Changeset 7998

Timestamp:

06/13/12 15:35:22 (12 years ago)

Author:

mkommend

Message:

#1081: Corrected time series interpreter and updated visualizations.

Location:

branches/HeuristicLab.TimeSeries

Files:

• HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisExpressionTreeInterpreter.cs (modified) (3 diffs)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionLineChartView.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionPrognosedValuesView.cs (modified) (1 diff)
• HeuristicLab.Problems.Instances.DataAnalysis/3.3/TimeSeries/TimeSeriesPrognosisInstanceProvider.cs (modified) (2 diffs)

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SingleObjective/SymbolicTimeSeriesPrognosisSingleObjectiveMeanSquaredErrorEvaluator.cs

@@ -62 +62 @@
 
     public static double Calculate(ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, ISymbolicExpressionTree solution, double lowerEstimationLimit, double upperEstimationLimit, ITimeSeriesPrognosisProblemData problemData, IEnumerable<int> rows, int horizon, bool applyLinearScaling) {
-      IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows.SelectMany(r => Enumerable.Range(r, horizon)));
-      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows, horizon).SelectMany(x => x);
+      int horizion2 = problemData.TrainingPartition.End - problemData.TrainingPartition.Start;
+      IEnumerable<double> targetValues = problemData.Dataset.GetDoubleValues(problemData.TargetVariable, rows.Take(1).Select(r => Enumerable.Range(r, horizion2)).First());
+      IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows.Take(1), horizion2).SelectMany(x => x);
       IEnumerable<double> boundedEstimatedValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
       OnlineCalculatorError errorState;

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisExpressionTreeInterpreter.cs

@@ -86 +86 @@
         int row = rowsEnumerator.Current;
         int horizon = horizonsEnumerator.Current;
+        double[] vProgs = new double[horizon];
 
-        double[] vProgs = new double[horizon];
         for (int i = 0; i < horizon; i++) {
           int localRow = i + row; // create a local variable for the ref parameter
@@ -95 +95 @@
           state.Reset();
         }
-
         yield return vProgs;
 
@@ -121 +120 @@
             instr.iArg0 = dataset.GetReadOnlyDoubleValues(variableTreeNode.VariableName);
         } else if (instr.opCode == OpCodes.LagVariable) {
-          var laggedVariableTreeNode = (LaggedVariableTreeNode)instr.dynamicNode;
-          instr.iArg0 = dataset.GetReadOnlyDoubleValues(laggedVariableTreeNode.VariableName);
+          var variableTreeNode = (LaggedVariableTreeNode)instr.dynamicNode;
+          if (variableTreeNode.VariableName == TargetVariable)
+            instr.iArg0 = targetVariableCache;
+          else
+            instr.iArg0 = dataset.GetReadOnlyDoubleValues(variableTreeNode.VariableName);
         } else if (instr.opCode == OpCodes.VariableCondition) {
-          var variableConditionTreeNode = (VariableConditionTreeNode)instr.dynamicNode;
-          instr.iArg0 = dataset.GetReadOnlyDoubleValues(variableConditionTreeNode.VariableName);
+          var variableTreeNode = (VariableConditionTreeNode)instr.dynamicNode;
+          if (variableTreeNode.VariableName == TargetVariable)
+            instr.iArg0 = targetVariableCache;
+          else
+            instr.iArg0 = dataset.GetReadOnlyDoubleValues(variableTreeNode.VariableName);
         } else if (instr.opCode == OpCodes.Call) {
           necessaryArgStackSize += instr.nArguments + 1;

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionLineChartView.cs

@@ -214 +214 @@
         }
       } else if (Content != null) {
-        string targetVariable = Content.ProblemData.TargetVariable;
-
         IEnumerable<int> indizes = null;
         IEnumerable<double> predictedValues = null;

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionPrognosedValuesView.cs

@@ -124 +124 @@
       matrix.ColumnNames = columnNames.ToArray();
       matrix.SortableView = true;
+      matrixView.Content = matrix;
     }
     #endregion

branches/HeuristicLab.TimeSeries/HeuristicLab.Problems.Instances.DataAnalysis/3.3/TimeSeries/TimeSeriesPrognosisInstanceProvider.cs

@@ -21 +21 @@
 
 using System;
-using System.Collections;
 using System.Collections.Generic;
 using System.IO;
@@ -37 +36 @@
       Dataset dataset = new Dataset(csvFileParser.VariableNames, csvFileParser.Values);
       string targetVar = csvFileParser.VariableNames.Last();
-
-      IEnumerable<string> allowedInputVars = csvFileParser.VariableNames.Where(x => !x.Equals(targetVar));
+      
+      IEnumerable<string> allowedInputVars = dataset.DoubleVariables.Where(x => !x.Equals(targetVar));
 
       ITimeSeriesPrognosisProblemData regData = new TimeSeriesPrognosisProblemData(dataset, allowedInputVars, targetVar);