem.SymbolicExpressionTreeGrammar;*/
+      int flag = 1;
+      switch (flag) {
+        case 0: // for case when we want only create map, and do  not want made somting also.
+          Map = new EMMMapTreeModel(RandomParameter.Value, trees, ClusterNumbersParameter.Value.Value);
+          ClusterNumbersParameter.Value.Value = Map.K;
+          File.WriteAllLines("Map.txt", Map.MapToString());
+          File.WriteAllLines("MapToSee.txt", Map.MapToSee());
+          globalScope = new Scope("Global Scope");
+          executionContext = new ExecutionContext(null, this, globalScope);
+          break;
+        case 1: // for case when we want read existed map and work with it;
+          Map = new EMMMapTreeModel(RandomParameter.Value, trees);
+          ClusterNumbersParameter.Value.Value = Map.K;
+          if (previousExecutionState != ExecutionState.Paused) {
+            InitializeAlgorithm(cancellationToken);
+          }
+          globalScope.Variables.Add(new Variable("TreeModelMap", Map));
+          EMMEvolutionaryAlgorithmRun(cancellationToken);
+          break;
+
+        default: //for case of usial from zero step starting
+          Map = new EMMMapTreeModel(RandomParameter.Value, trees, ClusterNumbersParameter.Value.Value);
+          ClusterNumbersParameter.Value.Value = Map.K;
+          if (previousExecutionState != ExecutionState.Paused) {
+            InitializeAlgorithm(cancellationToken);
+          }
+          globalScope.Variables.Add(new Variable("TreeModelMap", Map));
+          EMMEvolutionaryAlgorithmRun(cancellationToken);
+          break;
+      }
+
     }
     private void EMMEvolutionaryAlgorithmRun(CancellationToken cancellationToken) {
@@ -201 +229 @@
         foreach (var node in tree.IterateNodesPostfix().OfType<TreeModelTreeNode>()) {
           node.Tree = Map.NewModelForInizializtion(random, out int cluster, out int treeNumber);
-          node.Tree.Root.ShakeLocalParameters(random, 0.5);
+          node.SetLocalParameters(random, 0.5);
           node.ClusterNumer = cluster;
           node.TreeNumber = treeNumber;

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

@@ -40 +40 @@
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
   [Item("MOEADAlgorithmBase", "Base class for all MOEA/D algorithm variants.")]
-  [StorableType("DD721D8A-A4DE-44C1-8D83-7888E8433B5F")]
+  [StorableType("A56A396B-965A-4ADE-8A2B-AE3A45F9C239")]
   public abstract class EvolvmentModelsOfModelsAlgorithmBase : FixedDataAnalysisAlgorithm<ISymbolicDataAnalysisSingleObjectiveProblem> {
     #region data members

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMMapBase.cs

@@ -25 +25 @@
 
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
-  [StorableType("8A5818D6-2B74-4148-AFBC-D36CE6256406")]
+  [StorableType("83CF9650-98FF-454B-9072-82EA4D39C752")]
   public abstract class EMMMapBase<T> : Item where T : class {
     public List<T> ModelSet { get; set; }
@@ -34 +34 @@
 
     protected abstract void CalculateDistances();
-    public abstract void CreateMap(IRandom random, int k);
+    protected abstract void CreateMap(IRandom random, int k);
     public abstract T NewModelForInizializtion(IRandom random, out int cluster, out int treeNumber);
 

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMMapTreeModel.cs

@@ -26 +26 @@
 using HeuristicLab.Problems.DataAnalysis.Symbolic;
 using System.Collections.Generic;
+using System.IO;
 using System.Linq;
 
