1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21 


22  using HeuristicLab.Common;


23  using HeuristicLab.Core;


24  using HeuristicLab.Data;


25  using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;


26  using HeuristicLab.Optimization.Operators;


27  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


28 


29  namespace HeuristicLab.Problems.DataAnalysis.Symbolic {


30  [Item("SymbolicExpressionTreePhenotypicSimilarityCalculator", "An operator that calculates the similarity betweeon two trees based on the correlation of their outputs.")]


31  [StorableClass]


32  public class SymbolicExpressionTreePhenotypicSimilarityCalculator : SingleObjectiveSolutionSimilarityCalculator {


33  public IDataAnalysisProblemData ProblemData { get; set; }


34  public ISymbolicDataAnalysisExpressionTreeInterpreter Interpreter { get; set; }


35 


36  [StorableConstructor]


37  protected SymbolicExpressionTreePhenotypicSimilarityCalculator(bool deserializing) : base(deserializing) { }


38 


39  public SymbolicExpressionTreePhenotypicSimilarityCalculator(SymbolicExpressionTreePhenotypicSimilarityCalculator original, Cloner cloner)


40  : base(original, cloner) {


41  this.ProblemData = original.ProblemData;


42  this.Interpreter = original.Interpreter;


43  }


44 


45  public override IDeepCloneable Clone(Cloner cloner) {


46  return new SymbolicExpressionTreePhenotypicSimilarityCalculator(this, cloner);


47  }


48 


49  public SymbolicExpressionTreePhenotypicSimilarityCalculator() { }


50 


51  public double CalculateSimilarity(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2) {


52  var v1 = Interpreter.GetSymbolicExpressionTreeValues(t1, ProblemData.Dataset, ProblemData.TrainingIndices);


53  var v2 = Interpreter.GetSymbolicExpressionTreeValues(t2, ProblemData.Dataset, ProblemData.TrainingIndices);


54 


55  OnlineCalculatorError error;


56  var r2 = OnlinePearsonsRSquaredCalculator.Calculate(v1, v2, out error);


57 


58  if (r2 > 1.0)


59  r2 = 1.0;


60 


61  return error == OnlineCalculatorError.None ? r2 : 0;


62  }


63 


64  public override double CalculateSolutionSimilarity(IScope leftSolution, IScope rightSolution) {


65  if (leftSolution == rightSolution)


66  return 1.0;


67 


68  var leftValues = (DoubleArray)leftSolution.Variables["EstimatedValues"].Value;


69  var rightValues = (DoubleArray)rightSolution.Variables["EstimatedValues"].Value;


70 


71  if (leftValues.Variance().IsAlmost(0) && rightValues.Variance().IsAlmost(0))


72  return 1.0;


73 


74  OnlineCalculatorError error;


75  var r2 = OnlinePearsonsRSquaredCalculator.Calculate(leftValues, rightValues, out error);


76 


77  if (r2 > 1.0)


78  r2 = 1.0; // sometimes due to fp errors it can happen that the r2 is over 1 (like 1.0000000009)


79 


80  return error == OnlineCalculatorError.None ? r2 : 0;


81  }


82  }


83  }

