Changeset 17159 for stable

Timestamp:

07/23/19 20:33:58 (5 years ago)

Author:

gkronber

Message:

#2847: merged r16853, r16855, r16856, r16858, r17078, r17079:17085, r17139 from trunk to stable

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab 3.3.sln (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis.DecisionTrees (copied) (copied from trunk/HeuristicLab.Algorithms.DataAnalysis.DecisionTrees)
• HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/LeafTypes/LeafBase.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/Pruning/ComplexityPruning.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/Splitting/SplitterBase.cs (modified) (2 diffs)
• HeuristicLab.Algorithms.DataAnalysis/3.4 (modified) (1 prop)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression (copied) (copied from trunk/HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/Interfaces (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafModels (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/LeafTypes (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/M5Regression.cs (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/M5Utilities (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/MetaModels (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/Pruning (deleted)
• HeuristicLab.Algorithms.DataAnalysis/3.4/M5Regression/Splitting (deleted)
• HeuristicLab.Problems.DataAnalysis.Symbolic (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/LinearModelToTreeConverter.cs (modified) (1 diff)

stable/HeuristicLab 3.3.sln

@@ -465 +465 @@
 EndProject
 Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.ExactOptimization.Views-3.3", "HeuristicLab.ExactOptimization.Views\3.3\HeuristicLab.ExactOptimization.Views-3.3.csproj", "{D1D69043-17E6-4B8C-BF41-0799C7E56032}"
+EndProject
+Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "HeuristicLab.Algorithms.DataAnalysis.DecisionTrees-3.4", "HeuristicLab.Algorithms.DataAnalysis.DecisionTrees\3.4\HeuristicLab.Algorithms.DataAnalysis.DecisionTrees-3.4.csproj", "{541A53F3-E6A7-402F-91BB-D76041CDD9FD}"
 EndProject
 Global
@@ -2260 +2262 @@
     {D1D69043-17E6-4B8C-BF41-0799C7E56032}.Release|x64.Build.0 = Release|x64
     {D1D69043-17E6-4B8C-BF41-0799C7E56032}.Release|x86.ActiveCfg = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|Any CPU.Build.0 = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|x64.ActiveCfg = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|x64.Build.0 = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|x86.ActiveCfg = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Debug|x86.Build.0 = Debug|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|Any CPU.ActiveCfg = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|Any CPU.Build.0 = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|x64.ActiveCfg = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|x64.Build.0 = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|x86.ActiveCfg = Release|Any CPU
+    {541A53F3-E6A7-402F-91BB-D76041CDD9FD}.Release|x86.Build.0 = Release|Any CPU
   EndGlobalSection
   GlobalSection(SolutionProperties) = preSolution

stable/HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/LeafTypes/LeafBase.cs

@@ -112 +112 @@
     public class LeafBuildingState : Item {
       [Storable]
-      public Queue<RegressionNodeModel> nodeQueue = new Queue<RegressionNodeModel>();
+      private RegressionNodeModel[] storableNodeQueue { get { return nodeQueue.ToArray(); } set { nodeQueue = new Queue<RegressionNodeModel>(value); } }
+      public Queue<RegressionNodeModel> nodeQueue;
       [Storable]
-      public Queue<IReadOnlyList<int>> trainingRowsQueue = new Queue<IReadOnlyList<int>>();
+      private IReadOnlyList<int>[] storabletrainingRowsQueue { get { return trainingRowsQueue.ToArray(); } set { trainingRowsQueue = new Queue<IReadOnlyList<int>>(value); } }
+      public Queue<IReadOnlyList<int>> trainingRowsQueue;
 
       //State.Code values denote the current action (for pausing)
@@ -130 +132 @@
         Code = original.Code;
       }
-      public LeafBuildingState() { }
+      public LeafBuildingState() {
+        nodeQueue = new Queue<RegressionNodeModel>();
+        trainingRowsQueue = new Queue<IReadOnlyList<int>>();
+      }
       public override IDeepCloneable Clone(Cloner cloner) {
         return new LeafBuildingState(this, cloner);

stable/HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/Pruning/ComplexityPruning.cs

@@ -204 +204 @@
     public class PruningState : Item {
       [Storable]
-      public IDictionary<RegressionNodeModel, int> modelComplexities = new Dictionary<RegressionNodeModel, int>();
-      [Storable]
-      public IDictionary<RegressionNodeModel, int> nodeComplexities = new Dictionary<RegressionNodeModel, int>();
-      [Storable]
-      public IDictionary<RegressionNodeModel, int> pruningSizes = new Dictionary<RegressionNodeModel, int>();
-      [Storable]
-      public IDictionary<RegressionNodeModel, double> modelErrors = new Dictionary<RegressionNodeModel, double>();
-
-      [Storable]
-      public Queue<RegressionNodeModel> nodeQueue = new Queue<RegressionNodeModel>();
-      [Storable]
-      public Queue<IReadOnlyList<int>> trainingRowsQueue = new Queue<IReadOnlyList<int>>();
-      [Storable]
-      public Queue<IReadOnlyList<int>> pruningRowsQueue = new Queue<IReadOnlyList<int>>();
+      public IDictionary<RegressionNodeModel, int> modelComplexities;
+      [Storable]
+      public IDictionary<RegressionNodeModel, int> nodeComplexities;
+      [Storable]
+      public IDictionary<RegressionNodeModel, int> pruningSizes;
+      [Storable]
+      public IDictionary<RegressionNodeModel, double> modelErrors;
+
+      [Storable]
+      private RegressionNodeModel[] storableNodeQueue { get { return nodeQueue.ToArray(); } set { nodeQueue = new Queue<RegressionNodeModel>(value); } }
+      public Queue<RegressionNodeModel> nodeQueue;
+      [Storable]
+      private IReadOnlyList<int>[] storabletrainingRowsQueue { get { return trainingRowsQueue.ToArray(); } set { trainingRowsQueue = new Queue<IReadOnlyList<int>>(value); } }
+      public Queue<IReadOnlyList<int>> trainingRowsQueue;
+      [Storable]
+      private IReadOnlyList<int>[] storablepruningRowsQueue { get { return pruningRowsQueue.ToArray(); } set { pruningRowsQueue = new Queue<IReadOnlyList<int>>(value); } }
+      public Queue<IReadOnlyList<int>> pruningRowsQueue;
 
