/*
CSTLEMMA - trainable lemmatiser

Copyright (C) 2002, 2005, 2009  Center for Sprogteknologi, University of Copenhagen

This file is part of CSTLEMMA.

CSTLEMMA 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.

CSTLEMMA 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 CSTLEMMA; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
*/
#ifndef SETTINGSAFFIXTRAIN_H
#define SETTINGSAFFIXTRAIN_H

// turn off warnings against dangerous standard functions:
#define _CRT_SECURE_NO_DEPRECATE

// OS-specific stuff:
#ifdef WIN32
#define COPY "copy "
//#define RENAME "ren "
#define COMBIFLEX "combiflex "
#else
#define COPY "cp -f "
//#define RENAME "mv -f "
#define COMBIFLEX "/var/csttools/bin/combiflex "
#endif
//#define COMBIFLEX "combiflex "

extern bool VERBOSE;

#define SLOW 0 
// SLOW 1 
// if training has to be done once more after the removal of the homographs that will be handled in the next iteration.

#define DOTEST 0 
// DOTEST 1
// do automatic (with some percentage of data set aside for test) or manual (interactive) testing

#define MAXPAIRS 500000 //100000 //500000 
// Set this number as high as possible. A high value entails very heavy use 
// of memory!

#define AMBIGUOUS 1
// AMBIGUOUS 1
// Handle ambiguous data by redoing training a second time without the
// homographs that were handled in the first round.

#define PESSIMISTIC 0

#define RULESASTEXTINDENTED 0
/* RULESASTEXTINDENTED 1
produce human readable tree:

threshold 0
|	{^*$	^*$}
		R+	Buffalo	Buffalo,semi-metro	semi-metro,pornofoto	pornofoto, ...
 |	{^*n$	^*n$}
		R+	mandarijn	mandarijn,waslijn	waslijn, ...
  |	{^*en$	^*en$}
		R+	overhebben	overhebben
   |	{^*gen$	^*g$}
		R+	boterbergen	boterberg
    |	{^*ngen$	^*ng$}
		R+	lammergangen	lammergang
     |	{^*ingen$	^*ing$}
		R+	plaatspanningen	plaatspanning,stukkenrekeningen	stukkenrekening, ...
      |	{^*elingen$	^*eling$}
		R+	omwisselingen	omwisseling,wildelingen	wildeling,loonregelingen	loonregeling
...
 |	{^k*u$	^k*uen$}
		R	keu	keuen
threshold 0:3309 words 1553 nodes 1322 nodes with words
*/

#define BRACMATOUTPUT 0
/* BRACMATOUTPUT 1
produce output as a Bracmat expression:
((((=?W: ?A ).(=!A)).1)
,((((=?W n&@(!W: ?A )).(=!A n)).2)
,((((=?W e&@(!W: ?A )).(=!A en)).3)
,((((=?W g&@(!W: ?A )).(=!A g)).4)
,((((=?W n&@(!W: ?A )).(=!A ng)).5)
,((((=?W i&@(!W: ?A )).(=!A ing)).6)
,((((=?W el&@(!W: ?A )).(=!A eling)).7)

...

(((=k ?W u&@(!W: ?A )).(=k !A uen)).1553)
)
*/

#define RULESASTEXT 0
/* RULESASTEXT 1
Produce output as text. This format is close to the binary format, only made 
"readable".

0			
6416		n	n


6260		e	en

500		g	g


132		n	ng

84		i	ing
56		el	eling

...

0k	k	u	uen
*/

#define WRITEINVERTED 0
/* WRITEINVERTED 1
Reverse words in training set and write them to file. You can base another
training on this set and see whether results get better.
Background: words are scanned from left to right. If an "infix" occurs more
than once in a word, the replacement may land in the wrong place. There may
be a bias indicating that "infixes" tend to be near the end, rather than near
the start, of a word. In that case, reversing words may improve results.
*/

#define _NA 1
/* NA 1
Allow weight functions (see comp.cpp) to use the numbers W__NA and N__NA,
the number of wrongly (correctly) lemmatized words that the a candidate rule 
does not apply to. These numbers are not updated (=decremented) as siblings
are added, in contrast to W__W, W__R, R__W and R__R.
*/

#define LEMMACLASS 0
/* LEMMACLASS 1
Read lemma class from file. No code in the training program currently uses
the lemma class.
*/

#define LEMMAINL 0
/* LEMMAINL 1
Read lemma frequency from file. No code in the training program currently uses
the lemma frequency.
Also enables word frequency.
*/

#define WORDCLASS 0
/* WORDCLASS 1
Read word class from file. No code in the training program currently uses
the word class.
*/

#if defined __BORLANDC__
#define CONSTSTRCHR
#define REFER(v) v;
#elif defined _MSC_VER
#define REFER(v) v;
#else
#define REFER(v)
#endif

#define ANY ':' // '*'
#define START '^'
#define END '$'

#endif