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source: trunk/sources/HeuristicLab.GP/TrainingWindowSlider.cs @ 1480

Last change on this file since 1480 was 1480, checked in by gkronber, 15 years ago

Changed sliding window approach to stop at the last window. #564 (Sliding window approach for data-based modeling)

File size: 3.1 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;
23using System.Collections.Generic;
24using System.Text;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Random;
28
29namespace HeuristicLab.GP {
30  public class TrainingWindowSlider : OperatorBase {
31
32    private const string TRAINING_SAMPLES_START = "TrainingSamplesStart";
33    private const string TRAINING_SAMPLES_END = "TrainingSamplesEnd";
34    private const string TRAINING_WINDOW_START = "TrainingWindowStart";
35    private const string TRAINING_WINDOW_END = "TrainingWindowEnd";
36    private const string WINDOW_SIZE = "WindowSize";
37    private const string STEP_SIZE = "SlidingStepSize";
38
39    public override string Description {
40      get { return @"Modifies variables TrainingSamplesStart and TrainingSamplesEnd to have a continually sliding window over the whole training data set."; }
41    }
42
43    public TrainingWindowSlider() {
44      AddVariableInfo(new VariableInfo(TRAINING_SAMPLES_START, "Start of whole training set", typeof(IntData), VariableKind.In));
45      AddVariableInfo(new VariableInfo(TRAINING_SAMPLES_END, "End of whole training set", typeof(IntData), VariableKind.In));
46      AddVariableInfo(new VariableInfo(TRAINING_WINDOW_START, "Start of training set window", typeof(IntData), VariableKind.In | VariableKind.Out));
47      AddVariableInfo(new VariableInfo(TRAINING_WINDOW_END, "End of training set window", typeof(IntData), VariableKind.In | VariableKind.Out));
48      AddVariableInfo(new VariableInfo(STEP_SIZE, "Number of samples to slide the window forward", typeof(IntData), VariableKind.In));
49    }
50
51    public override IOperation Apply(IScope scope) {
52      int trainingSamplesStart = GetVariableValue<IntData>(TRAINING_SAMPLES_START, scope, true).Data;
53      int trainingSamplesEnd = GetVariableValue<IntData>(TRAINING_SAMPLES_END, scope, true).Data;
54      int trainingWindowStart = GetVariableValue<IntData>(TRAINING_WINDOW_START, scope, true).Data;
55      int trainingWindowEnd = GetVariableValue<IntData>(TRAINING_WINDOW_END, scope, true).Data;
56      int stepSize = GetVariableValue<IntData>(STEP_SIZE, scope, true).Data;
57
58      if (trainingWindowEnd + stepSize <= trainingSamplesEnd) {
59        trainingWindowStart = trainingWindowStart + stepSize;
60        trainingWindowEnd = trainingWindowEnd + stepSize;
61      }
62
63      return null;
64    }
65  }
66}
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