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source: trunk/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/ConstantModel.cs @ 16243

Last change on this file since 16243 was 16243, checked in by mkommend, 5 years ago

#2955: Added IsProblemDataCompatible and IsDatasetCompatible to all DataAnalysisModels.

File size: 5.2 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
29
30namespace HeuristicLab.Problems.DataAnalysis {
31  [StorableClass]
32  [Item("Constant Model", "A model that always returns the same constant value regardless of the presented input data.")]
33  public class ConstantModel : RegressionModel, IClassificationModel, ITimeSeriesPrognosisModel, IStringConvertibleValue {
34    public override IEnumerable<string> VariablesUsedForPrediction { get { return Enumerable.Empty<string>(); } }
35
36
37    [Storable]
38    private readonly double constant;
39    public double Constant {
40      get { return constant; }
41      // setter not implemented because manipulation of the constant is not allowed
42    }
43
44    [StorableConstructor]
45    protected ConstantModel(bool deserializing) : base(deserializing) { }
46    protected ConstantModel(ConstantModel original, Cloner cloner)
47      : base(original, cloner) {
48      this.constant = original.constant;
49    }
50
51    public override IDeepCloneable Clone(Cloner cloner) { return new ConstantModel(this, cloner); }
52
53    public ConstantModel(double constant, string targetVariable)
54      : base(targetVariable) {
55      this.name = ItemName;
56      this.description = ItemDescription;
57      this.constant = constant;
58      this.ReadOnly = true; // changing a constant regression model is not supported
59    }
60
61    public override IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
62      return rows.Select(row => Constant);
63    }
64    public IEnumerable<double> GetEstimatedClassValues(IDataset dataset, IEnumerable<int> rows) {
65      return GetEstimatedValues(dataset, rows);
66    }
67    public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
68      return rows.Select(_ => horizons.Select(__ => Constant));
69    }
70
71    public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
72      return new ConstantRegressionSolution(this, new RegressionProblemData(problemData));
73    }
74    public IClassificationSolution CreateClassificationSolution(IClassificationProblemData problemData) {
75      return new ConstantClassificationSolution(this, new ClassificationProblemData(problemData));
76    }
77    public ITimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
78      return new TimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
79    }
80
81    public override string ToString() {
82      return string.Format("Constant: {0}", GetValue());
83    }
84
85    public virtual bool IsProblemDataCompatible(IClassificationProblemData problemData, out string errorMessage) {
86      return ClassificationModel.IsProblemDataCompatible(this, problemData, out errorMessage);
87    }
88
89    public override bool IsProblemDataCompatible(IDataAnalysisProblemData problemData, out string errorMessage) {
90      if (problemData == null) throw new ArgumentNullException("problemData", "The provided problemData is null.");
91
92      var regressionProblemData = problemData as IRegressionProblemData;
93      if (regressionProblemData != null)
94        return IsProblemDataCompatible(regressionProblemData, out errorMessage);
95
96      var classificationProblemData = problemData as IClassificationProblemData;
97      if (classificationProblemData != null)
98        return IsProblemDataCompatible(classificationProblemData, out errorMessage);
99
100      throw new ArgumentException("The problem data is not a regression nor a classification problem data. Instead a " + problemData.GetType().GetPrettyName() + " was provided.", "problemData");
101    }
102
103    #region IStringConvertibleValue
104    public bool ReadOnly { get; private set; }
105    public bool Validate(string value, out string errorMessage) {
106      throw new NotSupportedException(); // changing a constant regression model is not supported
107    }
108
109    public string GetValue() {
110      return string.Format("{0:E4}", constant);
111    }
112
113    public bool SetValue(string value) {
114      throw new NotSupportedException(); // changing a constant regression model is not supported
115    }
116
117#pragma warning disable 0067
118    public event EventHandler ValueChanged;
119#pragma warning restore 0067
120    #endregion
121
122  }
123}
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