Changeset 14939 for stable

Timestamp:

05/05/17 20:05:24 (8 years ago)

Author:

gkronber

Message:

#2529: merged r14422 and r14423 from trunk to stable

Location:

stable

Files:

• . (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisExpressionTreeInterpreter.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Views (modified) (1 prop)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/HeuristicLab.Problems.DataAnalysis.Views-3.4.csproj (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisLineChartView.Designer.cs (copied) (copied from trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisLineChartView.Designer.cs)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisLineChartView.cs (copied) (copied from trunk/sources/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisLineChartView.cs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolution.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionBase.cs (modified) (2 diffs)
• HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/TimeSeriesPrognosis/ITimeSeriesPrognosisSolution.cs (modified) (1 diff)

stable/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisExpressionTreeInterpreter.cs

@@ -45 +45 @@
     }
 
-    [ThreadStatic]
-    private static double[] targetVariableCache;
-    [ThreadStatic]
-    private static List<int> invalidateCacheIndexes;
-
     [StorableConstructor]
     private SymbolicTimeSeriesPrognosisExpressionTreeInterpreter(bool deserializing) : base(deserializing) { }
@@ -77 +72 @@
       if (CheckExpressionsWithIntervalArithmetic)
         throw new NotSupportedException("Interval arithmetic is not yet supported in the symbolic data analysis interpreter.");
-      if (targetVariableCache == null || targetVariableCache.GetLength(0) < dataset.Rows)
-        targetVariableCache = dataset.GetDoubleValues(TargetVariable).ToArray();
-      if (invalidateCacheIndexes == null)
-        invalidateCacheIndexes = new List<int>(10);
 
       string targetVariable = TargetVariable;
+      double[] targetVariableCache = dataset.GetDoubleValues(targetVariable).ToArray();
       lock (syncRoot) {
         EvaluatedSolutions++; // increment the evaluated solutions counter
@@ -100 +92 @@
           vProgs[i] = Evaluate(dataset, ref localRow, state);
           targetVariableCache[localRow] = vProgs[i];
-          invalidateCacheIndexes.Add(localRow);
           state.Reset();
         }
         yield return vProgs;
-
-        int j = 0;
-        foreach (var targetValue in dataset.GetDoubleValues(targetVariable, invalidateCacheIndexes)) {
-          targetVariableCache[invalidateCacheIndexes[j]] = targetValue;
-          j++;
-        }
-        invalidateCacheIndexes.Clear();
       }
 

stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/HeuristicLab.Problems.DataAnalysis.Views-3.4.csproj

@@ -410 +410 @@
     <Compile Include="Solution Views\TimeSeriesPrognosisSolutionView.Designer.cs">
       <DependentUpon>TimeSeriesPrognosisSolutionView.cs</DependentUpon>
+    </Compile>
+    <Compile Include="TimeSeriesPrognosis\TimeSeriesPrognosisLineChartView.cs">
+      <SubType>UserControl</SubType>
+    </Compile>
+    <Compile Include="TimeSeriesPrognosis\TimeSeriesPrognosisLineChartView.Designer.cs">
+      <DependentUpon>TimeSeriesPrognosisLineChartView.cs</DependentUpon>
     </Compile>
     <Compile Include="TimeSeriesPrognosis\TimeSeriesPrognosisResultsView.cs">

stable/HeuristicLab.Problems.DataAnalysis.Views/3.4/Regression/RegressionSolutionLineChartView.cs