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
-  [StorableType("A9AE93F0-E589-44D0-AD34-0E3AA358D669")]
   [Item("TreeModelMap", "A map of models of models of models")]
+  [StorableType("E4AB04B9-FD5D-47EE-949D-243660754F3A")]
   public class EMMMapTreeModel : EMMMapBase<ISymbolicExpressionTree> {
     #region conctructors
@@ -62 +63 @@
       CreateMap(random, k);
     }
+    public EMMMapTreeModel(IRandom random, IEnumerable<ISymbolicExpressionTree> trees) : this(1) {
+      ModelSet = trees.ToList();
+      string input = File.ReadAllText("Map.txt");
+
+      int i = 0;
+      foreach (var row in input.Split('\n')) {
+        Map.Add(new List<int>());
+        foreach (var col in row.Trim().Split(' ')) {
+          Map[i].Add(int.Parse(col.Trim()));
+        }
+        i++;
+      }
+      K = Map.Count;
+      MapPreparation();
+    }
     public override IDeepCloneable Clone(Cloner cloner) {
       return new EMMMapTreeModel(this, cloner);
@@ -75 +91 @@
       }
     }
-    override public void CreateMap(IRandom random, int k) {
+    override protected void CreateMap(IRandom random, int k) {
       K = k;
       //Clusterization
@@ -96 +112 @@
       }
     }
+    protected void MapPreparation() {
+      for (int i = 0; i < Map.Count; i++) {
+        for (int j = 0; j < Map[i].Count; j++) {
+          ClusterNumber.Add(0);
+        }
+      }
+      for (int i = 0; i < Map.Count; i++) {
+        for (int j = 0; j < Map[i].Count; j++) {
+          ClusterNumber[Map[i][j]] = i;
+        }
+      }
+    }
     #endregion
     #region Dialog with surroudings
@@ -103 +131 @@
       return (ISymbolicExpressionTree)ModelSet[treeNumber].Clone();
     }
+    public string[] MapToString() {
+      string[] s;
+      s = new string[K];
+      for (int i = 0; i < K; i++) {
+        s[i] = "";
+        for (int j = 0; j < Map[i].Count; j++) {
+          s[i] += Map[i][j].ToString();
+          s[i] += " ";
+        }
+      }
+      return s;
+    }
+    public string[] MapToSee() {
+      var fmt = new InfixExpressionFormatter();
+      string[] s;
+      s = new string[(ModelSet.Count) + 1];
+      s[0] = "ClusterNumber" + "," + "Modfelnumber" + "," + "Model";
+      for (int i = 1; i < ((ModelSet.Count) + 1); i++) {
+        s[i] = ClusterNumber[i - 1].ToString() + "," + (i - 1).ToString() + "," + fmt.Format(ModelSet[i - 1]);
+      }
+      return s;
+    }
 
     #endregion

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMMutators.cs

@@ -32 +32 @@
 
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
-  [StorableType("92D37E9F-8726-4524-AF8F-F3787641F7B9")]
   [Item("EMMChangeNodeTypeManipulation", "Selects a random tree node and changes the symbol.")]
+  [StorableType("990D3946-7F06-48B4-B8DB-F8E308D6304D")]
   public sealed class EMMMutators : SymbolicExpressionTreeManipulator {
     private const int MAX_TRIES = 100;
@@ -125 +125 @@
             int p = random.Next(map.Count);
             if (child is TreeModelTreeNode chNode) // in real life never bacame true. It need some cheking
-              p = chNode.ClusterNumer;
+            { p = chNode.ClusterNumer; }
             treeNode.TreeNumber = map[p].SampleRandom(random).Value;
             treeNode.Tree = (ISymbolicExpressionTree)modelSet[treeNode.TreeNumber].Clone();
-            treeNode.Tree.Root.ShakeLocalParameters(random, 0.5);
+            treeNode.SetLocalParameters(random, 0.5);
           } else
             newNode.ResetLocalParameters(random);

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMSolution.cs

@@ -26 +26 @@
 // Can be deleted potnetinaly
 namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
+  [StorableType("AB38211D-5F52-4420-A606-1C3CB58BA27C")]
   public interface IEMMSolution : IItem {
     IItem Individual { get; set; }
@@ -31 +32 @@
   }
   [Item("EMMSolution", "Represents a solution inside the EMM population")]
-  [StorableType("708BDF29-AD3F-4AFC-83AE-551A27FF45A0")]
+  [StorableType("C0E63430-5000-4592-BBE4-2D3E0EE1AE3F")]
   public class EMMSolution : Item, IEMMSolution {
     [Storable]
@@ -69 +70 @@
   }
   [Item("EMMSolution", "Represents a solution inside the EMM population")]
-  [StorableType("36929CD1-63A5-4270-8C65-2A8177BCA0AE")]
+  [StorableType("559EA31B-2263-4233-900C-EC62120EE580")]
   public class EMMSolution<T> : EMMSolution where T : class, IItem {
     public new T Individual {

branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/Plugin.cs

@@ -26 +26 @@
   /// Plugin class for HeuristicLab.Algorithms.EMMAlgorithm plugin.
   /// </summary>
-  [Plugin("HeuristicLab.Algorithms.EMMAlgorithm", "3.3.15.16565")]
+  [Plugin("HeuristicLab.Algorithms.EMMAlgorithm", "3.3.15.16722")]
   [PluginFile("HeuristicLab.Algorithms.EMMAlgorithm-3.3.dll", PluginFileType.Assembly)]
   [PluginDependency("HeuristicLab.Analysis", "3.3")]

branches/2988_ModelsOfModels2/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisVariableFrequencyAnalyzer.cs

@@ -20 +20 @@
 #endregion
 
-using System;
-using System.Collections.Generic;
-using System.Linq;
+using HEAL.Attic;
 using HeuristicLab.Analysis;
 using HeuristicLab.Common;
@@ -30 +28 @@
 using HeuristicLab.Optimization;
 using HeuristicLab.Parameters;
-using HEAL.Attic;
+using System;
+using System.Collections.Generic;
+using System.Linq;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {

branches/2988_ModelsOfModels2/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/HeuristicLab.Problems.DataAnalysis.Symbolic-3.4.csproj

@@ -216 +216 @@
     <Compile Include="Analyzers\MinAverageMaxSymbolicExpressionTreeVariablesNumberAnalyzer.cs" />
     <Compile Include="Analyzers\MinAverageMaxSymbolicExpressionTreeComplexcityAnalyzer.cs" />
+    <Compile Include="Analyzers\ModelClustersFrequencyAnalyzer.cs" />
+    <Compile Include="Analyzers\ModelsFrequencyAnalyzer.cs" />
     <Compile Include="Analyzers\SymbolicDataAnalysisBottomUpDiversityAnalyzer.cs" />
     <Compile Include="Analyzers\SymbolicDataAnalysisBuildingBlockAnalyzer.cs" />
@@ -232 +234 @@
       <SubType>Code</SubType>
     </Compile>
+    <Compile Include="Analyzers\SymbolicDataAnalysisVariableFrequencyAnalyzer.cs" />
     <Compile Include="Converters\LinearModelToTreeConverter.cs" />
     <Compile Include="Converters\TreeSimplifier.cs" />
@@ -260 +263 @@
     <Compile Include="SymbolicDataAnalysisModelComplexityCalculator.cs" />
     <Compile Include="SymbolicDataAnalysisExpressionPruningOperator.cs" />
-    <Compile Include="Analyzers\SymbolicDataAnalysisVariableFrequencyAnalyzer.cs" />
     <Compile Include="Analyzers\SymbolicDataAnalysisAlleleFrequencyAnalyzer.cs" />
     <Compile Include="Creators\MultiSymbolicDataAnalysisExpressionCreator.cs" />

branches/2988_ModelsOfModels2/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/ModelTreeNode.cs

