scripts/training/MGIZA/src/mkcls/mkcls.cpp - joshua - Git at Google

 /*

 Copyright (C) 1997,1998,1999,2000,2001  Franz Josef Och

 mkcls - a program for making word classes .

 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.

 */


 #ifdef WIN32
 #define strcasecmp strcmpi
 #endif

 #include <stdio.h>
 #include <iostream>
 #include <stdlib.h>
 #include <ctype.h>
 #include "general.h"

 #include "KategProblem.h"
 #include "KategProblemTest.h"

 #include "ProblemTest.h"
 #include "TAOptimization.h"
 #include "GDAOptimization.h"
 #include "RRTOptimization.h"
 #include "SAOptimization.h"
 #include "HCOptimization.h"


 double SigmaVerfaelschung=5.0;
 int OneWithHapas=1;
 char *hapaxInitName=0;


 static int nLaeufe=1,nLaeufeReduce=3;


 static int optimizeParameterAnzahl=10;


 static int IterOptVerf=TA_OPT;


 static int MaxIterOptSteps= -1;


 static int MaxSecs=0;


 static int InitValue=INIT_RAN;


 static int Criterion=CRITERION_ML;


 static int Wwahl=W_DET_DECR;


 static int Kwahl=K_BEST;


 static int NumberCategories=100;


 static int MinWordFrequency=0;


 static int IterOptSet=0;


 static KategProblem *p = 0;


 char korpusName[1024]="train";
 int korpusIsText=1;


 char *FileForOther=0;

 void printUsage(int r)
 {
   cout <<
     "mkcls - a program for making word classes: Usage: \n"
     " mkcls [-nnum] [-ptrain] [-Vfile] opt\n"


     "-V output classes (Default: no file)\n"


     "-n number of optimization runs (Default: 1); larger number => better results\n"

     "-p filename of training corpus (Default: 'train')\n"


     "Example:\n"
     " mkcls -c80 -n10 -pin -Vout opt\n"
     " (generates 80 classes for the corpus 'in' and writes the classes in 'out')\n"
     "Literature: \n"
     " Franz Josef Och: »Maximum-Likelihood-Schätzung von Wortkategorien mit Verfahren\n"
     " der kombinatorischen Optimierung?Studienarbeit, Universität Erlangen-Nürnberg,\n"
     " Germany,1995. \n";
   exit(r);
 }


 void makeIterOpt()
 {
   double maxTime=clockSec()+MaxSecs;
   if(MaxSecs==0)maxTime=0;
   double mean;
   StatVar end,laufzeit,init;
   solveProblem(1+(PrintBestTo!=0),*p,nLaeufe,MaxIterOptSteps,IterOptVerf,
 	       mean,end,laufzeit,init,maxTime);
   if( verboseMode>1 )
     p->dumpOn(cout);
 }


 void makeIzrOpt()
 {
   double maxTime=clockSec()+MaxSecs;
   if(MaxSecs==0)maxTime=0;
   izrOptimization(*p,nLaeufeReduce,nLaeufeReduce,0,maxTime,IterOptVerf);
 }


 int makeMetaOpt(int argc,char **argv)
 {
   int ret=0;

