scripts/training/giza-pp/GIZA++-v2/reports.cpp

/*

EGYPT Toolkit for Statistical Machine Translation
Written by Yaser Al-Onaizan, Jan Curin, Michael Jahr, Kevin Knight, John Lafferty, Dan Melamed, David Purdy, Franz Och, Noah Smith, and David Yarowsky.

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.

*/
#include <sstream>
#include <time.h>
#include <set>
#include "defs.h"
#include "vocab.h" 
#include "Perplexity.h"
#include "getSentence.h"
#include "TTables.h"
#include "Globals.h"
#include "Parameter.h"

void printHelp(void)
{
  cerr << "Usage:\n\n" << Usage << '\n';
  cerr << "Options (these override parameters set in the config file):\n\n";
  cerr << "\t--v \t\t print verbose message, Warning this is not very descriptive and not systematic.\n";
  cerr << "\t--NODUMPS \t Do not write any files to disk (This will over write dump frequency options).\n";
  cerr << "\t--h[elp]\t\tprint this help\n";
  cerr << "\t--p\t\tUse pegging when generating alignments for Model3 training.  (Default NO PEGGING)\n";
  cerr << "\t--st\t\tto use a fixed ditribution for the fertility parameters when tranfering from model 2 to model 3 (Default complicated estimation)\n";
  printGIZAPars(cout);
}


void generatePerplexityReport(const Perplexity& trainperp, 
			      const Perplexity& testperp, 
			      const Perplexity& trainVperp, 
			      const Perplexity& testVperp, 
			      ostream& of, int trainsize, int testsize, 
			      bool)
{
  unsigned int i, m;
  unsigned int m1 = max(trainperp.size(), testperp.size());
  unsigned int m2 = max(trainVperp.size(), testVperp.size());
  m = max(m1,m2);
  of << "#trnsz\ttstsz\titer\tmodel\ttrn-pp\t\ttest-pp\t\ttrn-vit-pp\t\ttst-vit-pp\n";
  for (i = 0 ; i <m ; i++){
    of << trainsize << '\t' << testsize << '\t' << i<< '\t' << trainperp.modelid[i] << '\t';
    if (i < trainperp.perp.size())
      of << trainperp.perp[i] << "\t\t" ;
    else 
      of << "N/A\t\t";
    if (i<testperp.perp.size())
      of << testperp.perp[i] << "\t\t" ;
    else 
      of << "N/A\t\t";
    if (i < trainVperp.perp.size())
      of << trainVperp.perp[i] << "\t\t" ;
    else 
      of << "N/A\t";
    if (i< testVperp.perp.size())
      of << testVperp.perp[i] << '\n' ;
    else 
      of << "N/A\n";
  }
}

void  printSentencePair(Vector<WordIndex>& es, 
			Vector<WordIndex>& fs, 
			ostream& of)
  
  // just writes a sentece pair to the give output stream, one sentence pair line
  // it writes token ids not actual tokens.
{
  WordIndex i, j, l, m;
  l = es.size() - 1;
  m = fs.size() - 1;
  of << "Source sentence length : " << l << " , target : " << m << "\n"; 
  for (i = 1 ; i <= l ; i++)
    of << es[i] << ' ';
  of << "\n";
  for (j = 1 ; j <= m ; j++)
    of << fs[j] << ' ';
  of << "\n";

}

extern short CompactAlignmentFormat;
void printAlignToFile(const Vector<WordIndex>& es, 
		      const Vector<WordIndex>& fs, 
		      const Vector<WordEntry>& evlist, 
		      const Vector<WordEntry>& fvlist, 
		      ostream& of2, 
		      const Vector<WordIndex>& viterbi_alignment, 
		      int pair_no, double alignment_score)
     
     // prints the given alignment to alignments file (given it stream pointer)
     // in a format recognizable by the draw-alignment tool ... which is of the
     // example (each line triple is one sentence pair): 
     //   # sentence caption 
     //   target_word_1 target_word_2  ..... target_word_m
     //   source_word_1 ({ x y z }) source_word_2 ({ })  .. source_word_n ({w})
     // where x, y, z, and w are positions of target words that each source word
     // is connected to.

