1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 |
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26 | namespace HeuristicLab.Problems.DataAnalysis {
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27 | public class SpearmansRankCorrelationCoefficientCalculator : IDependencyCalculator {
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28 |
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29 | public double Maximum { get { return 1.0; } }
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30 |
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31 | public double Minimum { get { return -1.0; } }
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32 |
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33 | public string Name { get { return "Spearmans Rank"; } }
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34 |
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35 | public double Calculate(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
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36 | return CalculateSpearmansRank(originalValues, estimatedValues, out errorState);
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37 | }
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38 | public double Calculate(IEnumerable<Tuple<double, double>> values, out OnlineCalculatorError errorState) {
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39 | return CalculateSpearmansRank(values.Select(v => v.Item1), values.Select(v => v.Item2), out errorState);
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40 | }
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41 |
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42 | public static double CalculateSpearmansRank(IEnumerable<double> originalValues, IEnumerable<double> estimatedValues, out OnlineCalculatorError errorState) {
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43 | double rs = double.NaN;
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44 | try {
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45 | var original = originalValues.ToArray();
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46 | var estimated = estimatedValues.ToArray();
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47 | rs = alglib.basestat.spearmancorr2(original, estimated, original.Length);
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48 | errorState = OnlineCalculatorError.None;
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49 | }
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50 | catch (alglib.alglibexception) {
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51 | errorState = OnlineCalculatorError.InvalidValueAdded;
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52 | }
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53 |
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54 | return rs;
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55 | }
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56 |
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57 |
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58 | }
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59 | }
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