1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System.Collections.Generic;
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23 | using System.Linq;
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24 | using HeuristicLab.Common;
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25 | using HeuristicLab.Core;
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26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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27 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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28 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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29 |
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30 | namespace HeuristicLab.Problems.DataAnalysis.Trading.Symbolic {
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31 | /// <summary>
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32 | /// Represents a symbolic trading model
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33 | /// </summary>
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34 | [StorableClass]
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35 | [Item(Name = "Model (symbolic trading)", Description = "Represents a symbolic trading model.")]
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36 | public class Model : SymbolicDataAnalysisModel, IModel {
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37 |
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38 | [StorableConstructor]
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39 | protected Model(bool deserializing) : base(deserializing) { }
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40 | protected Model(Model original, Cloner cloner)
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41 | : base(original, cloner) { }
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42 | public Model(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter)
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43 | : base(tree, interpreter, -10, 10) { }
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44 |
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45 | public override IDeepCloneable Clone(Cloner cloner) {
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46 | return new Model(this, cloner);
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47 | }
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48 |
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49 | public IEnumerable<double> GetSignals(IDataset dataset, IEnumerable<int> rows) {
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50 | ISymbolicDataAnalysisExpressionTreeInterpreter interpreter = Interpreter;
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51 | ISymbolicExpressionTree tree = SymbolicExpressionTree;
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52 | return GetSignals(interpreter.GetSymbolicExpressionTreeValues(tree, dataset, rows));
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53 | }
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54 |
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55 | // Transforms an enumerable of real values to an enumerable of trading signals (buy(1) / hold(0) / sell(-1))
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56 | public static IEnumerable<double> GetSignals(IEnumerable<double> xs) {
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57 | // two iterations over xs
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58 | // 1) determine min / max to calculate the mid-range value
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59 | // 2) range is split into three thirds
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60 | double max = double.NegativeInfinity;
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61 | double min = double.PositiveInfinity;
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62 | foreach (var x in xs) {
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63 | if (x > max) max = x;
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64 | if (x < min) min = x;
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65 | }
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66 | if (double.IsInfinity(max) || double.IsNaN(max) || double.IsInfinity(min) || double.IsNaN(min))
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67 | return xs.Select(x => 0.0);
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68 |
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69 | double range = (max - min);
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70 | double midRange = range / 2.0 + min;
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71 | double offset = range / 6.0;
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72 | return from x in xs
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73 | select x > midRange + offset ? 1.0 : x < midRange - offset ? -1.0 : 0.0;
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74 | }
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75 | }
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76 | }
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