1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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 HEAL.Attic;
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26 | using HeuristicLab.Common;
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27 | using HeuristicLab.Core;
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28 | using HeuristicLab.Data;
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29 | using HeuristicLab.Parameters;
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30 |
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31 | namespace HeuristicLab.Problems.DataAnalysis {
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32 | [StorableType("8D44EABE-2D52-4501-B62D-5E28FB4CFEAE")]
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33 | [Item("ShapeConstrainedProblemData", "Represents an item containing all data defining a regression problem with shape constraints.")]
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34 | public class ShapeConstrainedRegressionProblemData : RegressionProblemData, IShapeConstrainedRegressionProblemData {
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35 | protected const string ShapeConstraintsParameterName = "ShapeConstraints";
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36 |
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37 | private static double[,] kozaF1 = new double[,] {
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38 | {2.017885919, -1.449165046},
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39 | {1.30060506, -1.344523885},
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40 | {1.147134798, -1.317989331},
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41 | {0.877182504, -1.266142284},
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42 | {0.852562452, -1.261020794},
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43 | {0.431095788, -1.158793317},
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44 | {0.112586002, -1.050908405},
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45 | {0.04594507, -1.021989402},
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46 | {0.042572879, -1.020438113},
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47 | {-0.074027291, -0.959859562},
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48 | {-0.109178553, -0.938094706},
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49 | {-0.259721109, -0.803635355},
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50 | {-0.272991057, -0.387519561},
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51 | {-0.161978191, -0.193611001},
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52 | {-0.102489983, -0.114215349},
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53 | {-0.01469968, -0.014918985},
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54 | {-0.008863365, -0.008942626},
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55 | {0.026751057, 0.026054094},
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56 | {0.166922436, 0.14309643},
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57 | {0.176953808, 0.1504144},
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58 | {0.190233418, 0.159916534},
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59 | {0.199800708, 0.166635331},
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60 | {0.261502822, 0.207600348},
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61 | {0.30182879, 0.232370249},
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62 | {0.83763905, 0.468046718}
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63 | };
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64 |
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65 | private static readonly Dataset defaultDataset;
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66 | private static readonly IEnumerable<string> defaultAllowedInputVariables;
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67 | private static readonly string defaultTargetVariable;
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68 |
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69 | private static readonly ShapeConstrainedRegressionProblemData emptyProblemData;
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70 | public new static ShapeConstrainedRegressionProblemData EmptyProblemData {
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71 | get { return emptyProblemData; }
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72 | }
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73 |
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74 | static ShapeConstrainedRegressionProblemData() {
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75 | defaultDataset = new Dataset(new string[] { "y", "x" }, kozaF1);
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76 | defaultDataset.Name = "Fourth-order Polynomial Function Benchmark Dataset";
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77 | defaultDataset.Description = "f(x) = x^4 + x^3 + x^2 + x^1";
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78 | defaultAllowedInputVariables = new List<string>() { "x" };
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79 | defaultTargetVariable = "y";
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80 | var problemData = new ShapeConstrainedRegressionProblemData();
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81 | problemData.Parameters.Clear(); // parameters are cleared and added below because we cannot set / change parameters of ProblemData
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82 | problemData.Name = "Empty Regression ProblemData";
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83 | problemData.Description = "This ProblemData acts as place holder before the correct problem data is loaded.";
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84 | problemData.isEmpty = true;
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85 |
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86 | problemData.Parameters.Add(new FixedValueParameter<Dataset>(DatasetParameterName, "", new Dataset()));
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87 | problemData.Parameters.Add(new FixedValueParameter<ReadOnlyCheckedItemList<StringValue>>(InputVariablesParameterName, ""));
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88 | problemData.Parameters.Add(new FixedValueParameter<IntRange>(TrainingPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly()));
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89 | problemData.Parameters.Add(new FixedValueParameter<IntRange>(TestPartitionParameterName, "", (IntRange)new IntRange(0, 0).AsReadOnly()));
