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source: stable/HeuristicLab.Problems.DataAnalysis.Trading/3.4/Symbolic/Model.cs @ 10188

Last change on this file since 10188 was 10020, checked in by gkronber, 11 years ago

#1508: merged r9804:9805,r9808:9809,r9811:9812,r9822,r9824:9825,r9897,r9928,r9938:9941,r9964:9965,r9989,r9991:9992,r9995,r9997,r10004:10015 from trunk into stable branch.

File size: 3.1 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis.Symbolic;
29
30namespace HeuristicLab.Problems.DataAnalysis.Trading.Symbolic {
31  /// <summary>
32  /// Represents a symbolic trading model
33  /// </summary>
34  [StorableClass]
35  [Item(Name = "Model (symbolic trading)", Description = "Represents a symbolic trading model.")]
36  public class Model : SymbolicDataAnalysisModel, IModel {
37
38    [StorableConstructor]
39    protected Model(bool deserializing) : base(deserializing) { }
40    protected Model(Model original, Cloner cloner)
41      : base(original, cloner) { }
42    public Model(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter)
43      : base(tree, interpreter, -10, 10) { }
44
45    public override IDeepCloneable Clone(Cloner cloner) {
46      return new Model(this, cloner);
47    }
48
49    public IEnumerable<double> GetSignals(Dataset dataset, IEnumerable<int> rows) {
50      ISymbolicDataAnalysisExpressionTreeInterpreter interpreter = Interpreter;
51      ISymbolicExpressionTree tree = SymbolicExpressionTree;
52      return GetSignals(interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows));
53    }
54
55    // Transforms an enumerable of real values to an enumerable of trading signals (buy(1) / hold(0) / sell(-1))
56    public static IEnumerable<double> GetSignals(IEnumerable<double> xs) {
57      // two iterations over xs
58      // 1) determine min / max to calculate the mid-range value
59      // 2) range is split into three thirds
60      double max = double.NegativeInfinity;
61      double min = double.PositiveInfinity;
62      foreach (var x in xs) {
63        if (x > max) max = x;
64        if (x < min) min = x;
65      }
66      if (double.IsInfinity(max) || double.IsNaN(max) || double.IsInfinity(min) || double.IsNaN(min))
67        return xs.Select(x => 0.0);
68
69      double range = (max - min);
70      double midRange = range / 2.0 + min;
71      double offset = range / 6.0;
72      return from x in xs
73             select x > midRange + offset ? 1.0 : x < midRange - offset ? -1.0 : 0.0;
74    }
75  }
76}
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