Changeset 5551

Timestamp:

02/23/11 11:34:22 (13 years ago)

Author:

gkronber

Message:

#1418 removed ternary operator in LimitToRange extension as requested by mkommend. Removed range limitation in evaluators calculating the squared Pearson's r.

Location:

branches/DataAnalysis Refactoring

Files:

• HeuristicLab.Common/3.3/EnumerableStatisticExtensions.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs (modified) (1 diff)
• HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs (modified) (1 diff)

branches/DataAnalysis Refactoring/HeuristicLab.Common/3.3/EnumerableStatisticExtensions.cs

@@ -109 +109 @@
 
     public static IEnumerable<double> LimitToRange(this IEnumerable<double> values, double min, double max) {
-      return from x in values
-             select double.IsNaN(x) ? x : (x < min ? min : (x > max ? max : x));
+      foreach (var x in values) {
+        if (double.IsNaN(x)) yield return x;
+        else if (x < min) yield return min;
+        else if (x > max) yield return max;
+        else yield return x;
+      }
     }
   }

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/MultiObjective/SymbolicClassificationMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

@@ -33 +33 @@
       IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
-      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
-      double r2 = OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, boundedEstimationValues);
+      double r2 = OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
       return new double[2] { r2, solution.Length };
     }

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SingleObjective/SymbolicClassificationSingleObjectivePearsonRSquaredEvaluator.cs

@@ -54 +54 @@
       IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
-      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
-      return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, boundedEstimationValues);
+      return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
     }
   }

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/MultiObjective/SymbolicRegressionMultiObjectivePearsonRSquaredTreeSizeEvaluator.cs

@@ -54 +54 @@
       IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
-      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
-      double r2 = OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, boundedEstimationValues);
+      double r2 = OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
       return new double[2] { r2, solution.Length };
     }

branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SingleObjective/SymbolicRegressionSingleObjectivePearsonRSquaredEvaluator.cs

@@ -54 +54 @@
       IEnumerable<double> estimatedValues = interpreter.GetSymbolicExpressionTreeValues(solution, problemData.Dataset, rows);
       IEnumerable<double> originalValues = problemData.Dataset.GetEnumeratedVariableValues(problemData.TargetVariable, rows);
-      IEnumerable<double> boundedEstimationValues = estimatedValues.LimitToRange(lowerEstimationLimit, upperEstimationLimit);
-      return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, boundedEstimationValues);
+      return OnlinePearsonsRSquaredEvaluator.Calculate(originalValues, estimatedValues);
     }
   }