1 | // $Id: Smoother.cc 1797 2009-02-12 18:07:10Z peter $ |
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2 | |
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3 | /* |
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4 | Copyright (C) 2008 Jari Häkkinen, Peter Johansson |
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5 | |
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6 | This file is part of the yat library, http://dev.thep.lu.se/yat |
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7 | |
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8 | The yat library is free software; you can redistribute it and/or |
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9 | modify it under the terms of the GNU General Public License as |
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10 | published by the Free Software Foundation; either version 3 of the |
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11 | License, or (at your option) any later version. |
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12 | |
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13 | The yat library is distributed in the hope that it will be useful, |
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14 | but WITHOUT ANY WARRANTY; without even the implied warranty of |
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15 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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16 | General Public License for more details. |
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17 | |
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18 | You should have received a copy of the GNU General Public License |
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19 | along with yat. If not, see <http://www.gnu.org/licenses/>. |
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20 | */ |
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21 | |
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22 | #include "Smoother.h" |
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23 | #include "yat/regression/Kernel.h" |
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24 | |
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25 | #include <algorithm> |
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26 | #include <cassert> |
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27 | #include <ostream> |
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28 | |
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29 | namespace theplu { |
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30 | namespace yat { |
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31 | namespace statistics { |
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32 | |
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33 | Smoother::Smoother(const regression::Kernel& kernel, double width, |
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34 | const std::vector<double>& values) |
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35 | : kernel_(kernel), width_(width), x_(values) |
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36 | { |
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37 | density_.resize(values.size(), 0.0); |
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38 | assert(density_.size()==x_.size()); |
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39 | } |
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40 | |
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41 | Smoother::Smoother(const regression::Kernel& kernel, double width, |
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42 | double min, double max, size_t n) |
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43 | : density_(std::vector<double>(n)), kernel_(kernel), width_(width) |
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44 | { |
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45 | x_.reserve(n); |
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46 | double step_size = (max-min)/n; |
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47 | for (double x=min; x_.size()<n; x+=step_size) |
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48 | x_.push_back(x); |
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49 | assert(x_.back()==max); |
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50 | assert(density_.size()==x_.size()); |
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51 | } |
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52 | |
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53 | |
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54 | void Smoother::add(const double x, const double w) |
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55 | { |
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56 | if (w==0) |
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57 | return; |
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58 | // Peter, we should probably do something clever here to avoid x+=0 |
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59 | for (size_t i=0; i<x_.size(); ++i) |
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60 | density_[i] += w*kernel_( (x-x_[i])/width_); |
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61 | } |
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62 | |
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63 | |
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64 | const std::vector<double>& Smoother::density(void) const |
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65 | { |
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66 | return density_; |
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67 | } |
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68 | |
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69 | |
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70 | void Smoother::reset(void) |
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71 | { |
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72 | std::fill(density_.begin(), density_.end(), 0.0); |
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73 | } |
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74 | |
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75 | |
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76 | const std::vector<double>& Smoother::value(void) const |
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77 | { |
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78 | return x_; |
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79 | } |
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80 | |
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81 | |
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82 | std::ostream& operator<<(std::ostream& os,const Smoother& smoother) |
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83 | { |
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84 | os << "# column 1: x\n" |
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85 | << "# column 2: estimated density\n"; |
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86 | |
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87 | for (size_t i=0; i<smoother.value().size(); ++i) { |
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88 | os << smoother.value()[i] << "\t"; |
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89 | os << smoother.density()[i] << "\n"; |
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90 | } |
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91 | |
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92 | return os; |
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93 | } |
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94 | |
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95 | }}} // of namespace statistics, yat, and theplu |
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