source: trunk/yat/statistics/SNR.h @ 748

Last change on this file since 748 was 748, checked in by Peter, 16 years ago

documentation for SNR improved. fixes #123

  • Property svn:eol-style set to native
  • Property svn:keywords set to Id
File size: 2.7 KB
Line 
1#ifndef _theplu_yat_statistics_snr
2#define _theplu_yat_statistics_snr
3
4// $Id: SNR.h 748 2007-02-11 17:48:22Z peter $
5
6/*
7  Copyright (C) The authors contributing to this file.
8
9  This file is part of the yat library, http://lev.thep.lu.se/trac/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#include "Score.h"
28
29#include <gsl/gsl_cdf.h>
30
31namespace theplu {
32namespace yat {
33  namespace utility {
34    class vector;
35  }
36  namespace classifier {
37    class DataLookWeighted1D;
38  }
39namespace statistics { 
40
41  /**
42     @brief Class for score based on signal-to-noise ratio (SNR). 
43     
44     Also
45     sometimes referred to as Golub score. The score is the ratio
46     between difference in mean and the sum of standard deviations
47     for two groups:  \f$ \frac{ m_x-m_y}{ s_x + s_y} \f$ where \f$
48     s \f$ is standard deviation.
49  */
50  class SNR : public Score
51  {
52 
53  public:
54    ///
55    /// @brief Default Constructor.
56    ///
57    SNR(bool absolute=true);
58
59    /**
60       SNR is defined as \f$ \frac{m_x-m_y}{s_x+s_y} \f$ where \f$ m
61       \f$ and \f$ s \f$ are mean and standard deviation,
62       respectively. @see Averager
63
64       @return SNR score. If absolute=true absolute value of SNR is
65       returned
66    */
67    double score(const classifier::Target& target, 
68                 const utility::vector& value); 
69
70    /**
71       SNR is defined as \f$ \frac{m_x-m_y}{s_x+s_y} \f$ where \f$ m
72       \f$ and \f$ s \f$ are weighted versions of mean and standard
73       deviation, respectively. @see AveragerWeighted
74
75       @return SNR score. If absolute=true absolute value of SNR is
76       returned
77    */
78    double score(const classifier::Target& target, 
79                 const classifier::DataLookupWeighted1D& value);         
80
81    /**
82       SNR is defined as \f$ \frac{m_x-m_y}{s_x+s_y} \f$ where \f$ m
83       \f$ and \f$ s \f$ are weighted versions of mean and standard
84       deviation, respectively. @see AveragerWeighted
85
86       @return SNR score. If absolute=true absolute value of SNR is
87       returned
88    */
89    double score(const classifier::Target& target, 
90                 const utility::vector& value, 
91                 const utility::vector& weight);         
92  private:
93    double score_;
94  };
95
96}}} // of namespace statistics, yat, and theplu
97
98#endif
Note: See TracBrowser for help on using the repository browser.