source: branches/0.4-stable/yat/classifier/InputRanker.cc @ 1392

// $Id$

/*
  Copyright (C) 2004 Peter Johansson
  Copyright (C) 2005 Jari Häkkinen, Peter Johansson
  Copyright (C) 2006, 2007 Jari Häkkinen, Peter Johansson, Markus Ringnér

  This file is part of the yat library, http://dev.thep.lu.se/yat

  The yat library is free software; you can redistribute it and/or
  modify it under the terms of the GNU General Public License as
  published by the Free Software Foundation; either version 2 of the
  License, or (at your option) any later version.

  The yat library is distributed in the hope that it will be useful,
  but WITHOUT ANY WARRANTY; without even the implied warranty of
  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  General Public License for more details.

  You should have received a copy of the GNU General Public License
  along with this program; if not, write to the Free Software
  Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA
  02111-1307, USA.
*/

#include "InputRanker.h"
#include "MatrixLookup.h"
#include "MatrixLookupWeighted.h"
#include "DataLookup1D.h"
#include "DataLookupWeighted1D.h"
#include "Target.h"
#include "yat/statistics/Score.h"
#include "yat/utility/stl_utility.h"

#include <cassert>
#include <cmath>
#include <functional>
#include <utility>
#include <vector>

namespace theplu {
namespace yat {
namespace classifier {  


  InputRanker::InputRanker(const MatrixLookup& data, 
                           const Target& target, 
                           const statistics::Score& score_object)
  {
    assert(data.columns()==target.size());
    size_t nof_genes = data.rows();

    //scoring each input
    std::vector<std::pair<double, size_t> > score;
    for (size_t i=0; i<nof_genes; i++) {
      double area = score_object.score(target,DataLookup1D(data,i,true));
      score.push_back(std::make_pair(area,i));
    }

    //sort the scores and assign id_ and rank_
    sort(score.begin(), score.end(), std::greater<std::pair<double,size_t> >());
    
    id_.resize(nof_genes);
    rank_.resize(nof_genes);
    score_.resize(nof_genes);
    for (size_t i=0; i<nof_genes; i++){
      id_[i]=score[i].second;
      score_[i]=score[i].first;
      rank_[id_[i]]=i;            
    }
  }


  InputRanker::InputRanker(const MatrixLookupWeighted& data, 
                           const Target& target, 
                           const statistics::Score& score_object)
  {
    assert(data.columns()==target.size());
    size_t nof_genes = data.rows();

    //scoring each input
    std::vector<std::pair<double, size_t> > score;
    for (size_t i=0; i<nof_genes; i++) {
      double area=score_object.score(target,DataLookupWeighted1D(data,i,true));
      score.push_back(std::make_pair(area,i));
    }

    //sort the scores and assign id_ and rank_
    sort(score.begin(), score.end(), std::greater<std::pair<double,size_t> >());
    
    id_.resize(nof_genes);
    rank_.resize(nof_genes);
    score_.resize(nof_genes);
    for (size_t i=0; i<nof_genes; i++){
      id_[i]=score[i].second;
      score_[i]=score[i].first;
      rank_[id_[i]]=i;            
    }
  }


  const std::vector<size_t>& InputRanker::id(void) const
  {
    return id_;
  }


  const std::vector<size_t>& InputRanker::rank(void) const
  {
    return rank_;
  }


  double InputRanker::score(size_t rank) const
  {
    return score_[rank];
  }

}}} // of namespace classifier, yat, and theplu