1 | #ifndef theplu_yat_statistics_pearson_distance_h |
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2 | #define theplu_yat_statistics_pearson_distance_h |
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3 | |
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4 | // $Id: PearsonDistance.h 1437 2008-08-25 17:55:00Z peter $ |
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5 | |
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6 | /* |
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7 | Copyright (C) 2007 Jari Häkkinen, Peter Johansson, Markus Ringnér |
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8 | Copyright (C) 2008 Peter Johansson, Markus Ringnér |
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9 | |
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10 | This file is part of the yat library, http://dev.thep.lu.se/yat |
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11 | |
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12 | The yat library is free software; you can redistribute it and/or |
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13 | modify it under the terms of the GNU General Public License as |
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14 | published by the Free Software Foundation; either version 2 of the |
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15 | License, or (at your option) any later version. |
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16 | |
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17 | The yat library is distributed in the hope that it will be useful, |
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18 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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19 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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20 | General Public License for more details. |
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21 | |
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22 | You should have received a copy of the GNU General Public License |
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23 | along with this program; if not, write to the Free Software |
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24 | Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA |
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25 | 02111-1307, USA. |
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26 | */ |
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27 | |
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28 | #include "averager_traits.h" |
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29 | #include "yat/utility/iterator_traits.h" |
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30 | |
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31 | namespace theplu { |
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32 | namespace yat { |
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33 | namespace statistics { |
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34 | |
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35 | /// |
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36 | /// @brief Calculates the %Pearson correlation distance between two points given by elements of ranges. |
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37 | /// |
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38 | /// This class is modelling the concept \ref concept_distance. |
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39 | /// |
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40 | struct PearsonDistance |
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41 | { |
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42 | /** |
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43 | \brief Calculates the %Pearson correlation distance between |
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44 | elements of two ranges. |
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45 | |
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46 | If elements of both ranges are unweighted the distance is |
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47 | calculated as \f$ 1-\mbox{C}(x,y) \f$, where \f$ x \f$ and \f$ |
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48 | y \f$ are the two points and C is the %Pearson correlation. |
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49 | |
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50 | If elements of one or both of ranges have weights the distance |
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51 | is calculated as \f$ 1-[\sum w_{x,i}w_{y,i}(x_i-y_i)^2/(\sum |
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52 | w_{x,i}w_{y,i}(x_i-m_x)^2\sum w_{x,i}w_{y,i}(y_i-m_y)^2)] \f$, |
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53 | where and \f$ w_x \f$ and \f$ w_y \f$ are weights for the |
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54 | elements of the first and the second range, respectively, and |
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55 | \f$ m_x=\sum w_{x,i}w_{y,i}x_i/\sum w_{x,i}w_{y,i} \f$ and |
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56 | correspondingly for \f$ m_y \f$. If the elements of one of the |
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57 | two ranges are unweighted, the weights for these elements are |
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58 | set to unity. |
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59 | */ |
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60 | template <typename Iter1, typename Iter2> |
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61 | double operator() |
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62 | (Iter1 beg1,Iter1 end1, Iter2 beg2) const |
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63 | { |
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64 | typename averager_pair<Iter1, Iter2>::type ap; |
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65 | add(ap,beg1,end1,beg2); |
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66 | return 1-ap.correlation(); |
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67 | } |
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68 | }; |
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69 | |
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70 | }}} // of namespace statistics, yat, and theplu |
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71 | |
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72 | #endif |
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