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source: trunk/sources/HeuristicLab.StructureIdentification/Recombination/SizeFairCrossOver.cs @ 575

Last change on this file since 575 was 526, checked in by gkronber, 16 years ago

refactoring: removed method GetMinMaxArity in TreeGardener (#263 (List of allowed sub-functions for each function should be cached))

File size: 13.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using System.Text;
26using HeuristicLab.Core;
27using HeuristicLab.Operators;
28using HeuristicLab.Random;
29using HeuristicLab.Data;
30using HeuristicLab.Constraints;
31using HeuristicLab.Functions;
32using System.Diagnostics;
33
34namespace HeuristicLab.StructureIdentification {
35  public class SizeFairCrossOver : OperatorBase {
36    private const int MAX_RECOMBINATION_TRIES = 20;
37    public override string Description {
38      get {
39        return @"Takes two parent individuals P0 and P1 each. Selects a random node N0 of P0 and a random node N1 of P1.
40And replaces the branch with root0 N0 in P0 with N1 from P1 if the tree-size limits are not violated.
41When recombination with N0 and N1 would create a tree that is too large or invalid the operator randomly selects new N0 and N1
42until a valid configuration is found.";
43      }
44    }
45    public SizeFairCrossOver()
46      : base() {
47      AddVariableInfo(new VariableInfo("Random", "Pseudo random number generator", typeof(MersenneTwister), VariableKind.In));
48      AddVariableInfo(new VariableInfo("OperatorLibrary", "The operator library containing all available operators", typeof(GPOperatorLibrary), VariableKind.In));
49      AddVariableInfo(new VariableInfo("MaxTreeHeight", "The maximal allowed height of the tree", typeof(IntData), VariableKind.In));
50      AddVariableInfo(new VariableInfo("MaxTreeSize", "The maximal allowed size (number of nodes) of the tree", typeof(IntData), VariableKind.In));
51      AddVariableInfo(new VariableInfo("FunctionTree", "The tree to mutate", typeof(IFunctionTree), VariableKind.In | VariableKind.New));
52      AddVariableInfo(new VariableInfo("TreeSize", "The size (number of nodes) of the tree", typeof(IntData), VariableKind.New));
53      AddVariableInfo(new VariableInfo("TreeHeight", "The height of the tree", typeof(IntData), VariableKind.New));
54    }
55
56    public override IOperation Apply(IScope scope) {
57      MersenneTwister random = GetVariableValue<MersenneTwister>("Random", scope, true);
58      GPOperatorLibrary opLibrary = GetVariableValue<GPOperatorLibrary>("OperatorLibrary", scope, true);
59      int maxTreeHeight = GetVariableValue<IntData>("MaxTreeHeight", scope, true).Data;
60      int maxTreeSize = GetVariableValue<IntData>("MaxTreeSize", scope, true).Data;
61
62      TreeGardener gardener = new TreeGardener(random, opLibrary);
63
64      if((scope.SubScopes.Count % 2) != 0)
65        throw new InvalidOperationException("Number of parents is not even");
66
67      CompositeOperation initOperations = new CompositeOperation();
68
69      int children = scope.SubScopes.Count / 2;
70      for(int i = 0; i < children; i++) {
71        IScope parent1 = scope.SubScopes[0];
72        scope.RemoveSubScope(parent1);
73        IScope parent2 = scope.SubScopes[0];
74        scope.RemoveSubScope(parent2);
75        IScope child = new Scope(i.ToString());
76        IOperation childInitOperation = Cross(gardener, maxTreeSize, maxTreeHeight, scope, random, parent1, parent2, child);
77        initOperations.AddOperation(childInitOperation);
78        scope.AddSubScope(child);
79      }
80
81      return initOperations;
82    }
83
84    private IOperation Cross(TreeGardener gardener, int maxTreeSize, int maxTreeHeight,
85      IScope scope, MersenneTwister random, IScope parent1, IScope parent2, IScope child) {
86      List<IFunctionTree> newBranches;
87      IFunctionTree newTree = Cross(gardener, parent1, parent2,
88        random, maxTreeSize, maxTreeHeight, out newBranches);
89
90
91      int newTreeSize = newTree.Size;
92      int newTreeHeight = newTree.Height;
93      child.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("FunctionTree"), newTree));
94      child.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeSize"), new IntData(newTreeSize)));
95      child.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("TreeHeight"), new IntData(newTreeHeight)));
96
97      // check if the new tree is valid and if the height of is still in the allowed bounds (we are not so strict for the max-size)