@@ -57 +57 @@
     }
 
+    protected virtual void GetTrainingSeries(out int[] x, out double[] y) {
+      x = Content.ProblemData.TrainingIndices.ToArray();
+      y = Content.EstimatedTrainingValues.ToArray();
+    }
+
+    protected virtual void GetTestSeries(out int[] x, out double[] y) {
+      x = Content.ProblemData.TestIndices.ToArray();
+      y = Content.EstimatedTestValues.ToArray();
+    }
+
+    protected virtual void GetAllValuesSeries(out int[] x, out double[] y) {
+      x = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
+      var tmp = Content.EstimatedValues.ToArray();
+      y = x.Select(index => tmp[index]).ToArray();
+    }
+
     private void RedrawChart() {
       this.chart.Series.Clear();
@@ -73 +89 @@
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.Color = this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Color;
-        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TrainingIndices.ToArray(), Content.EstimatedTrainingValues.ToArray());
+        int[] trainingIdx;
+        double[] trainingY;
+        GetTrainingSeries(out trainingIdx, out trainingY);
+        this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Points.DataBindXY(trainingIdx, trainingY);
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
+
         // test series
         this.chart.Series.Add(ESTIMATEDVALUES_TEST_SERIES_NAME);
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].LegendText = ESTIMATEDVALUES_TEST_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(Content.ProblemData.TestIndices.ToArray(), Content.EstimatedTestValues.ToArray());
+        int[] testIdx;
+        double[] testY;
+        GetTestSeries(out testIdx, out testY);
+        this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Points.DataBindXY(testIdx, testY);
         this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME]);
         this.chart.Series[ESTIMATEDVALUES_TEST_SERIES_NAME].Tag = Content;
+
         // series of remaining points
-        int[] allIndices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
-        var estimatedValues = Content.EstimatedValues.ToArray();
-        List<double> allEstimatedValues = allIndices.Select(index => estimatedValues[index]).ToList();
+        int[] allIdx;
+        double[] allEstimatedValues;
+        GetAllValuesSeries(out allIdx, out allEstimatedValues);
+
         this.chart.Series.Add(ESTIMATEDVALUES_ALL_SERIES_NAME);
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].LegendText = ESTIMATEDVALUES_ALL_SERIES_NAME;
         this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].ChartType = SeriesChartType.FastLine;
-        if (allEstimatedValues.Count > 0) {
-          this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIndices, allEstimatedValues);
+        if (allEstimatedValues.Length > 0) {
+          this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME].Points.DataBindXY(allIdx, allEstimatedValues);
           this.InsertEmptyPoints(this.chart.Series[ESTIMATEDVALUES_ALL_SERIES_NAME]);
         }
@@ -244 +269 @@
         }
       } else if (Content != null) {
-        string targetVariableName = Content.ProblemData.TargetVariable;
-
-        IEnumerable<int> indices = null;
+
+        int[] indices = null;
         double[] predictedValues = null;
         switch (series.Name) {
           case ESTIMATEDVALUES_ALL_SERIES_NAME:
-            indices = Enumerable.Range(0, Content.ProblemData.Dataset.Rows).Except(Content.ProblemData.TrainingIndices).Except(Content.ProblemData.TestIndices).ToArray();
-            var estimatedValues = Content.EstimatedValues.ToArray();
-            predictedValues = indices.Select(index => estimatedValues[index]).ToArray();
+            GetAllValuesSeries(out indices, out predictedValues);
             break;
           case ESTIMATEDVALUES_TRAINING_SERIES_NAME:
-            indices = Content.ProblemData.TrainingIndices.ToArray();
-            predictedValues = Content.EstimatedTrainingValues.ToArray();
+            GetTrainingSeries(out indices, out predictedValues);
             break;
           case ESTIMATEDVALUES_TEST_SERIES_NAME:
-            indices = Content.ProblemData.TestIndices.ToArray();
-            predictedValues = Content.EstimatedTestValues.ToArray();
+            GetTestSeries(out indices, out predictedValues);
             break;
         }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolution.cs

@@ -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();
+      }
+    }
   }
 }

stable/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionBase.cs

@@ -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,ProblemData.TargetVariable);
+      var meanModel = new ConstantModel(trainingMean, ProblemData.TargetVariable);
 
       double alpha, beta;

stable/HeuristicLab.Problems.DataAnalysis/3.4/Interfaces/TimeSeriesPrognosis/ITimeSeriesPrognosisSolution.cs

@@ -28 +28 @@
     IEnumerable<IEnumerable<double>> GetPrognosedValues(IEnumerable<int> rows, IEnumerable<int> horizon);
 
+    IEnumerable<double> PrognosedTestValues { get; }
+
     double TrainingTheilsUStatisticAR1 { get; }
     double TestTheilsUStatisticAR1 { get; }