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source: trunk/sources/HeuristicLab.GP.StructureIdentification/3.3/Predictor.cs @ 2600

Last change on this file since 2600 was 2567, checked in by gkronber, 15 years ago

Implemented #818 (Additional model meta data field that stores the number of input variables of the model).

File size: 4.4 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2008 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.Collections.Generic;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.GP.Interfaces;
26using HeuristicLab.GP;
27using HeuristicLab.Modeling;
28using System;
29using System.Xml;
30using HeuristicLab.DataAnalysis;
31
32namespace HeuristicLab.GP.StructureIdentification {
33  public class Predictor : PredictorBase {
34    public Predictor() : base() { } // for persistence
35    public Predictor(ITreeEvaluator evaluator, IGeneticProgrammingModel tree, double lowerPredictionLimit, double upperPredictionLimit)
36      : base(lowerPredictionLimit, upperPredictionLimit) {
37      this.treeEvaluator = evaluator;
38      this.functionTree = tree;
39    }
40
41    private ITreeEvaluator treeEvaluator;
42    public ITreeEvaluator TreeEvaluator {
43      get { return (ITreeEvaluator)this.treeEvaluator.Clone(); }
44    }
45
46    private IGeneticProgrammingModel functionTree;
47    public IGeneticProgrammingModel FunctionTree {
48      get { return functionTree; }
49      set { this.functionTree = value; }
50    }
51
52    public override double[] Predict(Dataset input, int start, int end) {
53      treeEvaluator.UpperEvaluationLimit = UpperPredictionLimit;
54      treeEvaluator.LowerEvaluationLimit = LowerPredictionLimit;
55
56      if (start < 0 || end <= start) throw new ArgumentException("start must be larger than zero and strictly smaller than end");
57      if (end > input.Rows) throw new ArgumentOutOfRangeException("number of rows in input is smaller then end");
58      treeEvaluator.PrepareForEvaluation(input, functionTree.FunctionTree);
59      double[] result = new double[end - start];
60      for (int i = 0; i < result.Length; i++) {
61        try {
62          result[i] = treeEvaluator.Evaluate(i + start);
63        }
64        catch (ArgumentException) {
65          result[i] = double.NaN;
66        }
67      }
68      return result;
69    }
70
71    public override IEnumerable<string> GetInputVariables() {
72      HashSet<string> inputVariables = new HashSet<string>();
73      foreach (IFunctionTree ft in FunctionTreeIterator.IteratePrefix(functionTree.FunctionTree)) {
74        VariableFunctionTree varFunTree = ft as VariableFunctionTree;
75        if (varFunTree != null) {
76          inputVariables.Add(varFunTree.VariableName);
77        }
78      }
79      return inputVariables;
80    }
81
82    public override IView CreateView() {
83      return new PredictorView(this);
84    }
85
86    public override object Clone(IDictionary<Guid, object> clonedObjects) {
87      Predictor clone = (Predictor)base.Clone(clonedObjects);
88      clone.treeEvaluator = (ITreeEvaluator)Auxiliary.Clone(treeEvaluator, clonedObjects);
89      clone.functionTree = (IGeneticProgrammingModel)Auxiliary.Clone(functionTree, clonedObjects);
90      return clone;
91    }
92
93    public override System.Xml.XmlNode GetXmlNode(string name, System.Xml.XmlDocument document, IDictionary<Guid, IStorable> persistedObjects) {
94      XmlNode node = base.GetXmlNode(name, document, persistedObjects);
95      node.AppendChild(PersistenceManager.Persist("Evaluator", treeEvaluator, document, persistedObjects));
96      node.AppendChild(PersistenceManager.Persist("FunctionTree", functionTree, document, persistedObjects));
97      return node;
98    }
99
100    public override void Populate(System.Xml.XmlNode node, IDictionary<Guid, IStorable> restoredObjects) {
101      base.Populate(node, restoredObjects);
102      treeEvaluator = (ITreeEvaluator)PersistenceManager.Restore(node.SelectSingleNode("Evaluator"), restoredObjects);
103      functionTree = (IGeneticProgrammingModel)PersistenceManager.Restore(node.SelectSingleNode("FunctionTree"), restoredObjects);
104    }
105  }
106}
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