98      Debug.Assert(gardener.IsValidTree(newTree) && newTreeHeight <= maxTreeHeight && newTreeSize <= maxTreeSize);
99      return gardener.CreateInitializationOperation(newBranches, child);
100    }
101
102
103    private IFunctionTree Cross(TreeGardener gardener, IScope f, IScope g, MersenneTwister random, int maxTreeSize, int maxTreeHeight, out List<IFunctionTree> newBranches) {
104      IFunctionTree tree0 = f.GetVariableValue<IFunctionTree>("FunctionTree", false);
105      int tree0Height = f.GetVariableValue<IntData>("TreeHeight", false).Data;
106      int tree0Size = f.GetVariableValue<IntData>("TreeSize", false).Data;
107
108      IFunctionTree tree1 = g.GetVariableValue<IFunctionTree>("FunctionTree", false);
109      int tree1Height = g.GetVariableValue<IntData>("TreeHeight", false).Data;
110      int tree1Size = g.GetVariableValue<IntData>("TreeSize", false).Data;
111
112      if(tree0Size == 1 && tree1Size == 1) {
113        return CombineTerminals(gardener, tree0, tree1, random, maxTreeHeight, out newBranches);
114      } else {
115        newBranches = new List<IFunctionTree>();
116
117        // we are going to insert tree1 into tree0 at a random place so we have to make sure that tree0 is not a terminal
118        // in case both trees are higher than 1 we swap the trees with probability 50%
119        if(tree0Height == 1 || (tree1Height > 1 && random.Next(2) == 0)) {
120          IFunctionTree tmp = tree0; tree0 = tree1; tree1 = tmp;
121          int tmpHeight = tree0Height; tree0Height = tree1Height; tree1Height = tmpHeight;
122          int tmpSize = tree0Size; tree0Size = tree1Size; tree1Size = tmpSize;
123        }
124
125        // save the roots because later on we change tree0 and tree1 while searching a valid tree configuration
126        IFunctionTree root0 = tree0;
127        IFunctionTree root1 = tree1;
128        int root0Height = tree0Height;
129        int root1Height = tree1Height;
130        int rootSize = tree0Size;
131
132        // select a random suboperators of the two trees at a random level
133        int tree0Level = random.Next(root0Height - 1); // since we checked before that the height of tree0 is > 1 this is OK
134        int tree1Level = random.Next(root1Height);
135        tree0 = gardener.GetRandomBranch(tree0, tree0Level);
136        tree1 = gardener.GetRandomBranch(tree1, tree1Level);
137
138        // recalculate the size and height of tree1 (the one that we want to insert) because we need to check constraints later on
139        tree1Size = tree1.Size;
140        tree1Height = tree1.Height;
141
142        List<int> possibleChildIndices = new List<int>();
143
144        // Now tree0 is supposed to take tree1 as one if its children. If this is not possible,
145        // then go down in either of the two trees as far as possible. If even then it is not possible
146        // to merge the trees then throw an exception
147        // find the list of allowed indices (regarding allowed sub-trees, maxTreeSize and maxTreeHeight)
148        for(int i = 0; i < tree0.SubTrees.Count; i++) {
149          int subTreeSize = tree0.SubTrees[i].Size;
150
151          // the index is ok when the function is allowed as sub-tree and we don't violate the maxSize and maxHeight constraints
152          if(gardener.GetAllowedSubFunctions(tree0.Function, i).Contains(tree1.Function) &&
153            rootSize - subTreeSize + tree1Size < maxTreeSize &&
154            tree0Level + tree1Height < maxTreeHeight) {
155            possibleChildIndices.Add(i);
156          }
157        }
158        int tries = 0;
159        while(possibleChildIndices.Count == 0) {
160          if(tries++ > MAX_RECOMBINATION_TRIES) {
161            if(random.Next() > 0.5) return root1;
162            else return root0;
163          }
164          // we couln't find a possible configuration given the current tree0 and tree1
165          // possible reasons for this are:
166          //  - tree1 is not allowed as sub-tree of tree0
167          //  - appending tree1 as child of tree0 would create a tree that exceedes the maxTreeHeight
168          //  - replacing any child of tree0 with tree1 woulde create a tree that exceedes the maxTeeSize
169          // thus we just try until we find a valid configuration
170
171          tree0Level = random.Next(root0Height - 1);
172          tree1Level = random.Next(root1Height);
173          tree0 = gardener.GetRandomBranch(root0, tree0Level);
174          tree1 = gardener.GetRandomBranch(root1, tree1Level);
