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;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using System.Text;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.DataAnalysis;
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29 |
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30 | namespace HeuristicLab.GP.StructureIdentification.ConditionalEvaluation {
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31 | public abstract class ConditionalEvaluatorBase : GPEvaluatorBase {
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32 | public virtual string OutputVariableName { get { return "Quality"; } }
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33 |
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34 | public ConditionalEvaluatorBase()
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35 | : base() {
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36 | AddVariableInfo(new VariableInfo("MaxTimeOffset", "Maximal time offset for all feature", typeof(IntData), VariableKind.In));
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37 | AddVariableInfo(new VariableInfo("MinTimeOffset", "Minimal time offset for all feature", typeof(IntData), VariableKind.In));
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38 | AddVariableInfo(new VariableInfo("ConditionVariable", "Variable index which indicates if the row should be evaluated (0 means do not evaluate, != 0 evaluate)", typeof(IntData), VariableKind.In));
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39 | AddVariableInfo(new VariableInfo(OutputVariableName, OutputVariableName, typeof(DoubleData), VariableKind.New | VariableKind.Out));
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40 | }
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41 |
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42 | public override void Evaluate(IScope scope, ITreeEvaluator evaluator, Dataset dataset, int targetVariable, int start, int end, bool updateTargetValues) {
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43 | int maxTimeOffset = GetVariableValue<IntData>("MaxTimeOffset", scope, true).Data;
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44 | int minTimeOffset = GetVariableValue<IntData>("MinTimeOffset", scope, true).Data;
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45 | int conditionVariable = GetVariableValue<IntData>("ConditionVariable", scope, true).Data;
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46 |
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47 | // store original and estimated values in a double array
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48 | double[,] values = new double[end - start, 2];
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49 | for (int sample = start; sample < end; sample++) {
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50 | // check if condition variable is true between sample - minTimeOffset and sample - maxTimeOffset
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51 | bool skip = false;
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52 | for (int checkIndex = sample - minTimeOffset; checkIndex <= sample - maxTimeOffset && !skip ; checkIndex++) {
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53 | if (dataset.GetValue(checkIndex, conditionVariable) == 0)
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54 | skip = true;
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55 | }
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56 | if (!skip) {
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57 | double original = dataset.GetValue(sample, targetVariable);
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58 | double estimated = evaluator.Evaluate(sample);
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59 | if (updateTargetValues) {
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60 | dataset.SetValue(sample, targetVariable, estimated);
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61 | }
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62 | values[sample - start, 0] = estimated;
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63 | values[sample - start, 1] = original;
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64 | }
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65 | }
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66 |
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67 | // calculate quality value
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68 | double quality = Evaluate(values);
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69 |
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70 | DoubleData qualityData = GetVariableValue<DoubleData>(OutputVariableName, scope, false, false);
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71 | if (qualityData == null) {
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72 | qualityData = new DoubleData();
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73 | scope.AddVariable(new HeuristicLab.Core.Variable(scope.TranslateName(OutputVariableName), qualityData));
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74 | }
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75 | qualityData.Data = quality;
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76 | }
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77 |
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78 | public abstract double Evaluate(double[,] values);
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79 | }
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80 | }
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