Changeset 17325 for branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Extensions/ConstrainedNLS.cs

Timestamp:

10/09/19 11:13:11 (5 years ago)

Author:

gkronber

Message:

#2994: worked on ConstrainedNLS

File:

• branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Extensions/ConstrainedNLS.cs (modified) (6 diffs)

branches/2994-AutoDiffForIntervals/HeuristicLab.Problems.DataAnalysis.Regression.Symbolic.Extensions/ConstrainedNLS.cs

@@ -10 +10 @@
 using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
 using HeuristicLab.Analysis;
+using System.Collections.Generic;
 
 namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Regression {
@@ -157 +158 @@
       Results.AddOrUpdateResult("Qualities", qualitiesTable);
 
-      var curConstraintValue = new DoubleValue(0);
-      Results.AddOrUpdateResult("Current Constraint Value", curConstraintValue);
-      var curConstraintIdx = new IntValue(0);
-      Results.AddOrUpdateResult("Current Constraint Index", curConstraintIdx);
-
-      var curConstraintRow = new DataRow("Constraint Value");
-      var constraintsTable = new DataTable("Constraints");
-
-      constraintsTable.Rows.Add(curConstraintRow);
+      var constraintRows = new List<IndexedDataRow<int>>(); // for access via index
+      var constraintsTable = new IndexedDataTable<int>("Constraints");
       Results.AddOrUpdateResult("Constraints", constraintsTable);
+      foreach (var constraint in problem.ProblemData.IntervalConstraints.Constraints.Where(c => c.Enabled)) {
+        if (constraint.Interval.LowerBound > double.NegativeInfinity) {
+          var constraintRow = new IndexedDataRow<int>("-" + constraint.Expression + " < " + (-constraint.Interval.LowerBound));
+          constraintRows.Add(constraintRow);
+          constraintsTable.Rows.Add(constraintRow);
+        }
+        if (constraint.Interval.UpperBound < double.PositiveInfinity) {
+          var constraintRow = new IndexedDataRow<int>(constraint.Expression + " < " + (constraint.Interval.UpperBound));
+          constraintRows.Add(constraintRow);
+          constraintsTable.Rows.Add(constraintRow);
+        }
+      }
+
+      var parametersTable = new IndexedDataTable<int>("Parameters");
 
       #endregion
@@ -175 +183 @@
       var formatter = new InfixExpressionFormatter();
       var constraintDescriptions = state.ConstraintDescriptions.ToArray();
-      foreach(var constraintTree in state.constraintTrees) {
+      foreach (var constraintTree in state.constraintTrees) {
         // HACK to remove parameter nodes which occurr multiple times
         var reparsedTree = parser.Parse(formatter.Format(constraintTree));
@@ -186 +194 @@
       state.ConstraintEvaluated += State_ConstraintEvaluated;
 
-      state.Optimize();
+      state.Optimize(ConstrainedNLSInternal.OptimizationMode.UpdateParametersAndKeepLinearScaling);
       bestError.Value = state.BestError;
       curQualityRow.Values.Add(state.CurError);
@@ -205 +213 @@
         curQualityRow.Values.Add(state.CurError);
         bestQualityRow.Values.Add(bestError.Value);
+
+        // on the first call create the data rows
+        if(!parametersTable.Rows.Any()) {
+          for(int i=0;i<state.BestSolution.Length;i++) {
+            parametersTable.Rows.Add(new IndexedDataRow<int>("p" + i));
+          }
+        }
+        for (int i = 0; i < state.BestSolution.Length; i++) {
+          parametersTable.Rows["p" + i].Values.Add(Tuple.Create(functionEvaluations.Value, state.BestSolution[i])); // TODO: remove access via string
+        }
       }
 
       // local function
       void State_ConstraintEvaluated(int constraintIdx, double value) {
-        curConstraintIdx.Value = constraintIdx;
-        curConstraintValue.Value = value;
-        curConstraintRow.Values.Add(value);
+        constraintRows[constraintIdx].Values.Add(Tuple.Create(functionEvaluations.Value, value));
       }
     }
@@ -217 +233 @@
     private static ISymbolicRegressionSolution CreateSolution(ISymbolicExpressionTree tree, IRegressionProblemData problemData) {
       var model = new SymbolicRegressionModel(problemData.TargetVariable, tree, new SymbolicDataAnalysisExpressionTreeLinearInterpreter());
-      // model.Scale(problemData);
+      // model.CreateRegressionSolution produces a new ProblemData and recalculates intervals ==> use SymbolicRegressionSolution.ctor instead
+      var sol = new SymbolicRegressionSolution(model, (IRegressionProblemData)problemData.Clone());
+      // NOTE: the solution has slightly different derivative values because simplification of derivatives can be done differently when parameter values are fixed.
+
       // var sol = model.CreateRegressionSolution((IRegressionProblemData)problemData.Clone());
-      // model.CreateRegressionSolution produces a new ProblemData and recalculates intervals
-
-      var sol = new SymbolicRegressionSolution(model, (IRegressionProblemData)problemData.Clone());
-
-      // ==> set variable ranges to same range as in original problemData
-      // foreach(var interval in problemData.VariableRanges.GetIntervals()) {
-      //   sol.ProblemData.VariableRanges.SetInterval
-      // }
+
       return sol;
     }