175
176          // recalculate the size and height of tree1 (the one that we want to insert) because we need to check constraints later on
177          tree1Size = tree1.Size;
178          tree1Height = tree1.Height;
179          // recalculate the list of possible indices
180          possibleChildIndices.Clear();
181          for(int i = 0; i < tree0.SubTrees.Count; i++) {
182            int subTreeSize = tree0.SubTrees[i].Size;
183
184            // when the function is allowed as sub-tree and we don't violate the maxSize and maxHeight constraints
185            // the index is ok
186            if(gardener.GetAllowedSubFunctions(tree0.Function, i).Contains(tree1.Function) &&
187              rootSize - subTreeSize + tree1Size < maxTreeSize &&
188              tree0Level + tree1Height < maxTreeHeight) {
189              possibleChildIndices.Add(i);
190            }
191          }
192        }
193        // replace the existing sub-tree at a random index in tree0 with tree1
194        int selectedIndex = possibleChildIndices[random.Next(possibleChildIndices.Count)];
195        tree0.RemoveSubTree(selectedIndex);
196        tree0.InsertSubTree(selectedIndex, tree1);
197        return root0;
198      }
199    }
200
201
202    // take f and g and create a tree that has f and g as sub-trees
203    // example
204    //       O
205    //      /|\
206    //     g 2 f
207    //
208    private IFunctionTree CombineTerminals(TreeGardener gardener, IFunctionTree f, IFunctionTree g, MersenneTwister random, int maxTreeHeight, out List<IFunctionTree> newBranches) {
209      newBranches = new List<IFunctionTree>();
210      // determine the set of possible parent functions
211      ICollection<IFunction> possibleParents = gardener.GetPossibleParents(new List<IFunction>() { f.Function, g.Function });
212      if(possibleParents.Count == 0) throw new InvalidProgramException();
213      // and select a random one
214      IFunctionTree parent = possibleParents.ElementAt(random.Next(possibleParents.Count())).GetTreeNode();
215
216      int nSlots = Math.Max(2, parent.Function.MinArity);
217      // determine which slot can take which sub-trees
218      List<IFunctionTree>[] slots = new List<IFunctionTree>[nSlots];
219      for(int slot = 0; slot < nSlots; slot++) {
220        ICollection<IFunction> allowedSubFunctions = gardener.GetAllowedSubFunctions(parent.Function, slot);
221        List<IFunctionTree> allowedTrees = new List<IFunctionTree>();
222        if(allowedSubFunctions.Contains(f.Function)) allowedTrees.Add(f);
223        if(allowedSubFunctions.Contains(g.Function)) allowedTrees.Add(g);
224        slots[slot] = allowedTrees;
225      }
226      // fill the slots in the order of degrees of freedom
227      int[] slotSequence = Enumerable.Range(0, slots.Count()).OrderBy(slot => slots[slot].Count()).ToArray();
228
229      // tmp arry to store the tree for each sub-tree slot of the parent
230      IFunctionTree[] selectedFunctionTrees = new IFunctionTree[nSlots];
231
232      // fill the sub-tree slots of the parent starting with the slots that can take potentially both functions (f and g)
233      for(int i = 0; i < slotSequence.Length; i++) {
234        int slot = slotSequence[i];
235        List<IFunctionTree> allowedTrees = slots[slot];
236        // when neither f nor g fit into the slot => create a new random tree
237        if(allowedTrees.Count() == 0) {
238          var allowedFunctions = gardener.GetAllowedSubFunctions(parent.Function, slot);
239          selectedFunctionTrees[slot] = gardener.CreateRandomTree(allowedFunctions, 1, 1);
240          newBranches.AddRange(gardener.GetAllSubTrees(selectedFunctionTrees[slot]));
241        } else {
242          // select randomly which tree to insert into this slot
243          IFunctionTree selectedTree = allowedTrees[random.Next(allowedTrees.Count())];
244          selectedFunctionTrees[slot] = selectedTree;
245          // remove the tree that we used in this slot from following function-sets
246          for(int j = i + 1; j < slotSequence.Length; j++) {
247            int otherSlot = slotSequence[j];
248            slots[otherSlot].Remove(selectedTree);
249          }
250        }
251      }
252      // actually append the sub-trees to the parent tree
253      for(int i = 0; i < selectedFunctionTrees.Length; i++) {
254        parent.InsertSubTree(i, selectedFunctionTrees[i]);
255      }
256
257      return parent;
258    }
259  }
260}
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