[2041] | 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.Text;
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| 25 | using System.Xml;
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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 | using System.Linq;
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| 30 |
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| 31 | namespace HeuristicLab.Modeling {
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| 32 | public abstract class VariableImpactCalculatorBase<T> : OperatorBase {
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| 33 | public override string Description {
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| 34 | get { return @"Calculates the impact of all allowed input variables on the model."; }
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| 35 | }
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| 36 |
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| 37 | public abstract string OutputVariableName { get; }
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| 38 |
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| 39 | public VariableImpactCalculatorBase()
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| 40 | : base() {
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| 41 | AddVariableInfo(new VariableInfo("Dataset", "Dataset", typeof(Dataset), VariableKind.In));
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| 42 | AddVariableInfo(new VariableInfo("TargetVariable", "TargetVariable", typeof(IntData), VariableKind.In));
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| 43 | AddVariableInfo(new VariableInfo("AllowedFeatures", "Indexes of allowed input variables", typeof(ItemList<IntData>), VariableKind.In));
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| 44 | AddVariableInfo(new VariableInfo("TrainingSamplesStart", "TrainingSamplesStart", typeof(IntData), VariableKind.In));
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| 45 | AddVariableInfo(new VariableInfo("TrainingSamplesEnd", "TrainingSamplesEnd", typeof(IntData), VariableKind.In));
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| 46 | AddVariableInfo(new VariableInfo(OutputVariableName, OutputVariableName, typeof(ItemList), VariableKind.New));
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| 47 | }
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| 48 |
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| 49 | public override IOperation Apply(IScope scope) {
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| 50 | ItemList<IntData> allowedFeatures = GetVariableValue<ItemList<IntData>>("AllowedFeatures", scope, true);
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| 51 | int targetVariable = GetVariableValue<IntData>("TargetVariable", scope, true).Data;
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| 52 | Dataset dataset = GetVariableValue<Dataset>("Dataset", scope, true);
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| 53 | Dataset dirtyDataset = (Dataset)dataset.Clone();
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| 54 | int start = GetVariableValue<IntData>("TrainingSamplesStart", scope, true).Data;
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| 55 | int end = GetVariableValue<IntData>("TrainingSamplesEnd", scope, true).Data;
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| 56 |
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| 57 | T referenceValue = CalculateValue(scope, dataset, targetVariable, start, end);
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| 58 | double[] impacts = new double[allowedFeatures.Count];
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| 59 |
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| 60 | for (int i = 0; i < allowedFeatures.Count; i++) {
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| 61 | int currentVariable = allowedFeatures[i].Data;
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| 62 | var oldValues = ReplaceVariableValues(dirtyDataset, currentVariable , CalculateNewValues(dirtyDataset, currentVariable, start, end), start, end);
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| 63 | T newValue = CalculateValue(scope, dirtyDataset, targetVariable, start, end);
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| 64 | impacts[i] = CalculateImpact(referenceValue, newValue);
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| 65 | ReplaceVariableValues(dirtyDataset, currentVariable, oldValues, start, end);
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| 66 | }
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| 67 |
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| 68 | impacts = PostProcessImpacts(impacts);
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| 69 |
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| 70 | ItemList variableImpacts = new ItemList();
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| 71 | for (int i = 0; i < allowedFeatures.Count; i++) {
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| 72 | int currentVariable = allowedFeatures[i].Data;
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| 73 | ItemList row = new ItemList();
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| 74 | row.Add(new StringData(dataset.GetVariableName(currentVariable)));
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| 75 | row.Add(new DoubleData(impacts[i]));
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| 76 | variableImpacts.Add(row);
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| 77 | }
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| 78 |
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| 79 | scope.AddVariable(new Variable(scope.TranslateName(OutputVariableName), variableImpacts));
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| 80 | return null;
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| 81 | }
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| 82 |
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| 83 | protected abstract T CalculateValue(IScope scope, Dataset dataset, int targetVariable, int start, int end);
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| 84 |
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| 85 | protected abstract double CalculateImpact(T referenceValue, T newValue);
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| 86 |
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| 87 | protected virtual double[] PostProcessImpacts(double[] impacts) {
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| 88 | return impacts;
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| 89 | }
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| 90 |
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| 91 | private IEnumerable<double> ReplaceVariableValues(Dataset ds, int variableIndex, IEnumerable<double> newValues, int start, int end) {
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| 92 | double[] oldValues = new double[end - start];
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| 93 | for (int i = 0; i < end - start; i++) oldValues[i] = ds.GetValue(i + start, variableIndex);
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| 94 | if (newValues.Count() != end - start) throw new ArgumentException("The length of the new values sequence doesn't match the required length (number of replaced values)");
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| 95 |
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| 96 | int index = start;
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| 97 | ds.FireChangeEvents = false;
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| 98 | foreach(double v in newValues) {
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| 99 | ds.SetValue(index++, variableIndex, v);
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| 100 | }
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| 101 | ds.FireChangeEvents = true;
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| 102 | ds.FireChanged();
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| 103 | return oldValues;
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| 104 | }
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| 105 |
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| 106 | private IEnumerable<double> CalculateNewValues(Dataset ds, int variableIndex, int start, int end) {
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| 107 | double mean = ds.GetMean(variableIndex, start, end);
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| 108 | return Enumerable.Repeat(mean, end - start);
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| 109 | }
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| 110 | }
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| 111 | }
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