   if(argc==4 || argc==3)
     {
       int typ=0;
       if( argc==4 )
 	{
 	  sscanf(argv[3],"%d",&typ);
 	  assert(typ>0 && typ<=11 );
 	}
       if( isdigit(argv[2][0]) )
 	{
 	  int a;
 	  sscanf(argv[2],"%d",&a);
 	  switch(a)
 	    {
 	    case 1:
 	      SAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,1);
 	      break;
 	    case 2:
 	      SAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,2);
 	      break;
 	    case 3:
 	      SAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,10);
 	      break;
 	    case 4:
 	      TAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,1);
 	      break;
 	    case 5:
 	      TAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,10);
 	      break;
 	    case 6:
 	      RRTOptimization::optimizeValue(*p,nLaeufe,
 					     optimizeParameterAnzahl,1);
 	      break;
 	    case 7:
 	      RRTOptimization::optimizeValue(*p,nLaeufe,
 					     optimizeParameterAnzahl,10);
 	      break;
 	    case 8:
 	      GDAOptimization::optimizeValue(*p,nLaeufe,
 					     optimizeParameterAnzahl,1);
 	      break;
 	    default:
 	      cerr << "Error: Wrong number of parameter (" << argv[2]
 		<< ").\n";
 	      printUsage(1);
 	    }
 	}
       else
 	{
 	  if(strcasecmp(argv[2],"gda")==0)
 	    {
 	      GDAOptimization::optimizeValue(*p,nLaeufe,
 					     optimizeParameterAnzahl,typ);
 	    }
 	  else if(strcasecmp(argv[2],"ta")==0)
 	    {
 	      TAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,typ);
 	    }
 	  else if(strcasecmp(argv[2],"rrt")==0)
 	    {
 	      RRTOptimization::optimizeValue(*p,nLaeufe,
 					     optimizeParameterAnzahl,typ);
 	    }
 	  else if(strcasecmp(argv[2],"sa")==0)
 	    {
 	      SAOptimization::optimizeValue(*p,nLaeufe,
 					    optimizeParameterAnzahl,typ);
 	    }


 	  else
 	    {
 	      cerr << "Error: unknown algorithm" << argv[2] << endl;
 	      printUsage(1);
 	    }
 	}
     }
   else
     {
       cerr << "Error: wrong number of arguments: " << argc << endl;
       printUsage(1);
     }
   return ret;
 }


 void setVerfahren(char *p)
 {
   if(strcasecmp(p,"rrt")==0 )
     IterOptVerf=RRT_OPT;
   else if(strcasecmp(p,"ta")==0)
     IterOptVerf=TA_OPT;
   else if(strcasecmp(p,"gda")==0)
     IterOptVerf=GDA_OPT;
   else if(strcasecmp(p,"sa")==0)
     IterOptVerf=SA_OPT;
   else if(strcasecmp(p,"hc")==0)
     IterOptVerf=HC_OPT;
   else
     {
       cerr << "Error: Unknown iterativ-optimizing algorithm '" << p << "'.\n";
       printUsage(1);
     }
 }


 void setInitValue(char *iv,char *fileForOther)
 {
   if(strcasecmp(iv,"ran")==0 )
     InitValue=INIT_RAN;
   else if(strcasecmp(iv,"aio")==0)
     InitValue=INIT_AIO;
   else if(strcasecmp(iv,"gda")==0)
     InitValue=INIT_LWRW;
   else if(strcasecmp(iv,"freq")==0)
     InitValue=INIT_FREQ;
   else if(strcasecmp(iv,"other")==0)
     {
       InitValue=INIT_OTHER;
       FileForOther=strdup(fileForOther);
     }
   else
     {
       cerr << "Error: Unknown initialization '" << p << "'.\n";;
       printUsage(1);
     }
 }


 void setWwahl(const char *ww)
 {
   if(strcasecmp(ww,"ran")==0 )
     Wwahl=W_RAN;
   else if(strcasecmp(ww,"det")==0)
     Wwahl=W_DET_DECR;
   else if(strcasecmp(ww,"incr")==0)
     Wwahl=W_DET_INCR;
   else
     {
       cerr << "Error: Unknown word-selection '" << ww << "'.\n";;
       printUsage(1);
     }
 }


 void setKwahl(const char *kw)
 {
   if( strcasecmp(kw,"det")==0 )
     Kwahl=K_DET;
   else if(strcasecmp(kw,"ran")==0 )
     Kwahl=K_RAN;
   else if(strcasecmp(kw,"best")==0)
     Kwahl=K_BEST;
   else
     {
       cerr << "Error: Unknown category-selection '" << kw << "'.\n";
       printUsage(1);
     }
 }