{
  WordIndex l, m;
  Vector<Vector<WordIndex> > translations(es.size()); // each english words has a vector 
  // of zero or more translations .
  l = es.size() - 1;
  m = fs.size() - 1;
  if( CompactAlignmentFormat )
    {
      for (WordIndex j = 1 ; j <= m ; j++)
	if( viterbi_alignment[j] )
	  of2 << viterbi_alignment[j]-1 << ' ' << j-1 << ' ';
      of2 << '\n';
    }
  else
    {
      of2 << "# Sentence pair (" << pair_no <<") source length " << l << " target length "<< m << 
	" alignment score : "<< alignment_score << '\n';
      for (WordIndex j = 1 ; j <= m ; j++){
	of2 << fvlist[fs[j]].word << " " ;
	translations[viterbi_alignment[j]].push_back(j);
      }
      of2 << '\n';
      
      for (WordIndex i = 0  ; i <= l ; i++){
	of2 << evlist[es[i]].word << " ({ " ;
	for (WordIndex j = 0 ; j < translations[i].size() ; j++)
	  of2 << translations[i][j] << " " ;
	of2 << "}) ";
      }
      of2 << '\n';
    }
}


void printOverlapReport(const tmodel<COUNT, PROB>& tTable, 
			sentenceHandler& testHandler,  vcbList& trainEList, 
			vcbList& trainFList, vcbList& testEList, vcbList& testFList)
{
  set<pair<WordIndex, WordIndex> > testCoocur ;
  sentPair s ;
  /*  string unseenCoocurFile = Prefix + ".tst.unseen.cooc" ;
      ofstream of_unseenCoocur(unseenCoocurFile.c_str());
      
      string seenCoocurFile = Prefix + ".tst.seen.cooc" ;
      ofstream of_seenCoocur(seenCoocurFile.c_str());
  */  
  testHandler.rewind();
  int seen_coocur = 0, unseen_coocur = 0, srcUnk = 0, trgUnk = 0 ;
  while(testHandler.getNextSentence(s)){    
    for (WordIndex i = 1 ; i < s.eSent.size() ; i++)
      for (WordIndex j = 1 ; j < s.fSent.size() ; j++)	
	testCoocur.insert(pair<WordIndex, WordIndex> (s.eSent[i], s.fSent[j])) ;
  }
  set<pair<WordIndex, WordIndex> >::const_iterator i ;
  for (i = testCoocur.begin() ; i != testCoocur.end() ; ++i){
    if (tTable.getProb((*i).first, (*i).second) > PROB_SMOOTH){
      seen_coocur ++ ;
      //      of_seenCoocur << (*i).first << ' ' << (*i).second << '\n';
    }
    else {
      unseen_coocur++;
      //      of_unseenCoocur << (*i).first << ' ' << (*i).second << '\n';
    }
  }
  
  string trgUnkFile = Prefix + ".tst.trg.unk" ;
  ofstream of_trgUnk(trgUnkFile.c_str());

  for (WordIndex i = 0 ; i <  testFList.getVocabList().size() && i < testFList.uniqTokens();i++)
    if (testFList.getVocabList()[i].freq > 0 && trainFList.getVocabList()[i].freq <= 0){
      of_trgUnk << i << ' ' << testFList.getVocabList()[i].word << ' ' << testFList.getVocabList()[i].freq
		<< '\n';
      trgUnk++ ;
    }
  string srcUnkFile = Prefix + ".tst.src.unk" ;
  ofstream of_srcUnk(srcUnkFile.c_str());

  for (WordIndex j = 0 ; j <  testEList.getVocabList().size() && j < testEList.uniqTokens();j++)
    if (testEList.getVocabList()[j].freq > 0 && trainEList.getVocabList()[j].freq <= 0){
      srcUnk++ ;
      of_srcUnk << j << ' ' << testEList.getVocabList()[j].word << ' ' << testEList.getVocabList()[j].freq
		<< '\n';
    }
  string summaryFile = Prefix + ".tst.stats" ;  
  ofstream of_summary(summaryFile.c_str());
  of_summary << "\t\t STATISTICS ABOUT TEST CORPUS\n\n";
  of_summary << "source unique tokens: " <<  testEList.uniqTokens() << '\n';
  of_summary << "target unique tokens: " <<  testFList.uniqTokens() << '\n';
  of_summary << "unique unseen source tokens: " << srcUnk << '\n';
  of_summary << "unique unseen target tokens: " << trgUnk << '\n';
  of_summary << "cooccurrences not found in the final t table: " << unseen_coocur << '\n';
  of_summary << "cooccurrences found in the final t table: " << seen_coocur << '\n';
  
}