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source: branches/DataAnalysis/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/SimpleVarianceAccountedForEvaluator.cs @ 4233

Last change on this file since 4233 was 4068, checked in by swagner, 14 years ago

Sorted usings and removed unused usings in entire solution (#1094)

File size: 3.4 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;
29
30namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
31  /// <summary>
32  /// The Variance Accounted For (VAF) function calculates is computed as
33  /// VAF(y,y') =  1 - var(y-y')/var(y)
34  /// where y' denotes the predicted / modelled values for y and var(x) the variance of a signal x.
35  /// </summary>
36  public class SimpleVarianceAccountedForEvaluator : SimpleEvaluator {
37
38    public ILookupParameter<DoubleValue> VarianceAccountedForParameter {
39      get { return (ILookupParameter<DoubleValue>)Parameters["VarianceAccountedFor"]; }
40    }
41
42    public SimpleVarianceAccountedForEvaluator() {
43      Parameters.Add(new LookupParameter<DoubleValue>("VarianceAccountedFor", "The variance of the original values accounted for by the estimated values (VAF(y,y') = 1 - var(y-y') / var(y) )."));
44    }
45
46    protected override void Apply(DoubleMatrix values) {
47      var original = from i in Enumerable.Range(0, values.Rows)
48                     select values[i, ORIGINAL_INDEX];
49      var estimated = from i in Enumerable.Range(0, values.Rows)
50                      select values[i, ESTIMATION_INDEX];
51      VarianceAccountedForParameter.ActualValue = new DoubleValue(Calculate(original, estimated));
52    }
53
54    public static double Calculate(IEnumerable<double> original, IEnumerable<double> estimated) {
55      var originalEnumerator = original.GetEnumerator();
56      var estimatedEnumerator = estimated.GetEnumerator();
57      var errors = new List<double>();
58      while (originalEnumerator.MoveNext() & estimatedEnumerator.MoveNext()) {
59        double e = estimatedEnumerator.Current;
60        double o = originalEnumerator.Current;
61        if (!double.IsNaN(e) && !double.IsInfinity(e) &&
62          !double.IsNaN(o) && !double.IsInfinity(o)) {
63          errors.Add(o - e);
64        }
65      }
66      if (estimatedEnumerator.MoveNext() || originalEnumerator.MoveNext()) {
67        throw new ArgumentException("Number of elements in original and estimated enumeration doesn't match.");
68      }
69
70      double errorsVariance = errors.Variance();
71      double originalsVariance = original.Variance();
72      if (originalsVariance.IsAlmost(0.0))
73        if (errorsVariance.IsAlmost(0.0)) {
74          return 1.0;
75        } else {
76          return double.MaxValue;
77        } else {
78        return 1.0 - errorsVariance / originalsVariance;
79      }
80    }
81  }
82}
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