 void setParameter(const char *nr1,const char *nr2)
 {
   int n1;
   float n2;
   sscanf(nr1,"%d",&n1);
   sscanf(nr2,"%f",&n2);
   IterOptSet=1;
   switch(n1)
     {
     case 1:
       SAOptimization::defaultAnfAnnRate=n2;
       if(verboseMode)cout << "Parameter gamma_0 (SA) set to "
 	<< SAOptimization::defaultAnfAnnRate << endl;
       iassert(0<=SAOptimization::defaultAnfAnnRate&&
 	      SAOptimization::defaultAnfAnnRate<=1);
       break;
     case 2:
       SAOptimization::defaultEndAnnRate=n2;
       if(verboseMode)cout << "Parameter gamma_e (SA) set to "
 	<< SAOptimization::defaultEndAnnRate << endl;
       iassert(0<=SAOptimization::defaultEndAnnRate
 	      &&SAOptimization::defaultEndAnnRate<=1);
       break;
     case 3:
       SAOptimization::defaultMultiple=n2;
       if(verboseMode)cout << "Parameter nu_e (SA) set to "
 	<< SAOptimization::defaultMultiple << endl;
       iassert( SAOptimization::defaultMultiple>0 );
       break;
     case 4:
       TAOptimization::defaultAnnRate=n2;
       if(verboseMode)cout << "Parameter gamma_{TA} set to "
 	<< TAOptimization::defaultAnnRate << endl;
       iassert(0<=TAOptimization::defaultAnnRate
 	      &&TAOptimization::defaultAnnRate<=1);
       break;
     case 5:
       TAOptimization::defaultMultiple=n2;
       if(verboseMode)cout << "Parameter nu_{TA} set to "
 	<< TAOptimization::defaultMultiple << endl;
       iassert( TAOptimization::defaultMultiple>0 );
       break;
     case 6:
       RRTOptimization::defaultAnnRate=n2;
       if(verboseMode)cout << "Parameter gamma_{RRT} set to "
 	<< RRTOptimization::defaultAnnRate << endl;
       iassert(0<=RRTOptimization::defaultAnnRate
 	      && RRTOptimization::defaultAnnRate<=1);
       break;
     case 7:
       RRTOptimization::defaultMultiple=n2;
       if(verboseMode)cout << "Parameter nu_{RRT} set to "
 	<< RRTOptimization::defaultMultiple << endl;
       iassert( RRTOptimization::defaultMultiple>0 );
       break;
     case 8:
       GDAOptimization::defaultAlpha=n2;
       if(verboseMode)cout << "Parameter alpha set to "
 	<< GDAOptimization::defaultAlpha << endl;
       iassert(0<=GDAOptimization::defaultAlpha
 	      && GDAOptimization::defaultAlpha<1 );
       break;
     default:
       cerr << "Error: Wrong parameter number " << nr1 << " " << n1 << endl;
       printUsage(1);
     }
 }


 void setKorpusName(const char *s)
 {
   strcpy(korpusName,s);
 }

 void setHapaxInitName(const char *s)
 {
   hapaxInitName=strdup(s);
 }

 void setKorpus()
 {
   if( korpusIsText )
     {
       if( (p=fromKModel(korpusName,NumberCategories,InitValue,Criterion,Wwahl|Kwahl,
 			MinWordFrequency))==0)
 	{
 	  cerr << "Error: Could not read the file '" << korpusName << "'.\n";
 	  printUsage(1);
 	}
     }
   else
     {
       if( (p=fromNgrFile(korpusName,NumberCategories,InitValue,Criterion,Wwahl|Kwahl,
 			 MinWordFrequency))==0)
 	{
 	  cerr << "Error: Could not read the file '" << korpusName << "'.\n";
 	  printUsage(1);
 	}
       p->wordFreq.initializeIndex(*(p->words),'1',2,1+NumberCategories/2,!OneWithHapas);
       p->wordFreq.initializeIndex(*(p->words),'2',2+NumberCategories/2,1+NumberCategories,OneWithHapas);
     }
   if( IterOptSet==0 )
     KategProblemSetParameters(*p);
 }


 int main(int argc,char **argv)
 {
   double startTime=clockSec();
   zufallSeed();
   while( argc>1 && argv[1][0]=='-' )
     {

