source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineCalculators/DependencyCalculator/SpearmansRankCorrelationCoefficientCalculator.cs @ 13938

Last change on this file since 13938 was 13938, checked in by mkommend, 5 years ago

#2619:

  • Refactored and separated the different feature correlation calculations.
  • Added a checkbox to ignore missing values in the calculation.
File size: 2.3 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  public class SpearmansRankCorrelationCoefficientCalculator : IDependencyCalculator {
28
29    public double Maximum { get { return 1.0; } }
30
31    public double Minimum { get { return -1.0; } }
32
33    public string Name { get { return "Spearmans Rank"; } }
34
35    public double Calculate(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
36      return CalculateSpearmansRank(originalValues, estimatedValues, out errorState);
37    }
38    public double Calculate(IEnumerable<Tuple<double, double>> values, out OnlineCalculatorError errorState) {
39      return CalculateSpearmansRank(values.Select(v => v.Item1), values.Select(v => v.Item2), out errorState);
40    }
41
42    public static double CalculateSpearmansRank(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
43      double rs = double.NaN;
44      try {
45        var original = originalValues.ToArray();
46        var estimated = estimatedValues.ToArray();
47        rs = alglib.basestat.spearmancorr2(original, estimated, original.Length);
48        errorState = OnlineCalculatorError.None;
49      }
50      catch (alglib.alglibexception) {
51        errorState = OnlineCalculatorError.InvalidValueAdded;
52      }
53
54      return rs;
55    }
56
57
58  }
59}
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