source: trunk/yat/utility/kNNI.cc @ 1271

Last change on this file since 1271 was 1271, checked in by Peter, 13 years ago

replaced u_int with unsigned int or size_t

  • Property svn:eol-style set to native
  • Property svn:keywords set to Author Date Id Revision
File size: 2.7 KB
Line 
1// $Id: kNNI.cc 1271 2008-04-09 16:11:07Z peter $
2
3/*
4  Copyright (C) 2004 Jari Häkkinen
5  Copyright (C) 2005 Peter Johansson
6  Copyright (C) 2006, 2007 Jari Häkkinen
7
8  This file is part of the yat library, http://trac.thep.lu.se/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 "kNNI.h"
27#include "stl_utility.h"
28
29#include <algorithm>
30#include <cmath>
31#include <fstream>
32#include <vector>
33
34namespace theplu {
35namespace yat {
36namespace utility {
37
38  kNNI::kNNI(const utility::Matrix& matrix,const utility::Matrix& flag,
39             const unsigned int neighbours)
40    : NNI(matrix,flag,neighbours)
41  {
42    for (unsigned int i=0; i<weight_.rows(); i++)
43      for (unsigned int j=0; j<weight_.columns(); j++)
44        if (!weight_(i,j)) {
45          mv_rows_.push_back(i);
46          break;
47        }
48    //estimate();
49  }
50
51
52
53  // \hat{x_{ij}}=\frac{ \sum_{k=1,N} \frac{x_{kj}}{d_{ki}} }
54  //                   { \sum_{k=1,N} \frac{1     }{d_{ki}} },
55  // where N is defined in the paper cited in the NNI class definition
56  // documentation.
57  unsigned int kNNI::estimate(void)
58  {
59    for (size_t i=0; i<mv_rows_.size(); i++) {
60      std::vector<std::pair<size_t,double> >
61        distance(calculate_distances(mv_rows_[i]));
62      std::sort(distance.begin(),distance.end(),
63                pair_value_compare<size_t,double>());
64      for (size_t j=0; j<data_.columns(); j++)
65        if (!weight_(mv_rows_[i],j)) {
66          std::vector<size_t> knn=nearest_neighbours(j,distance);
67          double new_value=0.0;
68          double norm=0.0;
69          for (std::vector<size_t>::const_iterator k=knn.begin(); k!=knn.end();
70               ++k) {
71            // Avoid division with zero (perfect match vectors)
72            double d=(distance[*k].second ? distance[*k].second : 1e-10);
73            new_value+=data_(distance[*k].first,j)/d;
74            norm+=1.0/d;
75          }
76          // No impute if no contributions from neighbours.
77          if (norm)
78            imputed_data_(mv_rows_[i],j)=new_value/norm;
79          else {
80            not_imputed_.push_back(i);
81            // if norm is zero for one column it is zero for all columns
82            // having zero weight
83            break;
84          }
85        }
86    }
87    return not_imputed_.size();
88  }
89
90
91}}} // of namespace utility, yat, and theplu
Note: See TracBrowser for help on using the repository browser.