source: trunk/yat/utility/WeNNI.cc @ 759

Last change on this file since 759 was 759, checked in by Jari Häkkinen, 16 years ago

Fixes #171 and addresses #2. A few more GSL_error exceptions. Removed Jari comments.

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 2.6 KB
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1// $Id: WeNNI.cc 759 2007-02-19 19:41:25Z jari $
2
3/*
4  Copyright (C) 2004 Jari Häkkinen
5  Copyright (C) 2005 Jari Häkkinen, Peter Johansson
6  Copyright (C) 2006 Jari Häkkinen
7
8  This file is part of the yat library, http://lev.thep.lu.se/trac/yat
9
10  The yat library is free software; you can redistribute it and/or
11  modify it under the terms of the GNU General Public License as
12  published by the Free Software Foundation; either version 2 of the
13  License, or (at your option) any later version.
14
15  The yat library is distributed in the hope that it will be useful,
16  but WITHOUT ANY WARRANTY; without even the implied warranty of
17  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
18  General Public License for more details.
19
20  You should have received a copy of the GNU General Public License
21  along with this program; if not, write to the Free Software
22  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
23  02111-1307, USA.
24*/
25
26#include "WeNNI.h"
27#include "matrix.h"
28#include "stl_utility.h"
29
30#include <algorithm>
31#include <cmath>
32#include <fstream>
33
34namespace theplu {
35namespace yat {
36namespace utility {
37
38
39  WeNNI::WeNNI(const utility::matrix& matrix,const utility::matrix& flag,
40               const u_int neighbours)
41    : NNI(matrix,flag,neighbours), imputed_data_raw_(matrix)
42  {
43    //estimate();
44  }
45
46
47
48  // \hat{x_{ij}}=\frac{ \sum_{k=1,N} \frac{w_{kj}*x_{kj}}{d_{ki}} }
49  //                   { \sum_{k=1,N} \frac{w_{kj}       }{d_{ki}} }
50  // where N is defined in the paper cited in the NNI class definition
51  // documentation.
52  u_int WeNNI::estimate(void)
53  {
54    for (unsigned int i=0; i<data_.rows(); i++) {
55      std::vector<std::pair<u_int,double> > distance=calculate_distances(i);
56      std::sort(distance.begin(),distance.end(),
57                pair_value_compare<u_int,double>());
58      bool row_imputed=true;
59      for (unsigned int j=0; j<data_.columns(); j++) {
60        std::vector<u_int> knn=nearest_neighbours(j,distance);
61        double new_value=0.0;
62        double norm=0.0;
63        for (std::vector<u_int>::const_iterator k=knn.begin(); k!=knn.end();
64             ++k) {
65          // Avoid division with zero (perfect match vectors)
66          double d=(distance[*k].second ? distance[*k].second : 1e-10);
67          new_value+=(weight_(distance[*k].first,j) *
68                      data_(distance[*k].first,j)/d);
69          norm+=weight_(distance[*k].first,j)/d;
70        }
71        // No impute if no contributions from neighbours.
72        if (norm){
73          imputed_data_raw_(i,j) = new_value/norm;
74          imputed_data_(i,j)=
75            weight_(i,j)*data_(i,j) + (1-weight_(i,j))* imputed_data_raw_(i,j);
76        }
77        else
78          row_imputed=false;
79      }
80      if (!row_imputed)
81        not_imputed_.push_back(i);
82    }
83    return not_imputed_.size();
84  }
85
86
87}}} // of namespace utility, yat, and theplu
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