       switch(argv[1][1])
 	{
 	case 'v':
 	  sscanf(argv[1]+2,"%d",&verboseMode);
 	  iassert(verboseMode>=0);
 	  break;
 	case 'O':
 	  sscanf(argv[1]+2,"%d",&OneWithHapas);
 	  cout << "OneWithHapas: " << OneWithHapas << endl;
 	  break;
 	case 'n':
 	  sscanf(argv[1]+2,"%d",&nLaeufe);
 	  nLaeufeReduce=nLaeufe;
 	  iassert( nLaeufe>=1 );
 	  break;
 	case 'l':
 	  Criterion=1;
 	  if( argv[1][2] )
 	    {
 	      sscanf(argv[1]+2,"%lf",&rhoLo);
 	      if( verboseMode )
 		cout << "Parameter rho (for LO) set to" << rhoLo << ".\n";
 	      iassert(0<=rhoLo && rhoLo<=1);
 	    }
 	  if( verboseMode )
 	    cout << "Criterion LO used.\n";
 	  break;
 	case 'y':
 	  Criterion=2;
 	  if( argv[1][2] )
 	    {
 	      sscanf(argv[1]+2,"%lf",&SigmaVerfaelschung);
 	      if( verboseMode )
 		cout << "Parameter rho (for LO) set to" << SigmaVerfaelschung << ".\n";
 	      iassert(0<SigmaVerfaelschung);
 	    }
 	  if( verboseMode )
 	    cout << "My special criterion used.\n";
 	  break;
 	case 'p':
 	  setKorpusName(argv[1]+2);
 	  assert(argv[2]&&argv[2][0]!='-' || argv[2][0]!='i');
 	  break;
 	case 'P':
 	  setKorpusName(argv[1]+2);
 	  korpusIsText=0;
 	  assert(argv[2]&&argv[2][0]!='-' || argv[2][0]!='i');
 	  break;
 	case 'i':
 	  setInitValue(argv[1]+2,argv[2]);
 	  if( InitValue==INIT_OTHER )
 	    argv++,argc--;
 	  break;
 	case 'h':
 	  setHapaxInitName(argv[1]+2);
 	  break;
 	case 'k':
 	  setKwahl(argv[1]+2);
 	  break;
 	case 'w':
 	  setWwahl(argv[1]+2);
 	  break;
 	case 'c':
 	  sscanf(argv[1]+2,"%d",&NumberCategories);
 	  iassert(NumberCategories>=2);
 	  break;
 	case 'm':
 	  sscanf(argv[1]+2,"%d",&MinWordFrequency);
 	  break;
 	case 'e':
 	  setParameter(argv[1]+2,argv[2]);
 	  argv++,argc--;
 	  break;
 	case 'a':
 	  setVerfahren(argv[1]+2);
 	  break;
 	case 'r':
 	  {
 	    int s;
 	    sscanf(argv[1]+2,"%d",&s);
 	    zufallSeed(s);
 	  }
 	  break;
 	case 'V':
 	  if(argv[1][2])
 	    {
 	      char str[1024];
 	      strcpy(str,argv[1]+2);
 	      PrintBestTo=new ofstream(str);
 	      strcat(str,".cats");
 	      PrintBestTo2=new ofstream(str);
 	    }
 	  else
 	    cout << "AUSGABE auf cout\n";
 	  break;
 	case 'M':
 	  sscanf(argv[1]+2,"%d",&MaxIterOptSteps);
 	  break;
 	case 's':
 	  sscanf(argv[1]+2,"%d",&MaxSecs);
 	  break;
 	case 'N':
 	  sscanf(argv[1]+2,"%d",&optimizeParameterAnzahl);
 	  break;
 	case 'o':
 	  GraphOutput = new ofstream(argv[1]+2);
 	  if( GraphOutput==0 )
 	    cerr << "Warning: Open failed for file '" << argv[1]+2 << "'.\n";
 	  break;
     	default:
 	  cerr << "Fehlerhafte Option: " << argv[1] << endl;
 	  printUsage(1);
 	}
       argv++;
       argc--;
     }


   setKorpus();
   if( FileForOther )
     {
       fromCatFile(p,FileForOther);
       p->initialisierung=InitValue;
       p->_initialize(InitValue);
     }

