Changeset 16851 for branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs

Timestamp:

04/19/19 14:35:08 (5 years ago)

Author:

chaider

Message:

#2791 Refactored Constraint Evaluator and Analyzer

File:

• branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs (modified) (5 diffs)

branches/2971_named_intervals/HeuristicLab.Problems.DataAnalysis.Symbolic.Regression/3.4/SymbolicRegressionSolution.cs

@@ -98 +98 @@
     }
 
-
     public NamedIntervals IntervalEvaluationCollection {
       get { return (NamedIntervals)this[IntervalEvaluationResultName].Value; }
@@ -128 +127 @@
       estimationLimitResults.Add(new Result(TestNaNEvaluationsResultName, "", new IntValue()));
       Add(new Result(EstimationLimitsResultsResultName, "Results concerning the estimation limits of symbolic regression solution", estimationLimitResults));
-      Add(new Result(IntervalEvaluationResultName, "Results concerning the derivation of symbolic regression solution", GetIntervalEvaluations()));
+      Add(new Result(IntervalEvaluationResultName, "Results concerning the derivation of symbolic regression solution", new NamedIntervals()));
       RecalculateResults();
     }
@@ -148 +147 @@
         estimationLimitResults.Add(new Result(TestNaNEvaluationsResultName, "", new IntValue()));
         Add(new Result(EstimationLimitsResultsResultName, "Results concerning the estimation limits of symbolic regression solution", estimationLimitResults));
-        Add(new Result(IntervalEvaluationResultName, "Results concerning the derivation of symbolic regression solution", GetIntervalEvaluations()));
+        Add(new Result(IntervalEvaluationResultName, "Results concerning the derivation of symbolic regression solution", new NamedIntervals()));
         CalculateResults();
       }
@@ -156 +155 @@
       base.RecalculateResults();
       CalculateResults();
-    }
-
-    private NamedIntervals GetIntervalEvaluations() {
-      var intervalEvaluation = new NamedIntervals();
-      var interpreter = new IntervalInterpreter();
-      var variableRanges = ProblemData.VariableRanges.VariableIntervals;
-
-      if (variableRanges != null) {
-        intervalEvaluation.VariableIntervals.Add($"Target {ProblemData.TargetVariable}", new Interval(variableRanges[ProblemData.TargetVariable].LowerBound, variableRanges[ProblemData.TargetVariable].UpperBound));
-        intervalEvaluation.VariableIntervals.Add("Modell Interval", interpreter.GetSymbolicExpressionTreeInterval(Model.SymbolicExpressionTree, variableRanges));
-     
-        foreach (var derivate in variableRanges) {
-          if (derivate.Key != ProblemData.TargetVariable) {
-            var derived = DerivativeCalculator.Derive(Model.SymbolicExpressionTree, derivate.Key);
-            var derivedResultInterval = interpreter.GetSymbolicExpressionTreeInterval(derived, variableRanges);
-
-            intervalEvaluation.VariableIntervals.Add(" \u2202f/\u2202" + derivate.Key,
-              new Interval(derivedResultInterval.LowerBound, derivedResultInterval.UpperBound));
-          }
-        }
-      }
-      return intervalEvaluation;
     }
 
@@ -194 +171 @@
       TestNaNEvaluations = Model.Interpreter.GetSymbolicExpressionTreeValues(Model.SymbolicExpressionTree, ProblemData.Dataset, ProblemData.TestIndices).Count(double.IsNaN);
 
-      IntervalEvaluationCollection = GetIntervalEvaluations();
+      IntervalEvaluationCollection = CalculateModelIntervals(this);
+    }
+
+    private static NamedIntervals CalculateModelIntervals(ISymbolicRegressionSolution solution) {
+      var intervalEvaluation = new NamedIntervals();
+      var interpreter = new IntervalInterpreter();
+      var problemData = solution.ProblemData;
+      var model = solution.Model;
+      var variableRanges = problemData.VariableRanges.VariableIntervals;
+
+      intervalEvaluation.VariableIntervals.Add($"Target {problemData.TargetVariable}", new Interval(variableRanges[problemData.TargetVariable].LowerBound, variableRanges[problemData.TargetVariable].UpperBound));
+      intervalEvaluation.VariableIntervals.Add("Model Interval", interpreter.GetSymbolicExpressionTreeInterval(model.SymbolicExpressionTree, variableRanges));
+
+      foreach (var inputVariable in model.VariablesUsedForPrediction.OrderBy(v => v, new NaturalStringComparer())) {
+        var derivedModel = DerivativeCalculator.Derive(model.SymbolicExpressionTree, inputVariable);
+        var derivedResultInterval = interpreter.GetSymbolicExpressionTreeInterval(derivedModel, variableRanges);
+
+        intervalEvaluation.VariableIntervals.Add(" \u2202f/\u2202" + inputVariable,
+          new Interval(derivedResultInterval.LowerBound, derivedResultInterval.UpperBound));
+      }
+
+      return intervalEvaluation;
     }
   }