StrTableVMatrix.cc

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// PLearn ("A C++ Machine Learning Library")
// Copyright (C) 2002 Pascal Vincent and Julien Keable
// 

// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions are met:
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//  1. Redistributions of source code must retain the above copyright
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//  2. Redistributions in binary form must reproduce the above copyright
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//     documentation and/or other materials provided with the distribution.
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//     products derived from this software without specific prior written
//     permission.
// 
// THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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// This file is part of the PLearn library. For more information on the PLearn
// library, go to the PLearn Web site at www.plearn.org
 
/* *******************************************************      
   * $Id: StrTableVMatrix.cc,v 1.5 2004/03/23 23:08:09 morinf Exp $
   * This file is part of the PLearn library.
   ******************************************************* */

#include "StrTableVMatrix.h"

namespace PLearn {
using namespace std;

StrTableVMatrix::StrTableVMatrix()
{}


/* This contructor takes a StringTable (which is simply a matrix of string) and converts it to a matrix of reals
   using real->string and string->real maps
*/
StrTableVMatrix::StrTableVMatrix(const StringTable & st)
  : inherited(Mat(st.length(),st.width()))
{
  map<string,real>::iterator it;
  double dbl;
  TVec<int> mapnum(st.width(),0);
  TVec<string> vec(st.width());
  TVec<bool> hasreal;
  Vec colmax;
  hasreal.resize(st.width());
  colmax.resize(st.width());
  
  for(int j=0;j<st.width();j++)
    {
      hasreal[j]=false;
      colmax[j]=0;
    }

  map_sr.resize(st.width());
  map_rs.resize(st.width());

  for(int j=0;j<st.width();j++)
    declareField(j,st.getFieldName(j), VMField::UnknownType);

  // 1st pass to detect maximums
  for(int i=0;i<st.length();i++)
    {
      vec=st(i);
      for(int j=0;j<st.width();j++)
        if(pl_isnumber(vec[j],&dbl))
          {
            hasreal[j]=true;
            if(!is_missing(dbl))
              if(colmax[j]<dbl)
                colmax[j]=dbl;
          }
    }

  for(int j=0;j<st.width();j++)
    if(hasreal[j])
      mapnum[j]=(int)ceil((double)colmax[j])+1;
    
  for(int i=0;i<st.length();i++)
    {
      vec=st(i);
      for(int j=0;j<st.width();j++)
        if(!pl_isnumber(vec[j],&dbl))
          {
            if((it=map_sr[j].find(vec[j]))==map_sr[j].end())
              {
                data(i,j)=mapnum[j];
                map_sr[j][vec[j]]=mapnum[j];
                map_rs[j][mapnum[j]]=vec[j];
                mapnum[j]++;
              }      
            else data(i,j)=it->second;
          }
        else data(i,j)=dbl;
    }
  
}

PLEARN_IMPLEMENT_OBJECT(StrTableVMatrix, "ONE LINE DESCR", "NO HELP");

} // end of namespace PLearn

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