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source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/DataAnalysisProblemData.cs @ 5681

Last change on this file since 5681 was 5649, checked in by gkronber, 14 years ago

#1418 Implemented classes for classification based on a discriminant function and thresholds and implemented interfaces and base classes for clustering.

File size: 7.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Collections;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Data;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31
32namespace HeuristicLab.Problems.DataAnalysis {
33  [StorableClass]
34  public abstract class DataAnalysisProblemData : ParameterizedNamedItem, IDataAnalysisProblemData {
35    private const string DatasetParameterName = "Dataset";
36    private const string InputVariablesParameterName = "InputVariables";
37    private const string TrainingPartitionStartParameterName = "TrainingPartitionStart";
38    private const string TrainingPartitionEndParameterName = "TrainingPartitionEnd";
39    private const string TestPartitionStartParameterName = "TestPartitionStart";
40    private const string TestPartitionEndParameterName = "TestPartitionEnd";
41
42    #region parameter properites
43    public IFixedValueParameter<Dataset> DatasetParameter {
44      get { return (IFixedValueParameter<Dataset>)Parameters[DatasetParameterName]; }
45    }
46    public IFixedValueParameter<ICheckedItemList<StringValue>> InputVariablesParameter {
47      get { return (IFixedValueParameter<ICheckedItemList<StringValue>>)Parameters[InputVariablesParameterName]; }
48    }
49    public IFixedValueParameter<IntValue> TrainingPartitionStartParameter {
50      get { return (IFixedValueParameter<IntValue>)Parameters[TrainingPartitionStartParameterName]; }
51    }
52    public IFixedValueParameter<IntValue> TrainingPartitionEndParameter {
53      get { return (IFixedValueParameter<IntValue>)Parameters[TrainingPartitionEndParameterName]; }
54    }
55    public IFixedValueParameter<IntValue> TestPartitionStartParameter {
56      get { return (IFixedValueParameter<IntValue>)Parameters[TestPartitionStartParameterName]; }
57    }
58    public IFixedValueParameter<IntValue> TestPartitionEndParameter {
59      get { return (IFixedValueParameter<IntValue>)Parameters[TestPartitionEndParameterName]; }
60    }
61    #endregion
62
63    #region propeties
64    public Dataset Dataset {
65      get { return DatasetParameter.Value; }
66    }
67    public ICheckedItemList<StringValue> InputVariables {
68      get { return InputVariablesParameter.Value; }
69    }
70    public IEnumerable<string> AllowedInputVariables {
71      get { return InputVariables.CheckedItems.Select(x => x.Value.Value); }
72    }
73
74    public IntValue TrainingPartitionStart {
75      get { return TrainingPartitionStartParameter.Value; }
76    }
77    public IntValue TrainingPartitionEnd {
78      get { return TrainingPartitionEndParameter.Value; }
79    }
80    public IntValue TestPartitionStart {
81      get { return TestPartitionStartParameter.Value; }
82    }
83    public IntValue TestPartitionEnd {
84      get { return TestPartitionEndParameter.Value; }
85    }
86
87    public IEnumerable<int> TrainingIndizes {
88      get {
89        return Enumerable.Range(TrainingPartitionStart.Value, TrainingPartitionEnd.Value - TrainingPartitionStart.Value)
90                         .Where(i => i >= 0 && i < Dataset.Rows && (i < TestPartitionStart.Value || TestPartitionEnd.Value <= i));
91      }
92    }
93    public IEnumerable<int> TestIndizes {
94      get {
95        return Enumerable.Range(TestPartitionStart.Value, TestPartitionEnd.Value - TestPartitionStart.Value)
96           .Where(i => i >= 0 && i < Dataset.Rows);
97      }
98    }
99    #endregion
100
101    protected DataAnalysisProblemData(DataAnalysisProblemData original, Cloner cloner) : base(original, cloner) { }
102    [StorableConstructor]
103    protected DataAnalysisProblemData(bool deserializing) : base(deserializing) { }
104
105    protected DataAnalysisProblemData(Dataset dataset, IEnumerable<string> allowedInputVariables) {
106      if (dataset == null) throw new ArgumentNullException("The dataset must not be null.");
107      if (allowedInputVariables == null) throw new ArgumentNullException("The allowedInputVariables must not be null.");
108
109      if (allowedInputVariables.Except(dataset.VariableNames).Any())
110        throw new ArgumentException("All allowed input variables must be present in the dataset.");
111
112      var inputVariables = new CheckedItemList<StringValue>(dataset.VariableNames.Select(x => new StringValue(x)));
113      foreach (StringValue x in inputVariables)
114        inputVariables.SetItemCheckedState(x, allowedInputVariables.Contains(x.Value));
115
116      int trainingPartitionStart = 0;
117      int trainingPartitionEnd = dataset.Rows / 2;
118      int testPartitionStart = dataset.Rows / 2;
119      int testPartitionEnd = dataset.Rows;
120
121      Parameters.Add(new FixedValueParameter<Dataset>(DatasetParameterName, "", dataset));
122      Parameters.Add(new FixedValueParameter<ICheckedItemList<StringValue>>(InputVariablesParameterName, "", inputVariables.AsReadOnly()));
123      Parameters.Add(new FixedValueParameter<IntValue>(TrainingPartitionStartParameterName, "", new IntValue(trainingPartitionStart)));
124      Parameters.Add(new FixedValueParameter<IntValue>(TrainingPartitionEndParameterName, "", new IntValue(trainingPartitionEnd)));
125      Parameters.Add(new FixedValueParameter<IntValue>(TestPartitionStartParameterName, "", new IntValue(testPartitionStart)));
126      Parameters.Add(new FixedValueParameter<IntValue>(TestPartitionEndParameterName, "", new IntValue(testPartitionEnd)));
127
128      ((ValueParameter<Dataset>)DatasetParameter).ReactOnValueToStringChangedAndValueItemImageChanged = false;
129      RegisterEventHandlers();
130    }
131
132    private void RegisterEventHandlers() {
133      DatasetParameter.ValueChanged += new EventHandler(Parameter_ValueChanged);
134      InputVariables.CheckedItemsChanged += new CollectionItemsChangedEventHandler<IndexedItem<StringValue>>(InputVariables_CheckedItemsChanged);
135      TrainingPartitionStart.ValueChanged += new EventHandler(Parameter_ValueChanged);
136      TrainingPartitionEnd.ValueChanged += new EventHandler(Parameter_ValueChanged);
137      TestPartitionStart.ValueChanged += new EventHandler(Parameter_ValueChanged);
138      TestPartitionEnd.ValueChanged += new EventHandler(Parameter_ValueChanged);
139    }
140
141    private void InputVariables_CheckedItemsChanged(object sender, CollectionItemsChangedEventArgs<IndexedItem<StringValue>> e) {
142      OnChanged();
143    }
144
145    private void Parameter_ValueChanged(object sender, EventArgs e) {
146      OnChanged();
147    }
148
149    public event EventHandler Changed;
150    protected virtual void OnChanged() {
151      var listeners = Changed;
152      if (listeners != null) listeners(this, EventArgs.Empty);
153    }
154  }
155}
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