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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/DataAnalysisSolution.cs @ 3981

Last change on this file since 3981 was 3979, checked in by mkommend, 14 years ago

corrected DataAnalysis.Views.ResultsView to use an internal DoubleMatrix (ticket #1020)

File size: 5.9 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2010 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 HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Data;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using System.Collections.Generic;
29using System.Linq;
30using HeuristicLab.Problems.DataAnalysis.Evaluators;
31
32namespace HeuristicLab.Problems.DataAnalysis {
33  /// <summary>
34  /// Represents a solution for a data analysis problem which can be visualized in the GUI.
35  /// </summary>
36  [Item("DataAnalysisSolution", "Represents a solution for a data analysis problem which can be visualized in the GUI.")]
37  [StorableClass]
38  public abstract class DataAnalysisSolution : NamedItem {
39    protected DataAnalysisSolution()
40      : base() { }
41    protected DataAnalysisSolution(DataAnalysisProblemData problemData) : this(problemData, double.NegativeInfinity, double.PositiveInfinity) { }
42    protected DataAnalysisSolution(DataAnalysisProblemData problemData, double lowerEstimationLimit, double upperEstimationLimit)
43      : this() {
44      this.problemData = problemData;
45      this.lowerEstimationLimit = lowerEstimationLimit;
46      this.upperEstimationLimit = upperEstimationLimit;
47      Initialize();
48    }
49
50    [StorableConstructor]
51    private DataAnalysisSolution(bool deserializing) : base(deserializing) { }
52    [StorableHook(HookType.AfterDeserialization)]
53    private void Initialize() {
54      if (problemData != null)
55        RegisterProblemDataEvents();
56    }
57
58    [Storable]
59    private DataAnalysisProblemData problemData;
60    public DataAnalysisProblemData ProblemData {
61      get { return problemData; }
62      set {
63        if (problemData != value) {
64          if (value == null) throw new ArgumentNullException();
65          if (model != null && problemData != null && !problemData.InputVariables.Select(c => c.Value).SequenceEqual(
66            value.InputVariables.Select(c => c.Value)))
67            throw new ArgumentException("Could not set new problem data with different structure");
68
69          if (problemData != null) DeregisterProblemDataEvents();
70          problemData = value;
71          RegisterProblemDataEvents();
72          OnProblemDataChanged();
73          RecalculateEstimatedValues();
74        }
75      }
76    }
77
78    [Storable]
79    private IDataAnalysisModel model;
80    public IDataAnalysisModel Model {
81      get { return model; }
82      set {
83        if (model != value) {
84          if (value == null) throw new ArgumentNullException();
85          model = value;
86          OnModelChanged();
87          RecalculateEstimatedValues();
88        }
89      }
90    }
91
92    [Storable]
93    private double lowerEstimationLimit;
94    public double LowerEstimationLimit {
95      get { return lowerEstimationLimit; }
96      set {
97        if (lowerEstimationLimit != value) {
98          lowerEstimationLimit = value;
99          RecalculateEstimatedValues();
100        }
101      }
102    }
103
104    [Storable]
105    private double upperEstimationLimit;
106    public double UpperEstimationLimit {
107      get { return upperEstimationLimit; }
108      set {
109        if (upperEstimationLimit != value) {
110          upperEstimationLimit = value;
111          RecalculateEstimatedValues();
112        }
113      }
114    }
115
116    public abstract IEnumerable<double> EstimatedValues { get; }
117    public abstract IEnumerable<double> EstimatedTrainingValues { get; }
118    public abstract IEnumerable<double> EstimatedTestValues { get; }
119    protected abstract void RecalculateEstimatedValues();
120
121    #region Events
122    protected virtual void RegisterProblemDataEvents() {
123      ProblemData.ProblemDataChanged += new EventHandler(ProblemData_Changed);
124    }
125    protected virtual void DeregisterProblemDataEvents() {
126      ProblemData.ProblemDataChanged += new EventHandler(ProblemData_Changed);
127    }
128    private void ProblemData_Changed(object sender, EventArgs e) {
129      OnProblemDataChanged();
130    }
131
132    public event EventHandler ProblemDataChanged;
133    protected virtual void OnProblemDataChanged() {
134      var listeners = ProblemDataChanged;
135      if (listeners != null)
136        listeners(this, EventArgs.Empty);
137    }
138
139    public event EventHandler ModelChanged;
140    protected virtual void OnModelChanged() {
141      EventHandler handler = ModelChanged;
142      if (handler != null)
143        handler(this, EventArgs.Empty);
144    }
145
146    public event EventHandler EstimatedValuesChanged;
147    protected virtual void OnEstimatedValuesChanged() {
148      var listeners = EstimatedValuesChanged;
149      if (listeners != null)
150        listeners(this, EventArgs.Empty);
151    }
152    #endregion
153
154    public override IDeepCloneable Clone(Cloner cloner) {
155      DataAnalysisSolution clone = (DataAnalysisSolution)base.Clone(cloner);
156      clone.problemData = (DataAnalysisProblemData)cloner.Clone(problemData);
157      clone.model = (IDataAnalysisModel)cloner.Clone(model);
158      clone.lowerEstimationLimit = lowerEstimationLimit;
159      clone.upperEstimationLimit = upperEstimationLimit;
160      clone.Initialize();
161
162      return clone;
163    }
164  }
165}
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