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source: trunk/sources/HeuristicLab.GP.Operators/3.3/Initialization/RampedTreeCreator.cs @ 3446

Last change on this file since 3446 was 2222, checked in by gkronber, 15 years ago

Merged changes from GP-refactoring branch back into the trunk #713.

File size: 3.6 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 HeuristicLab.Core;
23using HeuristicLab.Data;
24using System;
25using HeuristicLab.Random;
26using System.Diagnostics;
27using HeuristicLab.GP.Interfaces;
28
29namespace HeuristicLab.GP.Operators {
30  public class RampedTreeCreator : OperatorBase {
31    public override string Description {
32      get { return @"Generates a new random operator tree."; }
33    }
34
35    public RampedTreeCreator()
36      : base() {
37      AddVariableInfo(new VariableInfo("Random", "Uniform random number generator", typeof(MersenneTwister), VariableKind.In));
38      AddVariableInfo(new VariableInfo("FunctionLibrary", "The function library containing all available functions", typeof(FunctionLibrary), VariableKind.In));
39      AddVariableInfo(new VariableInfo("MinTreeHeight", "The minimal allowed height of the tree", typeof(IntData), VariableKind.In));
40      AddVariableInfo(new VariableInfo("MaxTreeHeight", "The maximal allowed height of the tree", typeof(IntData), VariableKind.In));
41      AddVariableInfo(new VariableInfo("BalancedTreesRate", "Determines how many trees should be balanced", typeof(DoubleData), VariableKind.In));
42      AddVariableInfo(new VariableInfo("FunctionTree", "The created tree", typeof(IGeneticProgrammingModel), VariableKind.New | VariableKind.Out));
43      AddVariableInfo(new VariableInfo("TreeSize", "The size (number of nodes) of the tree", typeof(IntData), VariableKind.New | VariableKind.Out));
44      AddVariableInfo(new VariableInfo("TreeHeight", "The height of the tree", typeof(IntData), VariableKind.New | VariableKind.Out));
45    }
46
47    public override IOperation Apply(IScope scope) {
48      IRandom random = GetVariableValue<IRandom>("Random", scope, true);
49      FunctionLibrary opLibrary = GetVariableValue<FunctionLibrary>("FunctionLibrary", scope, true);
50      int minTreeHeight = GetVariableValue<IntData>("MinTreeHeight", scope, true).Data;
51      int maxTreeHeight = GetVariableValue<IntData>("MaxTreeHeight", scope, true).Data;
52      double balancedTreesRate = GetVariableValue<DoubleData>("BalancedTreesRate", scope, true).Data;
53
54      TreeGardener gardener = new TreeGardener(random, opLibrary);
55
56      int treeHeight = random.Next(minTreeHeight, maxTreeHeight + 1);
57      IFunctionTree root;
58      if(random.NextDouble() <= balancedTreesRate) {
59        root = gardener.CreateBalancedRandomTree(Int32.MaxValue, treeHeight);
60      } else {
61        root = gardener.CreateUnbalancedRandomTree(Int32.MaxValue, treeHeight);
62      }
63
64      Debug.Assert(gardener.IsValidTree(root) && root.GetHeight() <= maxTreeHeight);
65
66      scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName("FunctionTree"), new GeneticProgrammingModel(root)));
67      return Util.CreateInitializationOperation(TreeGardener.GetAllSubTrees(root), scope);
68    }
69  }
70}
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