@@ -25 +25 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Random;
-using System.Collections.Generic;
-
+using System.Linq;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
-  [StorableType("38C37AED-5B9D-488E-8785-D8FF541D9B4C")]
+  [StorableType("44B25E73-6C4D-404C-93E5-42B7D2807CF7")]
   public sealed class TreeModelTreeNode : SymbolicExpressionTreeTerminalNode {
     public new TreeModel Symbol {
@@ -71 +70 @@
       get { return true; }
     }
-    //public override void ResetLocalParameters(IRandom random, List<ISymbolicExpressionTree> modelSet, List<List<int>> map, List<int> cLusterNumber) {
-    //  base.ResetLocalParameters(random);
-    //  if (ClusterNumer < 0) {
-    //    //Tree = map.NewModelForInizializtion(ClusterNumer, random);
-    //    var selectedNodelNumber = random.Next(modelSet.Count);
-    //    ClusterNumer = cLusterNumber[selectedNodelNumber];
-    //    TreeNumber = selectedNodelNumber;
-    //    Tree = (ISymbolicExpressionTree)modelSet[selectedNodelNumber].Clone();
-    //  } else {
-    //    //New Model For Mutation Adding
-    //    var selectedNodelNumber = random.Next(map[ClusterNumer].Count);
-    //    TreeNumber = selectedNodelNumber;
-    //    Tree = (ISymbolicExpressionTree)modelSet[map[ClusterNumer][selectedNodelNumber]].Clone();
-    //  }
-
-    //}
-
     public override void ShakeLocalParameters(IRandom random, double shakingFactor) {
       base.ShakeLocalParameters(random, shakingFactor);
-      List<ISymbolicExpressionTreeNode> parametricNodes = new List<ISymbolicExpressionTreeNode>();
-      Tree.Root.ForEachNodePostfix(n => {
-        if (n.HasLocalParameters) parametricNodes.Add(n);
-      });
-      if (parametricNodes.Count > 0) {
+      var parametricNodes = Tree.IterateNodesPrefix().Where(x => x.HasLocalParameters).ToList();
+      if (parametricNodes.Any()) {
         var selectedPoint = parametricNodes.SampleRandom(random);
-        selectedPoint.ShakeLocalParameters(random, shakingFactor);
+        if (selectedPoint is VariableTreeNode variableTreeNode) {
+          var symbol = variableTreeNode.Symbol;
+          variableTreeNode.Weight = NormalDistributedRandom.NextDouble(random, symbol.WeightManipulatorMu, symbol.WeightManipulatorSigma);
+        } else {
+          selectedPoint.ShakeLocalParameters(random, shakingFactor);
+        }
+
       }
     }
-
+    public void SetLocalParameters(IRandom random, double shakingFactor) {
+      foreach (var node in Tree.IterateNodesPrefix().Where(x => x.HasLocalParameters)) {
+        if (node is VariableTreeNode variableTreeNode) {
+          var symbol = variableTreeNode.Symbol;
+          variableTreeNode.Weight = NormalDistributedRandom.NextDouble(random, symbol.WeightManipulatorMu, symbol.WeightManipulatorSigma);
+        } else {
+          node.ResetLocalParameters(random);
+        }
+      }
+    }
     public override IDeepCloneable Clone(Cloner cloner) {
       return new TreeModelTreeNode(this, cloner);
@@ -106 +100 @@
     public override string ToString() {
 
-      string s = "model" +" " +TreeNumber.ToString()+"\n " + new InfixExpressionFormatter().Format(tree);
+      string s = "model" + " " + TreeNumber.ToString() + "\n " + new InfixExpressionFormatter().Format(tree);
       return s;
     }

branches/2988_ModelsOfModels2/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/TreeModel.cs

@@ -20 +20 @@
 #endregion
 
-using System;
-using System.Collections.Generic;
+using HEAL.Attic;
 using HeuristicLab.Common;
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
-using HEAL.Attic;
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
-  [StorableType("F8A6AD96-28D9-4BEC-8392-8B7BA824B085")]
+  [StorableType("6F628649-7C71-49F3-862A-0BAB4BADF964")]
   public sealed class TreeModel : Symbol {
 
@@ -39 +37 @@
     [StorableConstructor]
     private TreeModel(StorableConstructorFlag _) : base(_) { }
-    private TreeModel(TreeModel original, Cloner cloner) : base(original, cloner) {   }
-    public TreeModel() : base("TreeModel", "Represents a TreeModel.") {    }
+    private TreeModel(TreeModel original, Cloner cloner) : base(original, cloner) { }
+    public TreeModel() : base("TreeModel", "Represents a TreeModel.") { }
     public override ISymbolicExpressionTreeNode CreateTreeNode() {
-      return new TreeModelTreeNode(this); }  
+      return new TreeModelTreeNode(this);
+    }
 
     public override IDeepCloneable Clone(Cloner cloner) {