   if( hapaxInitName )
     {
       fromCatFile(p,hapaxInitName,0);
       p->fixInitLike();
     }

   double start2Time=clockSec();

   if(argc>=2 && strcasecmp(argv[1],"opt")==0 )
     makeIterOpt();
   else if(argc>=2 && strcasecmp(argv[1],"meta-opt")==0)
     makeMetaOpt(argc,argv);
   else if(argc>=2 && strcasecmp(argv[1],"izr-opt")==0)
     makeIzrOpt();


   else
     {
       makeIterOpt();
     }

   if( verboseMode )
     {
       cout << "    full-time: " << clockSec()-startTime << endl;
       cout << "optimize-time: " << clockSec()-start2Time << endl;
     }
   return 0;
 }
	/*

	Copyright (C) 1997,1998,1999,2000,2001 Franz Josef Och

	mkcls - a program for making word classes .

	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.

	*/


	#ifdef WIN32
	#define strcasecmp strcmpi
	#endif

	#include <stdio.h>
	#include <iostream>
	#include <stdlib.h>
	#include <ctype.h>
	#include "general.h"

	#include "KategProblem.h"
	#include "KategProblemTest.h"

	#include "ProblemTest.h"
	#include "TAOptimization.h"
	#include "GDAOptimization.h"
	#include "RRTOptimization.h"
	#include "SAOptimization.h"
	#include "HCOptimization.h"


	double SigmaVerfaelschung=5.0;
	int OneWithHapas=1;
	char *hapaxInitName=0;





	static int nLaeufe=1,nLaeufeReduce=3;


	static int optimizeParameterAnzahl=10;


	static int IterOptVerf=TA_OPT;


	static int MaxIterOptSteps= -1;


	static int MaxSecs=0;





	static int InitValue=INIT_RAN;


	static int Criterion=CRITERION_ML;


	static int Wwahl=W_DET_DECR;


	static int Kwahl=K_BEST;


	static int NumberCategories=100;


	static int MinWordFrequency=0;


	static int IterOptSet=0;


	static KategProblem *p = 0;


	char korpusName[1024]="train";
	int korpusIsText=1;


	char *FileForOther=0;

	void printUsage(int r)
	{
	cout <<
	"mkcls - a program for making word classes: Usage: \n"
	" mkcls [-nnum] [-ptrain] [-Vfile] opt\n"






	"-V output classes (Default: no file)\n"


	"-n number of optimization runs (Default: 1); larger number => better results\n"

	"-p filename of training corpus (Default: 'train')\n"








	"Example:\n"
	" mkcls -c80 -n10 -pin -Vout opt\n"
	" (generates 80 classes for the corpus 'in' and writes the classes in 'out')\n"
	"Literature: \n"
	" Franz Josef Och: »Maximum-Likelihood-Schätzung von Wortkategorien mit Verfahren\n"
	" der kombinatorischen Optimierung?Studienarbeit, Universität Erlangen-Nürnberg,\n"
	" Germany,1995. \n";
	exit(r);
	}







	void makeIterOpt()
	{
	double maxTime=clockSec()+MaxSecs;
	if(MaxSecs==0)maxTime=0;
	double mean;
	StatVar end,laufzeit,init;
	solveProblem(1+(PrintBestTo!=0),*p,nLaeufe,MaxIterOptSteps,IterOptVerf,
	mean,end,laufzeit,init,maxTime);
	if( verboseMode>1 )
	p->dumpOn(cout);
	}



	void makeIzrOpt()
	{
	double maxTime=clockSec()+MaxSecs;
	if(MaxSecs==0)maxTime=0;
	izrOptimization(*p,nLaeufeReduce,nLaeufeReduce,0,maxTime,IterOptVerf);
	}



	int makeMetaOpt(int argc,char **argv)
	{
	int ret=0;

