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source: branches/Operator Architecture Refactoring/HeuristicLab.StructureIdentification/Manipulation/CutOutNodeManipulation.cs @ 630

Last change on this file since 630 was 324, checked in by gkronber, 17 years ago

added Size and Height properties to interface IFunctionTree and removed the helper methods from TreeGardener (specific implementations of size and height properties in classes implementing IFunctionTree can be more efficient than the general functions in TreeGardener)

File size: 7.1 KB
Line 
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.Collections.Generic;
23using System.Linq;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Operators;
27using HeuristicLab.Random;
28using System;
29using HeuristicLab.Functions;
30using System.Diagnostics;
31
32namespace HeuristicLab.StructureIdentification {
33  public class CutOutNodeManipulation : OperatorBase {
34    public override string Description {
35      get {
36        return @"Takes a tree, selects a random node of the tree and then tries to replace a random sub-tree
37of that node with one of the childs of the selected child.
38
39               O                             O
40              / \                           / \
41             O   X                         O   2
42                / \    2 is selected =>       / \
43               1   2                         4   5
44              /   / \
45             3   4   5
46";
47      }
48    }
49
50    public CutOutNodeManipulation()
51      : base() {
52      AddVariableInfo(new VariableInfo("Random", "Uniform random number generator", typeof(MersenneTwister), VariableKind.In));
53      AddVariableInfo(new VariableInfo("OperatorLibrary", "The operator library containing all available operators", typeof(GPOperatorLibrary), VariableKind.In));
54      AddVariableInfo(new VariableInfo("MaxTreeHeight", "The maximal allowed height of the tree", typeof(IntData), VariableKind.In));
55      AddVariableInfo(new VariableInfo("MaxTreeSize", "The maximal allowed size (number of nodes) of the tree", typeof(IntData), VariableKind.In));
56      AddVariableInfo(new VariableInfo("FunctionTree", "The tree to mutate", typeof(IFunctionTree), VariableKind.In | VariableKind.Out));
57      AddVariableInfo(new VariableInfo("TreeSize", "The size (number of nodes) of the tree", typeof(IntData), VariableKind.In | VariableKind.Out));
58      AddVariableInfo(new VariableInfo("TreeHeight", "The height of the tree", typeof(IntData), VariableKind.In | VariableKind.Out));
59    }
60
61
62    public override IOperation Apply(IScope scope) {
63      IFunctionTree root = GetVariableValue<IFunctionTree>("FunctionTree", scope, true);
64      MersenneTwister random = GetVariableValue<MersenneTwister>("Random", scope, true);
65      GPOperatorLibrary library = GetVariableValue<GPOperatorLibrary>("OperatorLibrary", scope, true);
66      int maxTreeHeight = GetVariableValue<IntData>("MaxTreeHeight", scope, true).Data;
67      int maxTreeSize = GetVariableValue<IntData>("MaxTreeSize", scope, true).Data;
68      TreeGardener gardener = new TreeGardener(random, library);
69      IFunctionTree parent = gardener.GetRandomParentNode(root);
70      // parent == null means we should cut out the root node
71      // => return a random sub-tree of the root
72      if (parent == null) {
73        // when there are sub-trees then replace the old tree with a random sub-tree
74        if (root.SubTrees.Count > 0) {
75          root = root.SubTrees[random.Next(root.SubTrees.Count)];
76          GetVariableValue<IntData>("TreeSize", scope, true).Data = root.Size;
77          GetVariableValue<IntData>("TreeHeight", scope, true).Data = root.Height;
78          // update the variable
79          scope.GetVariable(scope.TranslateName("FunctionTree")).Value = root;
80          Debug.Assert(gardener.IsValidTree(root));
81          // we reused a sub-tree so we don't have to schedule initialization operations
82          return null;
83        } else {
84          // we want to cut the root node and there are no sub-trees => create a new random terminal
85          IFunctionTree newTree;
86          newTree = gardener.CreateRandomTree(gardener.Terminals, 1, 1);
87          GetVariableValue<IntData>("TreeSize", scope, true).Data = newTree.Size;
88          GetVariableValue<IntData>("TreeHeight", scope, true).Data = newTree.Height;
89          // update the variable
90          scope.GetVariable(scope.TranslateName("FunctionTree")).Value = newTree;
91          Debug.Assert(gardener.IsValidTree(newTree));
92          // schedule an operation to initialize the whole tree
93          return gardener.CreateInitializationOperation(gardener.GetAllSubTrees(newTree), scope);
94        }
95      }
96      // select a child to cut away
97      int childIndex = random.Next(parent.SubTrees.Count);
98      IFunctionTree child = parent.SubTrees[childIndex];
99      // match the sub-trees of the child with the allowed sub-trees of the parent
100      ICollection<IFunction> allowedFunctions = gardener.GetAllowedSubFunctions(parent.Function, childIndex);
101      IFunctionTree[] possibleChilds = child.SubTrees.Where(t => allowedFunctions.Contains(t.Function)).ToArray();
102      if (possibleChilds.Length > 0) {
103        // replace child with a random child of that child
104        IFunctionTree selectedChild = possibleChilds[random.Next(possibleChilds.Length)];       
105        parent.RemoveSubTree(childIndex);
106        parent.InsertSubTree(childIndex, selectedChild);
107        Debug.Assert(gardener.IsValidTree(root));
108        // update the size and height of our tree
109        GetVariableValue<IntData>("TreeSize", scope, true).Data = root.Size;
110        GetVariableValue<IntData>("TreeHeight", scope, true).Data = root.Height;
111        // don't need to schedule initialization operations
112        return null;
113      } else {
114        // can't reuse an existing branch => create a new tree
115        // determine the level of the parent
116        int parentLevel = gardener.GetBranchLevel(root, parent);
117        // first remove the old child (first step essential!)
118        parent.RemoveSubTree(childIndex);
119        // then determine the number of nodes left over after the child has been removed!
120        int remainingNodes = root.Size;
121        allowedFunctions = gardener.GetAllowedSubFunctions(parent.Function, childIndex);
122        IFunctionTree newFunctionTree = gardener.CreateRandomTree(allowedFunctions, maxTreeSize - remainingNodes, maxTreeHeight - parentLevel);
123        parent.InsertSubTree(childIndex, newFunctionTree);
124        GetVariableValue<IntData>("TreeSize", scope, true).Data = root.Size;
125        GetVariableValue<IntData>("TreeHeight", scope, true).Data = root.Height;
126        Debug.Assert(gardener.IsValidTree(root));
127        // schedule an initialization operation for the new function-tree
128        return gardener.CreateInitializationOperation(gardener.GetAllSubTrees(newFunctionTree), scope);
129      }
130    }
131  }
132}
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