Changeset 7750 for branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

Timestamp:

04/23/12 16:50:08 (13 years ago)

Author:

sforsten

Message:

#1784:

• merged Problems.DataAnalysis r7273:7748 from trunk
• prepared SymbolicClassificationSingleObjectiveProblem and SymbolicRegressionSingleObjectiveProblem to load and export problem instances

File:

• branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs (modified) (4 diffs)

branches/ProblemInstancesRegressionAndClassification/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectiveProblem.cs

@@ -20 +20 @@
 #endregion
 
+using System;
+using System.Collections.Generic;
 using System.Linq;
 using HeuristicLab.Common;
@@ -25 +27 @@
 using HeuristicLab.Parameters;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
+using HeuristicLab.Problems.Instances;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
@@ -30 +33 @@
   [StorableClass]
   [Creatable("Problems")]
-  public class SymbolicRegressionSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IRegressionProblemData, ISymbolicRegressionSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IRegressionProblem {
+  public class SymbolicRegressionSingleObjectiveProblem : SymbolicDataAnalysisSingleObjectiveProblem<IRegressionProblemData, ISymbolicRegressionSingleObjectiveEvaluator, ISymbolicDataAnalysisSolutionCreator>, IRegressionProblem,
+    IProblemInstanceConsumer<RegressionData>, IProblemInstanceExporter<RegressionData> {
     private const double PunishmentFactor = 10;
     private const int InitialMaximumTreeDepth = 8;
@@ -116 +120 @@
       ProblemData = problemData;
     }
+
+    public void Load(RegressionData data) {
+      Name = data.Name;
+      Description = data.Description;
+      Dataset dataset = new Dataset(data.InputVariables, data.Values);
+      ProblemData = new RegressionProblemData(dataset, data.AllowedInputVariables, data.TargetVariable);
+      ProblemData.TrainingPartition.Start = data.TrainingPartitionStart;
+      ProblemData.TrainingPartition.End = data.TrainingPartitionEnd;
+      ProblemData.TestPartition.Start = data.TestPartitionStart;
+      ProblemData.TestPartition.End = data.TestPartitionEnd;
+      OnReset();
+    }
+
+    public RegressionData Export() {
+      if (!ProblemData.InputVariables.Count.Equals(ProblemData.Dataset.DoubleVariables.Count()))
+        throw new ArgumentException("Not all input variables are double variables! (Export only works with double variables)");
+
+      RegressionData regData = new RegressionData();
+      regData.Name = Name;
+      regData.Description = Description;
+      regData.TargetVariable = ProblemData.TargetVariable;
+      regData.InputVariables = ProblemData.InputVariables.Select(x => x.Value).ToArray();
+      regData.AllowedInputVariables = ProblemData.AllowedInputVariables.ToArray();
+      regData.TrainingPartitionStart = ProblemData.TrainingPartition.Start;
+      regData.TrainingPartitionEnd = ProblemData.TrainingPartition.End;
+      regData.TestPartitionStart = ProblemData.TestPartition.Start;
+      regData.TestPartitionEnd = ProblemData.TestPartition.End;
+
+      List<List<double>> data = new List<List<double>>();
+      foreach (var variable in ProblemData.Dataset.DoubleVariables) {
+        data.Add(ProblemData.Dataset.GetDoubleValues(variable).ToList());
+      }
+      regData.Values = Transformer.Transformation(data);
+
+      return regData;
+    }
   }
 }