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source: branches/2988_ModelsOfModels2/HeuristicLab.Algorithms.EMM/EMMMapTreeModel.cs @ 16722

Last change on this file since 16722 was 16722, checked in by msemenki, 5 years ago

#2988: Add first version of GP for Evolvment models of models.

File size: 4.1 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2019 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 HEAL.Attic;
23using HeuristicLab.Common;
24using HeuristicLab.Core;
25using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
26using HeuristicLab.Problems.DataAnalysis.Symbolic;
27using System.Collections.Generic;
28using System.Linq;
29
30namespace HeuristicLab.Algorithms.EvolvmentModelsOfModels {
31  [StorableType("A9AE93F0-E589-44D0-AD34-0E3AA358D669")]
32  [Item("TreeModelMap", "A map of models of models of models")]
33  public class EMMMapTreeModel : EMMMapBase<ISymbolicExpressionTree> {
34    #region conctructors
35    [StorableConstructor]
36    protected EMMMapTreeModel(StorableConstructorFlag _) : base(_) { }
37    public EMMMapTreeModel() : this(1) { }
38    public EMMMapTreeModel(int k) {
39      K = k;
40      ModelSet = new List<ISymbolicExpressionTree>();
41      ClusterNumber = new List<int>();
42      Map = new List<List<int>>();
43    }
44    public EMMMapTreeModel(EMMMapTreeModel original, Cloner cloner) {
45      //original.ModelSet.ForEach(x => ModelSet.Add((ISymbolicExpressionTree)x.Clone(cloner)));
46      //original.ClusterNumber.ForEach(x => ClusterNumber.Add(x));
47      //original.Map.ForEach(x => Map.Add(x));
48      if (original.ModelSet != null) {
49        ModelSet = original.ModelSet.Select(cloner.Clone).ToList();
50      }
51      if (original.ClusterNumber != null) {
52        ClusterNumber = original.ClusterNumber.ToList();
53      }
54      if (original.Map != null) {
55        Map = original.Map.Select(x => x.ToList()).ToList();
56      }
57      K = original.K;
58    }
59    public EMMMapTreeModel(IRandom random, IEnumerable<ISymbolicExpressionTree> trees, int k) : this(k) {
60      ModelSet = trees.ToList();
61      CalculateDistances();
62      CreateMap(random, k);
63    }
64    public override IDeepCloneable Clone(Cloner cloner) {
65      return new EMMMapTreeModel(this, cloner);
66    }
67    #endregion
68    #region MapTransformation
69    override protected void CalculateDistances() {
70      Distances = SymbolicExpressionTreeHash.ComputeSimilarityMatrix(ModelSet, simplify: false, strict: true);
71      for (int i = 0; i < ModelSet.Count - 1; i++) {
72        for (int j = i + 1; j < ModelSet.Count; j++) {
73          Distances[j, i] = Distances[i, j] = 1 - Distances[i, j];
74        }
75      }
76    }
77    override public void CreateMap(IRandom random, int k) {
78      K = k;
79      //Clusterization
80      EMModelsClusterizationAlgorithm clusteringAlgorithm = new EMModelsClusterizationAlgorithm(K);
81      K = clusteringAlgorithm.Apply(random, Distances, ClusterNumber);
82      // Cheking a Map size
83      if (Map != null) Map.Clear();
84      else Map = new List<List<int>>();
85      if (Map.Count != K) {
86        if (Map.Count != 0) {
87          Map.Clear();
88        }
89        for (int i = 0; i < K; i++) {
90          Map.Add(new List<int>());
91        }
92      }
93      // Map fulfilment
94      for (int i = 0; i < ModelSet.Count; i++) {
95        Map[ClusterNumber[i]].Add(i);
96      }
97    }
98    #endregion
99    #region Dialog with surroudings
100    override public ISymbolicExpressionTree NewModelForInizializtion(IRandom random, out int cluster, out int treeNumber) {
101      treeNumber = random.Next(ModelSet.Count);
102      cluster = ClusterNumber[treeNumber];
103      return (ISymbolicExpressionTree)ModelSet[treeNumber].Clone();
104    }
105
106    #endregion
107  }
108}
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