Changeset 15280 for branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic

Timestamp:

07/23/17 00:52:14 (7 years ago)

Author:

abeham

Message:

#2258: merged r13329:14000 from trunk into branch

Location:

branches/Async

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Creators/MultiSymbolicDataAnalysisExpressionCreator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionContextAwareCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDepthConstrainedCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDeterministicBestCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionProbabilisticFunctionalCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionSemanticSimilarityCrossover.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisMultiObjectiveEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Formatters/SymbolicDataAnalysisExpressionLatexFormatter.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModel.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/VariableCondition.cs (modified) (1 diff)

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Creators/MultiSymbolicDataAnalysisExpressionCreator.cs

@@ -35 +35 @@
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Creators {
+  [StorableClass]
   public class MultiSymbolicDataAnalysisExpressionCreator : StochasticMultiBranch<ISymbolicDataAnalysisSolutionCreator>,
     ISymbolicDataAnalysisSolutionCreator,

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionContextAwareCrossover.cs

@@ -34 +34 @@
                                  "- Randomly choose a node N from P1\n" +
                                  "- Test all crossover points from P0 to determine the best location for N to be inserted")]
+  [StorableClass]
   public sealed class SymbolicDataAnalysisExpressionContextAwareCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     [StorableConstructor]

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionCrossover.cs

@@ -32 +32 @@
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
+  [StorableClass]
   public abstract class SymbolicDataAnalysisExpressionCrossover<T> : SymbolicExpressionTreeCrossover, ISymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDepthConstrainedCrossover.cs

@@ -36 +36 @@
                                      "- Standard (mid 50% of the tree)\n" +
                                      "- LowLevel (lower 25% of the tree)")]
+  [StorableClass]
   public sealed class SymbolicDataAnalysisExpressionDepthConstrainedCrossover<T> :
     SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDeterministicBestCrossover.cs

@@ -34 +34 @@
                                       "- Randomly choose a crossover point C from P0\n" +
                                       "- Test all nodes from P1 to determine the one that produces the best child when inserted at place C in P0")]
+  [StorableClass]
   public sealed class SymbolicDataAnalysisExpressionDeterministicBestCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     [StorableConstructor]

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionProbabilisticFunctionalCrossover.cs

@@ -36 +36 @@
                                             "\t\tD(N,M) = 0.5 * ( abs(max(N) - max(M)) + abs(min(N) - min(M)) )\n" +
                                             "- Make a probabilistic weighted choice of node M from P1, based on the inversed and normalized behavioral distance")]
+  [StorableClass]
   public sealed class SymbolicDataAnalysisExpressionProbabilisticFunctionalCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     [StorableConstructor]

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionSemanticSimilarityCrossover.cs

@@ -37 +37 @@
                                        "- Find the first node M that satisfies the semantic similarity criteria\n" +
                                        "- Swap N for M and return P0")]
+  [StorableClass]
   public sealed class SymbolicDataAnalysisExpressionSemanticSimilarityCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
     private const string SemanticSimilarityRangeParameterName = "SemanticSimilarityRange";

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisEvaluator.cs

@@ -93 +93 @@
     public SymbolicDataAnalysisEvaluator()
       : base() {
-      Parameters.Add(new ValueLookupParameter<IRandom>(RandomParameterName, "The random generator to use."));
-      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree."));
-      Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic data analysis solution encoded as a symbolic expression tree."));
-      Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
-      Parameters.Add(new ValueLookupParameter<IntRange>(EvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated."));
-      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees."));
-      Parameters.Add(new ValueLookupParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index."));
-      Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the individual should be linearly scaled before evaluating."));
-      Parameters.Add(new ValueLookupParameter<StringValue>(ValidRowIndicatorParameterName, "An indicator variable in the data set that specifies which rows should be evaluated (those for which the indicator <> 0) (optional)."));
+      Parameters.Add(new ValueLookupParameter<IRandom>(RandomParameterName, "The random generator to use.") { Hidden = true });
+      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree.") { Hidden = true });
+      Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic data analysis solution encoded as a symbolic expression tree.") { Hidden = true });
+      Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated.") { Hidden = true });
+      Parameters.Add(new ValueLookupParameter<IntRange>(EvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated.") { Hidden = true });
+      Parameters.Add(new ValueLookupParameter<DoubleLimit>(EstimationLimitsParameterName, "The upper and lower limit that should be used as cut off value for the output values of symbolic data analysis trees.") { Hidden = true });
+      Parameters.Add(new ValueLookupParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index.") { Hidden = true });
+      Parameters.Add(new LookupParameter<BoolValue>(ApplyLinearScalingParameterName, "Flag that indicates if the individual should be linearly scaled before evaluating.") { Hidden = true });
+      Parameters.Add(new ValueLookupParameter<StringValue>(ValidRowIndicatorParameterName, "An indicator variable in the data set that specifies which rows should be evaluated (those for which the indicator <> 0) (optional).") { Hidden = true });
     }
 

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Evaluators/SymbolicDataAnalysisMultiObjectiveEvaluator.cs

@@ -24 +24 @@
 using HeuristicLab.Core;
 using HeuristicLab.Data;
+using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
-using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
+  [StorableClass]
   public abstract class SymbolicDataAnalysisMultiObjectiveEvaluator<T> : SymbolicDataAnalysisEvaluator<T>, ISymbolicDataAnalysisMultiObjectiveEvaluator<T>
    where T : class, IDataAnalysisProblemData {

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Formatters/SymbolicDataAnalysisExpressionLatexFormatter.cs

@@ -403 +403 @@
             var constStr = string.Format(System.Globalization.NumberFormatInfo.InvariantInfo, "{0:G5}", constant);
             if (!constStr.Contains(".")) constStr = constStr + ".0";
-            constStr = constStr.Replace(".", "\\negthickspace&.");  // fix problem in rendering of aligned expressions
+            constStr = constStr.Replace(".", "&.");  // fix problem in rendering of aligned expressions
             strBuilder.Append("c_{" + i + "}& = & " + constStr);
             strBuilder.Append(@"\\");

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisModel.cs

@@ -21 +21 @@
 
 using System;
+using System.Collections.Generic;
 using System.Drawing;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Core;
@@ -56 +58 @@
       get { return interpreter; }
     }
+
+    public IEnumerable<string> VariablesUsedForPrediction {
+      get {
+        var variables =
+          SymbolicExpressionTree.IterateNodesPrefix()
+            .OfType<VariableTreeNode>()
+            .Select(x => x.VariableName)
+            .Distinct();
+        var variableConditions = SymbolicExpressionTree.IterateNodesPrefix()
+          .OfType<VariableConditionTreeNode>().Select(x => x.VariableName).Distinct();
+
+        return variables.Union(variableConditions).OrderBy(x => x);
+      }
+    }
+
     #endregion
 
@@ -160 +177 @@
     }
     #endregion
+
   }
 }

branches/Async/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Symbols/VariableCondition.cs

@@ -100 +100 @@
         allVariableNames.Clear();
         allVariableNames.AddRange(value);
-        VariableNames = value;
       }
     }