Changeset 15973 for branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis

Timestamp:

06/28/18 11:13:37 (7 years ago)

Author:

gkronber

Message:

#2522: merged trunk changes from r13402:15972 to branch resolving conflicts where necessary

Location:

branches/2522_RefactorPluginInfrastructure

Files:

• . (modified) (2 props)
• HeuristicLab.Problems.DataAnalysis (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/Models/ConstantTimeSeriesPrognosisModel.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/Models/TimeSeriesPrognosisAutoRegressiveModel.cs (modified) (6 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblem.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblemData.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisResults.cs (modified) (5 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolution.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionBase.cs (modified) (3 diffs)

branches/2522_RefactorPluginInfrastructure

@@ -24 +24 @@
 protoc.exe
 obj
+.vs

@@ -24 +24 @@
 protoc.exe
 obj
+.vs

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/Models/ConstantTimeSeriesPrognosisModel.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -39 +39 @@
     }
 
-    public ConstantTimeSeriesPrognosisModel(double constant) : base(constant) { }
+    public ConstantTimeSeriesPrognosisModel(double constant, string targetVariable) : base(constant, targetVariable) { }
 
     public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/Models/TimeSeriesPrognosisAutoRegressiveModel.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -30 +30 @@
   [StorableClass]
   [Item("Autoregressive TimeSeries Model", "A linear autoregressive time series model used to predict future values.")]
-  public class TimeSeriesPrognosisAutoRegressiveModel : NamedItem, ITimeSeriesPrognosisModel {
+  public class TimeSeriesPrognosisAutoRegressiveModel : RegressionModel, ITimeSeriesPrognosisModel {
+    public override IEnumerable<string> VariablesUsedForPrediction {
+      get { return new[] { TargetVariable }; } 
+    }
+
     [Storable]
     public double[] Phi { get; private set; }
     [Storable]
     public double Constant { get; private set; }
-    [Storable]
-    public string TargetVariable { get; private set; }
 
     public int TimeOffset { get { return Phi.Length; } }
@@ -46 +48 @@
       this.Phi = (double[])original.Phi.Clone();
       this.Constant = original.Constant;
-      this.TargetVariable = original.TargetVariable;
     }
     public override IDeepCloneable Clone(Cloner cloner) {
@@ -52 +53 @@
     }
     public TimeSeriesPrognosisAutoRegressiveModel(string targetVariable, double[] phi, double constant)
-      : base("AR(1) Model") {
+      : base(targetVariable, "AR(1) Model") {
       Phi = (double[])phi.Clone();
       Constant = constant;
-      TargetVariable = targetVariable;
     }
 
@@ -91 +91 @@
     }
 
-    public IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
+    public override IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
       var targetVariables = dataset.GetReadOnlyDoubleValues(TargetVariable);
       foreach (int row in rows) {
@@ -111 +111 @@
       return new TimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
     }
-    public IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
+    public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
       throw new NotSupportedException();
     }

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblem.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisProblemData.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisResults.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -373 +373 @@
       //mean model
       double trainingMean = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices).Average();
-      var meanModel = new ConstantModel(trainingMean);
+      var meanModel = new ConstantModel(trainingMean, problemData.TargetVariable);
 
       //AR1 model
@@ -395 +395 @@
       PrognosisTrainingMeanAbsoluteError = errorState == OnlineCalculatorError.None ? trainingMAE : double.NaN;
       double trainingR = OnlinePearsonsRCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
-      PrognosisTrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR*trainingR : double.NaN;
+      PrognosisTrainingRSquared = errorState == OnlineCalculatorError.None ? trainingR * trainingR : double.NaN;
       double trainingRelError = OnlineMeanAbsolutePercentageErrorCalculator.Calculate(originalTrainingValues, estimatedTrainingValues, out errorState);
       PrognosisTrainingRelativeError = errorState == OnlineCalculatorError.None ? trainingRelError : double.NaN;
@@ -431 +431 @@
       PrognosisTestMeanAbsoluteError = errorState == OnlineCalculatorError.None ? testMAE : double.NaN;
       double testR = OnlinePearsonsRCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);
-      PrognosisTestRSquared = errorState == OnlineCalculatorError.None ? testR*testR : double.NaN;
+      PrognosisTestRSquared = errorState == OnlineCalculatorError.None ? testR * testR : double.NaN;
       double testRelError = OnlineMeanAbsolutePercentageErrorCalculator.Calculate(originalTestValues, estimatedTestValues, out errorState);
       PrognosisTestRelativeError = errorState == OnlineCalculatorError.None ? testRelError : double.NaN;
@@ -448 +448 @@
         //mean model
         double trainingMean = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, problemData.TrainingIndices).Average();
-        var meanModel = new ConstantModel(trainingMean);
+        var meanModel = new ConstantModel(trainingMean, problemData.TargetVariable);
 
         //AR1 model

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolution.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -21 +21 @@
 
 using System.Collections.Generic;
+using System.Linq;
 using HeuristicLab.Common;
 using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
@@ -43 +44 @@
       return Model.GetPrognosedValues(ProblemData.Dataset, rows, horizons);
     }
+
+    public override IEnumerable<double> PrognosedTestValues {
+      get {
+        return Model.GetPrognosedValues(ProblemData.Dataset, ProblemData.TestIndices.Take(1),
+          new int[] { ProblemData.TestIndices.Count() }).First();
+      }
+    }
   }
 }

branches/2522_RefactorPluginInfrastructure/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionBase.cs

@@ -1 +1 @@
 #region License Information
 /* HeuristicLab
- * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
+ * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
  *
  * This file is part of HeuristicLab.
@@ -64 +64 @@
     }
 
+    public abstract IEnumerable<double> PrognosedTestValues { get; }
     public abstract IEnumerable<IEnumerable<double>> GetPrognosedValues(IEnumerable<int> rows, IEnumerable<int> horizon);
 
@@ -150 +151 @@
       OnlineCalculatorError errorState;
       double trainingMean = ProblemData.TrainingIndices.Any() ? ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices).Average() : double.NaN;
-      var meanModel = new ConstantModel(trainingMean);
+      var meanModel = new ConstantModel(trainingMean, ProblemData.TargetVariable);
 
       double alpha, beta;

@@ -24 +24 @@
 protoc.exe
 obj
+.vs