	if(argc==4 \|\| argc==3)
	{
	int typ=0;
	if( argc==4 )
	{
	sscanf(argv[3],"%d",&typ);
	assert(typ>0 && typ<=11 );
	}
	if( isdigit(argv[2][0]) )
	{
	int a;
	sscanf(argv[2],"%d",&a);
	switch(a)
	{
	case 1:
	SAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,1);
	break;
	case 2:
	SAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,2);
	break;
	case 3:
	SAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,10);
	break;
	case 4:
	TAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,1);
	break;
	case 5:
	TAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,10);
	break;
	case 6:
	RRTOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,1);
	break;
	case 7:
	RRTOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,10);
	break;
	case 8:
	GDAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,1);
	break;
	default:
	cerr << "Error: Wrong number of parameter (" << argv[2]
	<< ").\n";
	printUsage(1);
	}
	}
	else
	{
	if(strcasecmp(argv[2],"gda")==0)
	{
	GDAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,typ);
	}
	else if(strcasecmp(argv[2],"ta")==0)
	{
	TAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,typ);
	}
	else if(strcasecmp(argv[2],"rrt")==0)
	{
	RRTOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,typ);
	}
	else if(strcasecmp(argv[2],"sa")==0)
	{
	SAOptimization::optimizeValue(*p,nLaeufe,
	optimizeParameterAnzahl,typ);
	}




	else
	{
	cerr << "Error: unknown algorithm" << argv[2] << endl;
	printUsage(1);
	}
	}
	}
	else
	{
	cerr << "Error: wrong number of arguments: " << argc << endl;
	printUsage(1);
	}
	return ret;
	}










	void setVerfahren(char *p)
	{
	if(strcasecmp(p,"rrt")==0 )
	IterOptVerf=RRT_OPT;
	else if(strcasecmp(p,"ta")==0)
	IterOptVerf=TA_OPT;
	else if(strcasecmp(p,"gda")==0)
	IterOptVerf=GDA_OPT;
	else if(strcasecmp(p,"sa")==0)
	IterOptVerf=SA_OPT;
	else if(strcasecmp(p,"hc")==0)
	IterOptVerf=HC_OPT;
	else
	{
	cerr << "Error: Unknown iterativ-optimizing algorithm '" << p << "'.\n";
	printUsage(1);
	}
	}



	void setInitValue(char iv,char fileForOther)
	{
	if(strcasecmp(iv,"ran")==0 )
	InitValue=INIT_RAN;
	else if(strcasecmp(iv,"aio")==0)
	InitValue=INIT_AIO;
	else if(strcasecmp(iv,"gda")==0)
	InitValue=INIT_LWRW;
	else if(strcasecmp(iv,"freq")==0)
	InitValue=INIT_FREQ;
	else if(strcasecmp(iv,"other")==0)
	{
	InitValue=INIT_OTHER;
	FileForOther=strdup(fileForOther);
	}
	else
	{
	cerr << "Error: Unknown initialization '" << p << "'.\n";;
	printUsage(1);
	}
	}


	void setWwahl(const char *ww)
	{
	if(strcasecmp(ww,"ran")==0 )
	Wwahl=W_RAN;
	else if(strcasecmp(ww,"det")==0)
	Wwahl=W_DET_DECR;
	else if(strcasecmp(ww,"incr")==0)
	Wwahl=W_DET_INCR;
	else
	{
	cerr << "Error: Unknown word-selection '" << ww << "'.\n";;
	printUsage(1);
	}
	}


	void setKwahl(const char *kw)
	{
	if( strcasecmp(kw,"det")==0 )
	Kwahl=K_DET;
	else if(strcasecmp(kw,"ran")==0 )
	Kwahl=K_RAN;
	else if(strcasecmp(kw,"best")==0)
	Kwahl=K_BEST;
	else
	{
	cerr << "Error: Unknown category-selection '" << kw << "'.\n";
	printUsage(1);
	}
	}