       //State.Code values denote the current action (for pausing)
@@ -242 +245 @@
         Code = original.Code;
       }
-      public PruningState() { }
+      public PruningState() {
+        modelComplexities = new Dictionary<RegressionNodeModel, int>();
+        nodeComplexities = new Dictionary<RegressionNodeModel, int>();
+        pruningSizes = new Dictionary<RegressionNodeModel, int>();
+        modelErrors = new Dictionary<RegressionNodeModel, double>();
+        nodeQueue = new Queue<RegressionNodeModel>();
+        trainingRowsQueue = new Queue<IReadOnlyList<int>>();
+        pruningRowsQueue = new Queue<IReadOnlyList<int>>();
+      }
       public override IDeepCloneable Clone(Cloner cloner) {
         return new PruningState(this, cloner);

stable/HeuristicLab.Algorithms.DataAnalysis.DecisionTrees/3.4/Splitting/SplitterBase.cs

@@ -112 +112 @@
     [StorableType("BC1149FD-370E-4F3A-92F5-6E519736D09A")]
     public class SplittingState : Item {
+      public Queue<RegressionNodeModel> nodeQueue;
       [Storable]
-      public Queue<RegressionNodeModel> nodeQueue = new Queue<RegressionNodeModel>();
+      private RegressionNodeModel[] storableNodeQueue {
+        get { return nodeQueue.ToArray(); }
+        set { nodeQueue = new Queue<RegressionNodeModel>(value); }
+      }
+
+      public Queue<IReadOnlyList<int>> trainingRowsQueue;
       [Storable]
-      public Queue<IReadOnlyList<int>> trainingRowsQueue = new Queue<IReadOnlyList<int>>();
+      private IReadOnlyList<int>[] storableTrainingRowsQueue {
+        get { return trainingRowsQueue.ToArray(); }
+        set { trainingRowsQueue = new Queue<IReadOnlyList<int>>(value); }
+      }
+
 
       //State.Code values denote the current action (for pausing)
@@ -131 +141 @@
         Code = original.Code;
       }
-      public SplittingState() { }
+      public SplittingState() : base() {
+        nodeQueue = new Queue<RegressionNodeModel>();
+        trainingRowsQueue = new Queue<IReadOnlyList<int>>();
+      }
       public override IDeepCloneable Clone(Cloner cloner) {
         return new SplittingState(this, cloner);

stable/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Converters/LinearModelToTreeConverter.cs

@@ -38 +38 @@
       double @const = 0) {
 
-      if (factorCoefficients.Length == 0 && coefficients.Length == 0) throw new ArgumentException();
+      if (factorCoefficients.Length == 0 && coefficients.Length == 0 && @const==0) throw new ArgumentException();
+
+      // Combine both trees
+      ISymbolicExpressionTreeNode add = (new Addition()).CreateTreeNode();
 
       // Create tree for double variables
-      ISymbolicExpressionTree tree = null;      
       if (coefficients.Length > 0) {
-        tree = CreateTree(variableNames, new int[variableNames.Length], coefficients, @const);
-        if (factorCoefficients.Length == 0) return tree;
+        var varTree = CreateTree(variableNames, new int[variableNames.Length], coefficients);
+        foreach (var varNode in varTree.IterateNodesPrefix().OfType<VariableTreeNode>())
+          add.AddSubtree(varNode);
       }
 
       // Create tree for string variables
-      ISymbolicExpressionTree factorTree = null;      
       if (factorCoefficients.Length > 0) {
-        factorTree = CreateTree(factors, factorCoefficients, @const);
-        if (tree == null) return factorTree;  
+        var factorTree = CreateTree(factors, factorCoefficients);
+        foreach (var binFactorNode in factorTree.IterateNodesPrefix().OfType<BinaryFactorVariableTreeNode>())
+          add.AddSubtree(binFactorNode);
       }
 
-      // Combine both trees
-      ISymbolicExpressionTreeNode add = tree.Root.GetSubtree(0).GetSubtree(0);
-      foreach (var binFactorNode in factorTree.IterateNodesPrefix().OfType<BinaryFactorVariableTreeNode>())
-        add.InsertSubtree(add.SubtreeCount - 1, binFactorNode);
+      if (@const!=0.0) {
+        ConstantTreeNode cNode = (ConstantTreeNode)new Constant().CreateTreeNode();
+        cNode.Value = @const;
+        add.AddSubtree(cNode);
+      }
+
+      ISymbolicExpressionTree tree = new SymbolicExpressionTree(new ProgramRootSymbol().CreateTreeNode());
+      ISymbolicExpressionTreeNode startNode = new StartSymbol().CreateTreeNode();
+      tree.Root.AddSubtree(startNode);
+      startNode.AddSubtree(add);
       return tree;
-
-      throw new ArgumentException();
     }