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source: trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/TreeEvaluatorInjector.cs @ 1814

Last change on this file since 1814 was 1796, checked in by gkronber, 15 years ago

Refactored GP evaluation to make it possible to use different evaluators to interpret function trees. #615 (Evaluation of HL3 function trees should be equivalent to evaluation in HL2)

File size: 3.2 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.Text;
25using System.Xml;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.DataAnalysis;
29using HeuristicLab.Constraints;
30using StructId = HeuristicLab.GP.StructureIdentification;
31
32namespace HeuristicLab.GP.StructureIdentification {
33  public class TreeEvaluatorInjector : OperatorBase {
34    private const string DATASET = "Dataset";
35    private const string TARGETVARIABLE = "TargetVariable";
36    private const string TRAININGSAMPLESSTART = "TrainingSamplesStart";
37    private const string TRAININGSAMPLESEND = "TrainingSamplesEnd";
38    private const string PUNISHMENTFACTOR = "PunishmentFactor";
39    private const string TREEEVALUATOR = "TreeEvaluator";
40
41
42    public override string Description {
43      get { return @"Injects a GP tree evaluator."; }
44    }
45
46    public TreeEvaluatorInjector()
47      : base() {
48      AddVariableInfo(new VariableInfo(DATASET, "The input dataset", typeof(Dataset), VariableKind.In));
49      AddVariableInfo(new VariableInfo(TARGETVARIABLE, "The target variable", typeof(IntData), VariableKind.In));
50      AddVariableInfo(new VariableInfo(TRAININGSAMPLESSTART, "Beginning of training set", typeof(IntData), VariableKind.In));
51      AddVariableInfo(new VariableInfo(TRAININGSAMPLESEND, "End of training set", typeof(IntData), VariableKind.In));
52      AddVariableInfo(new VariableInfo(PUNISHMENTFACTOR, "Punishmentfactor", typeof(DoubleData), VariableKind.In));
53      AddVariableInfo(new VariableInfo(TREEEVALUATOR, "TreeEvaluator", typeof(BakedTreeEvaluator), VariableKind.New));
54    }
55
56    public override IOperation Apply(IScope scope) {
57      Dataset ds = GetVariableValue<Dataset>(DATASET, scope, true);
58      int targetVariable = GetVariableValue<IntData>(TARGETVARIABLE, scope, true).Data;
59      int start = GetVariableValue<IntData>(TRAININGSAMPLESSTART, scope, true).Data;
60      int end = GetVariableValue<IntData>(TRAININGSAMPLESEND, scope, true).Data;
61      double punishmentFactor = GetVariableValue<DoubleData>(PUNISHMENTFACTOR, scope, true).Data;
62
63      BakedTreeEvaluator evaluator = new BakedTreeEvaluator();
64      evaluator.ResetEvaluator(ds, targetVariable, start, end, punishmentFactor);
65
66      scope.AddVariable(new HeuristicLab.Core.Variable(TREEEVALUATOR, evaluator));
67
68      return null;
69    }
70  }
71}
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