	void setParameter(const char nr1,const char nr2)
	{
	int n1;
	float n2;
	sscanf(nr1,"%d",&n1);
	sscanf(nr2,"%f",&n2);
	IterOptSet=1;
	switch(n1)
	{
	case 1:
	SAOptimization::defaultAnfAnnRate=n2;
	if(verboseMode)cout << "Parameter gamma_0 (SA) set to "
	<< SAOptimization::defaultAnfAnnRate << endl;
	iassert(0<=SAOptimization::defaultAnfAnnRate&&
	SAOptimization::defaultAnfAnnRate<=1);
	break;
	case 2:
	SAOptimization::defaultEndAnnRate=n2;
	if(verboseMode)cout << "Parameter gamma_e (SA) set to "
	<< SAOptimization::defaultEndAnnRate << endl;
	iassert(0<=SAOptimization::defaultEndAnnRate
	&&SAOptimization::defaultEndAnnRate<=1);
	break;
	case 3:
	SAOptimization::defaultMultiple=n2;
	if(verboseMode)cout << "Parameter nu_e (SA) set to "
	<< SAOptimization::defaultMultiple << endl;
	iassert( SAOptimization::defaultMultiple>0 );
	break;
	case 4:
	TAOptimization::defaultAnnRate=n2;
	if(verboseMode)cout << "Parameter gamma_{TA} set to "
	<< TAOptimization::defaultAnnRate << endl;
	iassert(0<=TAOptimization::defaultAnnRate
	&&TAOptimization::defaultAnnRate<=1);
	break;
	case 5:
	TAOptimization::defaultMultiple=n2;
	if(verboseMode)cout << "Parameter nu_{TA} set to "
	<< TAOptimization::defaultMultiple << endl;
	iassert( TAOptimization::defaultMultiple>0 );
	break;
	case 6:
	RRTOptimization::defaultAnnRate=n2;
	if(verboseMode)cout << "Parameter gamma_{RRT} set to "
	<< RRTOptimization::defaultAnnRate << endl;
	iassert(0<=RRTOptimization::defaultAnnRate
	&& RRTOptimization::defaultAnnRate<=1);
	break;
	case 7:
	RRTOptimization::defaultMultiple=n2;
	if(verboseMode)cout << "Parameter nu_{RRT} set to "
	<< RRTOptimization::defaultMultiple << endl;
	iassert( RRTOptimization::defaultMultiple>0 );
	break;
	case 8:
	GDAOptimization::defaultAlpha=n2;
	if(verboseMode)cout << "Parameter alpha set to "
	<< GDAOptimization::defaultAlpha << endl;
	iassert(0<=GDAOptimization::defaultAlpha
	&& GDAOptimization::defaultAlpha<1 );
	break;
	default:
	cerr << "Error: Wrong parameter number " << nr1 << " " << n1 << endl;
	printUsage(1);
	}
	}



	void setKorpusName(const char *s)
	{
	strcpy(korpusName,s);
	}

	void setHapaxInitName(const char *s)
	{
	hapaxInitName=strdup(s);
	}

	void setKorpus()
	{
	if( korpusIsText )
	{
	if( (p=fromKModel(korpusName,NumberCategories,InitValue,Criterion,Wwahl\|Kwahl,
	MinWordFrequency))==0)
	{
	cerr << "Error: Could not read the file '" << korpusName << "'.\n";
	printUsage(1);
	}
	}
	else
	{
	if( (p=fromNgrFile(korpusName,NumberCategories,InitValue,Criterion,Wwahl\|Kwahl,
	MinWordFrequency))==0)
	{
	cerr << "Error: Could not read the file '" << korpusName << "'.\n";
	printUsage(1);
	}
	p->wordFreq.initializeIndex(*(p->words),'1',2,1+NumberCategories/2,!OneWithHapas);
	p->wordFreq.initializeIndex(*(p->words),'2',2+NumberCategories/2,1+NumberCategories,OneWithHapas);
	}
	if( IterOptSet==0 )
	KategProblemSetParameters(*p);
	}






	int main(int argc,char **argv)
	{
	double startTime=clockSec();
	zufallSeed();
	while( argc>1 && argv[1][0]=='-' )
	{

