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source: branches/DataAnalysis.PopulationDiversityAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleNMSEEvaluator.cs @ 13749

Last change on this file since 13749 was 4951, checked in by swinkler, 14 years ago

Branched DataAnalysis plugin into DataAnalysis.PopulationDiversity branch. (#1278)

File size: 3.1 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 System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30
31namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
32  public class SimpleNMSEEvaluator : SimpleEvaluator {
33
34    public ILookupParameter<DoubleValue> NormalizedMeanSquaredErrorParameter {
35      get { return (ILookupParameter<DoubleValue>)Parameters["NormalizedMeanSquaredError"]; }
36    }
37
38    [StorableConstructor]
39    protected SimpleNMSEEvaluator(bool deserializing) : base(deserializing) { }
40    protected SimpleNMSEEvaluator(SimpleNMSEEvaluator original, Cloner cloner)
41      : base(original, cloner) {
42    }
43    public override IDeepCloneable Clone(Cloner cloner) {
44      return new SimpleNMSEEvaluator(this, cloner);
45    }
46    public SimpleNMSEEvaluator() {
47      Parameters.Add(new LookupParameter<DoubleValue>("NormalizedMeanSquaredError", "The normalized mean squared error (divided by variance) of estimated values."));
48    }
49
50    protected override void Apply(DoubleMatrix values) {
51      var original = from i in Enumerable.Range(0, values.Rows)
52                     select values[i, ORIGINAL_INDEX];
53      var estimated = from i in Enumerable.Range(0, values.Rows)
54                      select values[i, ESTIMATION_INDEX];
55
56      NormalizedMeanSquaredErrorParameter.ActualValue = new DoubleValue(Calculate(original, estimated));
57    }
58
59    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
60      OnlineNormalizedMeanSquaredErrorEvaluator nmseEvaluator = new OnlineNormalizedMeanSquaredErrorEvaluator();
61      var originalEnumerator = original.GetEnumerator();
62      var estimatedEnumerator = estimated.GetEnumerator();
63      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
64        nmseEvaluator.Add(originalEnumerator.Current, estimatedEnumerator.Current);
65      }
66      if (originalEnumerator.MoveNext() || estimatedEnumerator.MoveNext()) {
67        throw new ArgumentException("Number of elements in original and estimated enumerations doesn't match.");
68      }
69      return nmseEvaluator.NormalizedMeanSquaredError;
70    }
71  }
72}
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