adjustanalysis.cpp

模糊聚類分析源碼。包含教學文件

/*
  
  Context       : Fuzzy Clustering Algorithms

  Author        : Frank Hoeppner, see also AUTHORS file 

  Description   : implementation of class module AdjustAnalysis
                  
  History       :
    

  Comment       : 
    This file was generated automatically. DO NOT EDIT.

  Copyright     : Copyright (C) 1999-2000 Frank Hoeppner

    This program 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.

    This program 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
*/
/*
  The University of Applied Sciences Oldenburg/Ostfriesland/Wilhelmshaven
  hereby disclaims all copyright interests in the program package `fc' 
  (tool package for fuzzy cluster analysis) written by Frank Hoeppner.
  
  Prof. Haass, President of Vice, 2000-Mar-10
*/

#ifndef AdjustAnalysis_SOURCE
#define AdjustAnalysis_SOURCE

/* configuration include */
#ifdef HAVE_CONFIG_H
/*
//FILETREE_IFDEF HAVE_CONFIG_H
*/
#include "config.h"
/*
//FILETREE_ENDIF
*/
#endif



// necessary includes
#include "AdjustAnalysis.hpp"

// data


// implementation
template < class ANALYSIS >
AdjustAnalysis< ANALYSIS >::AdjustAnalysis
  (
  int a_adjust,
  Algorithm<ANALYSIS>* ap_alg
  )
  : mp_succ_alg(ap_alg)
  , m_adjust(a_adjust)
  
  {
  
  }
template < class ANALYSIS >
AdjustAnalysis< ANALYSIS >::~AdjustAnalysis
  (
  )
  {
  FUNCLOG("~AdjustAnalysis");
  
  delete mp_succ_alg;
  }
template < class ANALYSIS >
void
AdjustAnalysis< ANALYSIS >::operator()
  (
  ANALYSIS& a_analysis
  )
  {
  FUNCLOG("AdjustAnalysis");
  
  int c( a_analysis.option().number_prototypes() );
  if (c<1)
    {
    c=a_analysis.option().max_no_of_clusters();
    invariant(c>=1,"max number of clusters > 0",SOURCELOC);
    if (a_analysis.option().init()==FC_INIT_PROT)
      { a_analysis.option().init()=FC_INIT_AUTO; }
    }
  int n( a_analysis.option().number_features() );
  int p( a_analysis.option().data_dimension() );

    adjust_set_size(a_analysis.prototypes(),c);
    if (n>0) adjust_set_size(a_analysis.links(),n*c);
    a_analysis.option().number_prototypes()=c;
   
    for (
        typename ANALYSIS::prot_iter i_prot(a_analysis.prototypes().begin());
        i_prot != a_analysis.prototypes().end();
        ++i_prot
        )
      {
      if (IS_TAG(m_adjust,FC_ADJUST_CENTER)) 
        (*i_prot).center().adjust(p);
      if (IS_TAG(m_adjust,FC_ADJUST_COEFF))
        (*i_prot).coefficient().adjust(p);
      if (IS_TAG(m_adjust,FC_ADJUST_LINE))
        { (*i_prot).center().adjust(0); (*i_prot).start().adjust(p); (*i_prot).delta().adjust(p); }
      }

    (*mp_succ_alg)(a_analysis);
  //  }
  
  }
template <class SET>
void 
adjust_set_size
  (
  SET& a_set,
  int wanted
  )
  {
  if (wanted<=0)
    {
    a_set.erase(a_set.begin(),a_set.end());
    return;
    }

  int found = a_set.size();

  if (found != wanted)
    if (found > wanted)
      {
      for (int i=0;i<found-wanted;++i) 
        { a_set.pop_back(); }
      }
    else
      {
      typename SET::value_type entry;
      for (int i=0;i<wanted-found;++i) 
        { a_set.insert( a_set.end(), entry); }
      }
  }

// template instantiation



#endif // AdjustAnalysis_SOURCE