1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2008 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 HeuristicLab.Core;
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24 | using HeuristicLab.Data;
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25 | using HeuristicLab.GP.Interfaces;
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26 | using HeuristicLab.GP;
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27 | using HeuristicLab.Modeling;
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28 | using System;
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29 | using System.Xml;
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30 | using HeuristicLab.DataAnalysis;
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31 |
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32 | namespace HeuristicLab.GP.StructureIdentification {
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33 | public class Predictor : PredictorBase {
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34 | private ITreeEvaluator treeEvaluator;
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35 |
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36 | private IGeneticProgrammingModel functionTree;
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37 | public IGeneticProgrammingModel FunctionTree {
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38 | get { return functionTree; }
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39 | }
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40 | public Predictor() : base() { } // for persistence
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41 | public Predictor(ITreeEvaluator evaluator, IGeneticProgrammingModel tree, double lowerPredictionLimit, double upperPredictionLimit)
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42 | : base(lowerPredictionLimit, upperPredictionLimit) {
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43 | this.treeEvaluator = evaluator;
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44 | this.functionTree = tree;
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45 | }
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46 |
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47 | public override double[] Predict(Dataset input, int start, int end) {
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48 | treeEvaluator.UpperEvaluationLimit = UpperPredictionLimit;
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49 | treeEvaluator.LowerEvaluationLimit = LowerPredictionLimit;
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50 |
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51 | if (start < 0 || end <= start) throw new ArgumentException("start must be larger than zero and strictly smaller than end");
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52 | if (end > input.Rows) throw new ArgumentOutOfRangeException("number of rows in input is smaller then end");
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53 | treeEvaluator.PrepareForEvaluation(input, functionTree.FunctionTree);
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54 | double[] result = new double[end - start];
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55 | for (int i = 0; i < result.Length; i++) {
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56 | result[i] = treeEvaluator.Evaluate(i + start);
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57 | }
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58 | return result;
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59 | }
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60 |
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61 | public override IView CreateView() {
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62 | return new PredictorView(this);
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63 | }
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64 |
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65 | public override object Clone(IDictionary<Guid, object> clonedObjects) {
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66 | Predictor clone = (Predictor)base.Clone(clonedObjects);
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67 | clone.treeEvaluator = (ITreeEvaluator)Auxiliary.Clone(treeEvaluator, clonedObjects);
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68 | clone.functionTree = (IGeneticProgrammingModel)Auxiliary.Clone(functionTree, clonedObjects);
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69 | return clone;
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70 | }
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71 |
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72 | public override System.Xml.XmlNode GetXmlNode(string name, System.Xml.XmlDocument document, IDictionary<Guid, IStorable> persistedObjects) {
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73 | XmlNode node = base.GetXmlNode(name, document, persistedObjects);
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74 | node.AppendChild(PersistenceManager.Persist("Evaluator", treeEvaluator, document, persistedObjects));
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75 | node.AppendChild(PersistenceManager.Persist("FunctionTree", functionTree, document, persistedObjects));
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76 | return node;
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77 | }
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78 |
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79 | public override void Populate(System.Xml.XmlNode node, IDictionary<Guid, IStorable> restoredObjects) {
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80 | base.Populate(node, restoredObjects);
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81 | treeEvaluator = (ITreeEvaluator)PersistenceManager.Restore(node.SelectSingleNode("Evaluator"), restoredObjects);
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82 | functionTree = (IGeneticProgrammingModel)PersistenceManager.Restore(node.SelectSingleNode("FunctionTree"), restoredObjects);
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83 | }
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84 | }
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85 | }
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