1 | #ifndef _theplu_yat_statistics_smoother_ |
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2 | #define _theplu_yat_statistics_smoother_ |
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3 | |
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4 | // $Id: Smoother.h 1886 2009-03-31 17:02:39Z peter $ |
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5 | |
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6 | /* |
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7 | Copyright (C) 2008 Jari Häkkinen, Peter Johansson |
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8 | Copyright (C) 2009 Peter Johansson |
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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 3 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 yat. If not, see <http://www.gnu.org/licenses/>. |
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24 | */ |
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25 | |
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26 | |
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27 | #include "yat/utility/iterator_traits.h" |
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28 | |
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29 | #include <vector> |
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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 regression { |
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34 | class Kernel; |
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35 | } |
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36 | namespace statistics { |
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37 | |
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38 | /** |
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39 | @brief Estimating a distribution in a smooth fashion |
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40 | |
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41 | \since New in yat 0.5 |
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42 | */ |
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43 | class Smoother |
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44 | { |
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45 | public: |
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46 | /** |
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47 | Constructor taking vector describing for which values |
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48 | distribution should be estimated. |
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49 | |
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50 | \note if \a values are not sorted the behavior is undefined |
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51 | */ |
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52 | Smoother(const regression::Kernel&, double width, |
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53 | const std::vector<double>& values); |
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54 | |
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55 | /** |
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56 | Constructor creating observation points equally distributed |
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57 | between \a xmin and \a xmax. |
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58 | |
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59 | \param kernel doing the smoothing |
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60 | \param width |
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61 | \param xmin smallest observation point |
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62 | \param xmax largest observation point |
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63 | \param n number of observation points |
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64 | */ |
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65 | Smoother(const regression::Kernel& kernel, double width, |
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66 | double xmin, double xmax, size_t n); |
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67 | |
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68 | /** |
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69 | \brief Add a data point. |
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70 | */ |
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71 | void add(double x, double weight=1.0); |
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72 | |
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73 | /** |
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74 | \brief estimated values |
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75 | */ |
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76 | const std::vector<double>& density(void) const; |
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77 | |
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78 | /** |
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79 | \brief reset density to zero |
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80 | */ |
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81 | void reset(void); |
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82 | |
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83 | /** |
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84 | \brief values in which distribution is estimated |
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85 | */ |
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86 | const std::vector<double>& value(void) const; |
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87 | |
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88 | private: |
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89 | std::vector<double> density_; |
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90 | const regression::Kernel& kernel_; |
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91 | double width_; |
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92 | std::vector<double> x_; |
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93 | }; |
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94 | |
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95 | /** |
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96 | Add a range [first, last) of values to Smoother. |
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97 | |
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98 | \relates Smoother |
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99 | */ |
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100 | template<typename ForwardIterator> |
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101 | void add(Smoother& h, |
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102 | ForwardIterator first, ForwardIterator last) |
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103 | { |
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104 | while (first!=last) { |
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105 | h.add(utility::iterator_traits<ForwardIterator>().data(), |
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106 | utility::iterator_traits<ForwardIterator>().weight()); |
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107 | ++first; |
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108 | } |
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109 | } |
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110 | |
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111 | /** |
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112 | The Smoother output operator |
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113 | |
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114 | \relates Smoother |
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115 | */ |
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116 | std::ostream& operator<<(std::ostream& s,const Smoother&); |
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117 | |
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118 | }}} // of namespace statistics, yat, and theplu |
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119 | |
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120 | #endif |
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