	switch(argv[1][1])
	{
	case 'v':
	sscanf(argv[1]+2,"%d",&verboseMode);
	iassert(verboseMode>=0);
	break;
	case 'O':
	sscanf(argv[1]+2,"%d",&OneWithHapas);
	cout << "OneWithHapas: " << OneWithHapas << endl;
	break;
	case 'n':
	sscanf(argv[1]+2,"%d",&nLaeufe);
	nLaeufeReduce=nLaeufe;
	iassert( nLaeufe>=1 );
	break;
	case 'l':
	Criterion=1;
	if( argv[1][2] )
	{
	sscanf(argv[1]+2,"%lf",&rhoLo);
	if( verboseMode )
	cout << "Parameter rho (for LO) set to" << rhoLo << ".\n";
	iassert(0<=rhoLo && rhoLo<=1);
	}
	if( verboseMode )
	cout << "Criterion LO used.\n";
	break;
	case 'y':
	Criterion=2;
	if( argv[1][2] )
	{
	sscanf(argv[1]+2,"%lf",&SigmaVerfaelschung);
	if( verboseMode )
	cout << "Parameter rho (for LO) set to" << SigmaVerfaelschung << ".\n";
	iassert(0<SigmaVerfaelschung);
	}
	if( verboseMode )
	cout << "My special criterion used.\n";
	break;
	case 'p':
	setKorpusName(argv[1]+2);
	assert(argv[2]&&argv[2][0]!='-' \|\| argv[2][0]!='i');
	break;
	case 'P':
	setKorpusName(argv[1]+2);
	korpusIsText=0;
	assert(argv[2]&&argv[2][0]!='-' \|\| argv[2][0]!='i');
	break;
	case 'i':
	setInitValue(argv[1]+2,argv[2]);
	if( InitValue==INIT_OTHER )
	argv++,argc--;
	break;
	case 'h':
	setHapaxInitName(argv[1]+2);
	break;
	case 'k':
	setKwahl(argv[1]+2);
	break;
	case 'w':
	setWwahl(argv[1]+2);
	break;
	case 'c':
	sscanf(argv[1]+2,"%d",&NumberCategories);
	iassert(NumberCategories>=2);
	break;
	case 'm':
	sscanf(argv[1]+2,"%d",&MinWordFrequency);
	break;
	case 'e':
	setParameter(argv[1]+2,argv[2]);
	argv++,argc--;
	break;
	case 'a':
	setVerfahren(argv[1]+2);
	break;
	case 'r':
	{
	int s;
	sscanf(argv[1]+2,"%d",&s);
	zufallSeed(s);
	}
	break;
	case 'V':
	if(argv[1][2])
	{
	char str[1024];
	strcpy(str,argv[1]+2);
	PrintBestTo=new ofstream(str);
	strcat(str,".cats");
	PrintBestTo2=new ofstream(str);
	}
	else
	cout << "AUSGABE auf cout\n";
	break;
	case 'M':
	sscanf(argv[1]+2,"%d",&MaxIterOptSteps);
	break;
	case 's':
	sscanf(argv[1]+2,"%d",&MaxSecs);
	break;
	case 'N':
	sscanf(argv[1]+2,"%d",&optimizeParameterAnzahl);
	break;
	case 'o':
	GraphOutput = new ofstream(argv[1]+2);
	if( GraphOutput==0 )
	cerr << "Warning: Open failed for file '" << argv[1]+2 << "'.\n";
	break;
	default:
	cerr << "Fehlerhafte Option: " << argv[1] << endl;
	printUsage(1);
	}
	argv++;
	argc--;
	}


	setKorpus();
	if( FileForOther )
	{
	fromCatFile(p,FileForOther);
	p->initialisierung=InitValue;
	p->_initialize(InitValue);
	}

	if( hapaxInitName )
	{
	fromCatFile(p,hapaxInitName,0);
	p->fixInitLike();
	}

	double start2Time=clockSec();

	if(argc>=2 && strcasecmp(argv[1],"opt")==0 )
	makeIterOpt();
	else if(argc>=2 && strcasecmp(argv[1],"meta-opt")==0)
	makeMetaOpt(argc,argv);
	else if(argc>=2 && strcasecmp(argv[1],"izr-opt")==0)
	makeIzrOpt();


	else
	{
	makeIterOpt();
	}

	if( verboseMode )
	{
	cout << " full-time: " << clockSec()-startTime << endl;
	cout << "optimize-time: " << clockSec()-start2Time << endl;
	}
	return 0;
	}