source: trunk/yat/statistics/Smoother.h @ 1310

Last change on this file since 1310 was 1310, checked in by Peter, 13 years ago

closes #359

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  • Property svn:keywords set to Id
File size: 2.6 KB
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1#ifndef _theplu_yat_statistics_smoother_
2#define _theplu_yat_statistics_smoother_
3
4// $Id: Smoother.h 1310 2008-05-15 19:12:17Z peter $
5
6/*
7  Copyright (C) 2008 Peter Johansson
8
9  This file is part of the yat library, http://trac.thep.lu.se/yat
10
11  The yat library is free software; you can redistribute it and/or
12  modify it under the terms of the GNU General Public License as
13  published by the Free Software Foundation; either version 2 of the
14  License, or (at your option) any later version.
15
16  The yat library is distributed in the hope that it will be useful,
17  but WITHOUT ANY WARRANTY; without even the implied warranty of
18  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
19  General Public License for more details.
20
21  You should have received a copy of the GNU General Public License
22  along with this program; if not, write to the Free Software
23  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
24  02111-1307, USA.
25*/
26
27
28#include "yat/utility/iterator_traits.h"
29
30#include <vector>
31
32namespace theplu {
33namespace yat {
34  namespace regression { 
35    class Kernel; 
36  }
37namespace statistics {
38
39  /**
40     @brief Estimating a distribution in a smooth fashion
41  */
42  class Smoother
43  {
44  public:
45    /**
46       Constructor taking vector describing for which values
47       distribution should be estimated.
48
49       \note if \a values are not sorted the behavior is undefined
50     */
51    Smoother(const regression::Kernel&, double width, 
52             const std::vector<double>& values);
53
54    /**
55       Constructor creating observation points equally distributed
56       between \a xmin and \a xmax.
57
58       \param kernel doing the smoothing
59       \param width
60       \param xmin smallest observation point
61       \param xmax largest observation point
62       \param n number of observation points
63     */
64    Smoother(const regression::Kernel& kernel, double width, 
65             double xmin, double xmax, size_t n);
66
67    /**
68       \brief Add a data point.
69    */
70    void add(double x, double weight=1.0);
71
72    /**
73     */
74    const std::vector<double>& density(void) const;
75
76    /**
77     */
78    void reset(void);
79
80    /**
81     */
82    const std::vector<double>& value(void) const;
83
84  private:
85    std::vector<double> density_;
86    const regression::Kernel& kernel_;
87    double width_;
88    std::vector<double> x_;
89  };
90
91  /**
92     Add a range [first, last) of values to Smoother.
93   */
94  template<typename ForwardIterator>
95  void add(Smoother& h, 
96           ForwardIterator first, ForwardIterator last)
97  {
98    while (first!=last) {
99      h.add(utility::iterator_traits<ForwardIterator>().data(),
100            utility::iterator_traits<ForwardIterator>().weight());
101      ++first;
102    }
103  }
104
105  /**
106     The Smoother output operator
107  */
108  std::ostream& operator<<(std::ostream& s,const Smoother&);
109
110}}} // of namespace statistics, yat, and theplu
111
112#endif
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