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90 | problemData.Parameters.Add(new ConstrainedValueParameter<StringValue>(TargetVariableParameterName, new ItemSet<StringValue>()));
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91 | problemData.Parameters.Add(new FixedValueParameter<IntervalCollection>(VariableRangesParameterName, "", new IntervalCollection()));
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92 | problemData.Parameters.Add(new FixedValueParameter<ShapeConstraints>(ShapeConstraintsParameterName, "", new ShapeConstraints()));
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93 | emptyProblemData = problemData;
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94 | }
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95 |
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96 | public IFixedValueParameter<ShapeConstraints> ShapeConstraintsParameter => (IFixedValueParameter<ShapeConstraints>)Parameters[ShapeConstraintsParameterName];
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97 | public ShapeConstraints ShapeConstraints => ShapeConstraintsParameter.Value;
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98 |
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99 | [StorableConstructor]
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100 | protected ShapeConstrainedRegressionProblemData(StorableConstructorFlag _) : base(_) { }
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101 |
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102 | protected ShapeConstrainedRegressionProblemData(ShapeConstrainedRegressionProblemData original, Cloner cloner) : base(original, cloner) {
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103 | RegisterEventHandlers();
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104 | }
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105 |
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106 | [StorableHook(HookType.AfterDeserialization)]
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107 | private void AfterDeserialization() {
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108 | RegisterEventHandlers();
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109 | }
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110 | public override IDeepCloneable Clone(Cloner cloner) {
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111 | if (this == emptyProblemData) return emptyProblemData;
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112 | return new ShapeConstrainedRegressionProblemData(this, cloner);
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113 | }
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114 |
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115 | public ShapeConstrainedRegressionProblemData() : this(defaultDataset, defaultAllowedInputVariables, defaultTargetVariable,
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116 | trainingPartition: new IntRange(0, defaultDataset.Rows),
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117 | testPartition: new IntRange(0, 0)) { } // no test partition for the demo problem
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118 |
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119 | public ShapeConstrainedRegressionProblemData(IRegressionProblemData regressionProblemData)
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120 | : this(regressionProblemData.Dataset, regressionProblemData.AllowedInputVariables, regressionProblemData.TargetVariable,
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121 | regressionProblemData.TrainingPartition, regressionProblemData.TestPartition) {
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122 | }
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123 |
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124 | public ShapeConstrainedRegressionProblemData(IDataset dataset, IEnumerable<string> allowedInputVariables, string targetVariable,
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125 | IntRange trainingPartition, IntRange testPartition,
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126 | IEnumerable<ITransformation> transformations = null, ShapeConstraints sc = null)
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127 | : base(dataset, allowedInputVariables, targetVariable, transformations ?? Enumerable.Empty<ITransformation>()) {
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128 | TrainingPartition.Start = trainingPartition.Start;
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129 | TrainingPartition.End = trainingPartition.End;
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130 | TestPartition.Start = testPartition.Start;
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131 | TestPartition.End = testPartition.End;
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132 | if (sc == null) sc = new ShapeConstraints();
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133 | Parameters.Add(new FixedValueParameter<ShapeConstraints>(ShapeConstraintsParameterName, "Specifies the shape constraints for the regression problem.", (ShapeConstraints)sc.Clone()));
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134 |
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135 | RegisterEventHandlers();
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136 | }
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137 |
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138 | private void RegisterEventHandlers() {
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139 | ShapeConstraints.Changed += ShapeConstraints_Changed;
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140 | ShapeConstraints.CheckedItemsChanged += ShapeConstraints_Changed;
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141 | ShapeConstraints.CollectionReset += ShapeConstraints_Changed;
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142 | ShapeConstraints.ItemsAdded += ShapeConstraints_Changed;
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143 | ShapeConstraints.ItemsRemoved += ShapeConstraints_Changed;
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144 | ShapeConstraints.ItemsMoved += ShapeConstraints_Changed;
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145 | ShapeConstraints.ItemsReplaced += ShapeConstraints_Changed;
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146 | }
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147 |
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148 | private void ShapeConstraints_Changed(object sender, EventArgs e) {
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149 | OnChanged();
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150 | }
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151 | }
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152 | }
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