source: trunk/yat/statistics/Averager.h @ 937

Last change on this file since 937 was 937, checked in by Peter, 14 years ago

changing name of IteratorTraits? to iterator_traits

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 4.5 KB
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1#ifndef _theplu_yat_statistics_averager_
2#define _theplu_yat_statistics_averager_
3
4// $Id: Averager.h 937 2007-10-05 23:11:18Z peter $
5
6/*
7  Copyright (C) 2004 Jari Häkkinen, Peter Johansson
8  Copyright (C) 2005, 2006 Jari Häkkinen, Markus Ringnér, Peter Johansson
9  Copyright (C) 2007 Peter Johansson
10
11  This file is part of the yat library, http://trac.thep.lu.se/trac/yat
12
13  The yat library is free software; you can redistribute it and/or
14  modify it under the terms of the GNU General Public License as
15  published by the Free Software Foundation; either version 2 of the
16  License, or (at your option) any later version.
17
18  The yat library is distributed in the hope that it will be useful,
19  but WITHOUT ANY WARRANTY; without even the implied warranty of
20  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
21  General Public License for more details.
22
23  You should have received a copy of the GNU General Public License
24  along with this program; if not, write to the Free Software
25  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
26  02111-1307, USA.
27*/
28
29#include "yat/utility/iterator_traits.h"
30
31#include <cmath>
32#include <sys/types.h>
33
34namespace theplu{
35namespace yat{
36namespace statistics{
37
38  class ostream;
39
40  ///
41  /// @brief Class to calculate simple (first and second moments) averages.
42  ///
43  /// @see AveragerWeighted AveragerPair AveragerPairWeighted
44  ///
45  class Averager
46  {
47  public:
48
49    ///
50    /// Default constructor
51    ///
52    Averager(void);
53   
54    ///
55    /// Constructor taking sum of \a x, sum of squared x, \a xx, and
56    /// number of samples \a n.
57    ///
58    Averager(double x, double xx, u_long n);
59
60    ///
61    /// Copy constructor
62    ///
63    Averager(const Averager& a);
64
65    ///
66    /// Adding \a n (default=1) number of data point(s) with value \a d.
67    ///
68    void add(double d, u_long n=1);
69
70    /**
71       @brief Coeffient of variation
72
73       Coeffient of variation (cv) is defined as ratio between the
74       standard deviation and the mean: \f$ \frac{\sigma}{\mu} \f$.
75       
76       @return standard deviation divided by mean.
77    */
78    double cv(void) const;
79
80    ///
81    /// @return Mean of presented data, \f$ \frac{1}{n}\sum x_i \f$
82    ///
83    double mean(void) const;
84
85    ///
86    /// @return Number of data points
87    ///
88    u_long n(void) const;
89
90    ///
91    /// @brief Rescales the object
92    ///
93    /// \f$ \forall x_i \rightarrow a*x_i \f$,
94    /// \f$ \forall x_i^2 \rightarrow a^2*x_i^2 \f$
95    ///
96    void rescale(double a);
97
98    ///
99    /// @return Standard error, i.e. standard deviation of the mean
100    /// \f$ \sqrt{variance()/n} \f$
101    ///
102    double standard_error(void) const;
103
104    ///
105    /// @brief The standard deviation is defined as the square root of
106    /// the variance.
107    ///
108    /// @return The standard deviation, root of the variance().
109    ///
110    double std(void) const;
111
112    ///
113    /// @brief The standard deviation is defined as the square root of
114    /// the variance.
115    ///
116    /// @return Standard deviation around \a m, root of the variance(m).
117    ///
118    double std(double m) const;
119
120    ///
121    /// @return The sum of x
122    ///
123    double sum_x(void)  const;
124
125    ///
126    /// @return The sum of squares
127    ///
128    double sum_xx(void) const;
129
130    ///
131    /// @return \f$ \sum_i (x_i-m)^2 \f$
132    ///
133    double sum_xx_centered(void)  const;
134
135    ///
136    /// @brief The variance with know mean
137    ///
138    /// The variance is calculated as
139    /// \f$ \frac{1}{n}\sum (x_i-m)^2 \f$.
140    ///
141    /// @return Variance when the mean is known to be \a m.
142    ///
143    double variance(double m) const;
144
145    ///
146    /// @brief The estimated variance
147    ///
148    /// The variance is calculated as \f$ \frac{1}{N}\sum_i
149    /// (x_i-m)^2 \f$, where \f$ m \f$ is the mean.
150    ///
151    /// @return Estimation of variance
152    ///
153    double variance(void) const;
154
155    ///
156    /// The variance is calculated using the \f$ (n-1) \f$ correction,
157    /// which means it is the best unbiased estimator of the variance
158    /// \f$ \frac{1}{N-1}\sum_i (x_i-m)^2 \f$, where \f$ m \f$ is the
159    /// mean.
160    ///
161    /// @return unbiased estimation of variance
162    ///
163    double variance_unbiased(void) const;
164
165    ///
166    /// @brief Reset everything to zero
167    ///
168    void reset(void);
169
170    ///
171    /// @brief The assignment operator
172    ///
173    const Averager& operator=(const Averager&);
174
175    ///
176    /// Operator to add another Averager
177    ///
178    const Averager& operator+=(const Averager&);
179
180  private:
181    u_long  n_;
182    double  x_, xx_;
183  };
184 
185
186  /**
187     \brief adding a ranges of values to Averager \a a
188   */
189  template <typename Iter>
190  void add(Averager& a, Iter first, Iter last)
191  {
192    utility::check_iterator_is_unweighted(first);
193    for ( ; first != last; ++first)
194      a.add(*first);
195  }
196
197}}} // of namespace statistics, yat, and theplu
198
199#endif
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