1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022013 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 System;


23  using System.Collections.Generic;


24  using HeuristicLab.Common;


25  using HeuristicLab.Core;


26  using HeuristicLab.Encodings.IntegerVectorEncoding;


27  using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;


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


29  using HeuristicLab.Random;


30 


31  namespace HeuristicLab.Problems.GrammaticalEvolution {


32  /// <summary>


33  /// DepthFirstMapper


34  /// </summary>


35  [Item("DepthFirstMapper", "Resolves the nonterminal symbols of the resulting phenotypic syntax tree in a depthfirst manner.")]


36  [StorableClass]


37  public class DepthFirstMapper : GenotypeToPhenotypeMapper {


38 


39  [StorableConstructor]


40  protected DepthFirstMapper(bool deserializing) : base(deserializing) { }


41  protected DepthFirstMapper(DepthFirstMapper original, Cloner cloner) : base(original, cloner) { }


42  public DepthFirstMapper() : base() { }


43 


44  public override IDeepCloneable Clone(Cloner cloner) {


45  return new DepthFirstMapper(this, cloner);


46  }


47 


48 


49  /// <summary>


50  /// Maps a genotype (an integer vector) to a phenotype (a symbolic expression tree).


51  /// Depthfirst approach.


52  /// </summary>


53  /// <param name="grammar">grammar definition</param>


54  /// <param name="genotype">integer vector, which should be mapped to a tree</param>


55  /// <returns>phenotype (a symbolic expression tree)</returns>


56  public override SymbolicExpressionTree Map(ISymbolicExpressionGrammar grammar,


57  IntegerVector genotype) {


58 


59  SymbolicExpressionTree tree = new SymbolicExpressionTree();


60  var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.ProgramRootSymbol.CreateTreeNode();


61  if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(new MersenneTwister());


62  var startNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();


63  if (startNode.HasLocalParameters) startNode.ResetLocalParameters(new MersenneTwister());


64  rootNode.AddSubtree(startNode);


65  tree.Root = rootNode;


66 


67  MapDepthFirstIteratively(startNode, genotype, grammar,


68  genotype.Length, new MersenneTwister());


69  return tree;


70  }


71 


72 


73  /// <summary>


74  /// GenotypetoPhenotype mapper (iterative depthfirst approach, by using a stack > LIFO).


75  /// </summary>


76  /// <param name="startNode">first node of the tree with arity 1</param>


77  /// <param name="genotype">integer vector, which should be mapped to a tree</param>


78  /// <param name="grammar">grammar to determine the allowed child symbols for each node</param>


79  /// <param name="maxSubtreeCount">maximum allowed subtrees (= number of used genomes)</param>


80  /// <param name="random">random number generator</param>


81  private void MapDepthFirstIteratively(ISymbolicExpressionTreeNode startNode,


82  IntegerVector genotype,


83  ISymbolicExpressionGrammar grammar,


84  int maxSubtreeCount, IRandom random) {


85 


86  Stack<Tuple<ISymbolicExpressionTreeNode, int>> stack


87  = new Stack<Tuple<ISymbolicExpressionTreeNode, int>>(); // tuples of <node, arity>


88 


89  int genotypeIndex = 0;


90  int currSubtreeCount = 1;


91 


92  stack.Push(new Tuple<ISymbolicExpressionTreeNode, int>(startNode, 1));


93 


94  while ((currSubtreeCount < maxSubtreeCount) && (stack.Count > 0)) {


95 


96  // get next node from stack and repush it, if this node still has unhandled subtrees ...


97  Tuple<ISymbolicExpressionTreeNode, int> current = stack.Pop();


98  if (current.Item2 > 1) {


99  stack.Push(new Tuple<ISymbolicExpressionTreeNode, int>(current.Item1, current.Item2  1));


100  }


101 


102  var newNode = GetNewChildNode(current.Item1, genotype, grammar, genotypeIndex, random);


103  int arity = SampleArity(random, newNode, maxSubtreeCount  currSubtreeCount);


104 


105  if (arity < 0) {


106  current.Item1.AddSubtree(GetRandomTerminalNode(current.Item1, grammar, random));


107  } else {


108  current.Item1.AddSubtree(newNode);


109  genotypeIndex++;


110  currSubtreeCount += arity;


111  if (arity > 0) {


112  // new node has subtrees so push it onto the stack


113  stack.Push(new Tuple<ISymbolicExpressionTreeNode, int>(newNode, arity));


114  }


115  }


116  }


117 


118  // maximum allowed subtree count was already reached, but there are still


119  // incomplete subtrees (nonterminal symbols) in the tree


120  // > fill them with terminal symbols


121  while (stack.Count > 0) {


122  Tuple<ISymbolicExpressionTreeNode, int> current = stack.Pop();


123  if (current.Item2 > 1) {


124  stack.Push(new Tuple<ISymbolicExpressionTreeNode, int>(current.Item1, current.Item2  1));


125  }


126  current.Item1.AddSubtree(GetRandomTerminalNode(current.Item1, grammar, random));


127  }


128  }


129  }


130  } 
