source: trunk/yat/statistics/Smoother.h @ 1486

Last change on this file since 1486 was 1486, checked in by Jari Häkkinen, 13 years ago

Addresses #436.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.8 KB
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1#ifndef _theplu_yat_statistics_smoother_
2#define _theplu_yat_statistics_smoother_
3
4// $Id: Smoother.h 1486 2008-09-09 21:17:19Z jari $
5
6/*
7  Copyright (C) 2008 Peter Johansson
8
9  This file is part of the yat library, http://dev.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 3 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     \since New in yat 0.5
43  */
44  class Smoother
45  {
46  public:
47    /**
48       Constructor taking vector describing for which values
49       distribution should be estimated.
50
51       \note if \a values are not sorted the behavior is undefined
52     */
53    Smoother(const regression::Kernel&, double width, 
54             const std::vector<double>& values);
55
56    /**
57       Constructor creating observation points equally distributed
58       between \a xmin and \a xmax.
59
60       \param kernel doing the smoothing
61       \param width
62       \param xmin smallest observation point
63       \param xmax largest observation point
64       \param n number of observation points
65     */
66    Smoother(const regression::Kernel& kernel, double width, 
67             double xmin, double xmax, size_t n);
68
69    /**
70       \brief Add a data point.
71    */
72    void add(double x, double weight=1.0);
73
74    /**
75       \brief estimated values
76     */
77    const std::vector<double>& density(void) const;
78
79    /**
80       \brief reset density to zero
81     */
82    void reset(void);
83
84    /**
85       \brief values in which distribution is estimated
86     */
87    const std::vector<double>& value(void) const;
88
89  private:
90    std::vector<double> density_;
91    const regression::Kernel& kernel_;
92    double width_;
93    std::vector<double> x_;
94  };
95
96  /**
97     Add a range [first, last) of values to Smoother.
98   */
99  template<typename ForwardIterator>
100  void add(Smoother& h, 
101           ForwardIterator first, ForwardIterator last)
102  {
103    while (first!=last) {
104      h.add(utility::iterator_traits<ForwardIterator>().data(),
105            utility::iterator_traits<ForwardIterator>().weight());
106      ++first;
107    }
108  }
109
110  /**
111     The Smoother output operator
112  */
113  std::ostream& operator<<(std::ostream& s,const Smoother&);
114
115}}} // of namespace statistics, yat, and theplu
116
117#endif
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