/***************************************************************************
* Copyright (C) 2008 by Matthias Ihrke *
* mihrke@uni-goettingen.de *
* *
* 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 "tools.h"
#include "eeg.h"
#include "mathadd.h"
/** Remove baseline from eeg-data. Computes the average of the eeg-values
in the given time-window and substracts it from the all data.
\param eeg - the struct
\param win_from - the time-window in ms (starting from)
\param win_to - the time-window in ms (until)
\note both win_from and win_to must be in the times-array of eeg->times
*/
EEG* eeg_remove_baseline( EEG *eeg, double win_from, double win_to, bool alloc ){
#ifdef FIXEEG
int lim[2], c, i;
double mean;
EEG *eeg_out;
if( !eeg->times ){
errprintf("Need times-array, aborting...\n");
return NULL;
}
if( alloc ){
eeg_out = eeg_clone( eeg, EEG_CLONE_ALL );
} else {
eeg_out = eeg;
}
lim[0] = closest_index( eeg->times, eeg->n, win_from );
lim[1] = closest_index( eeg->times, eeg->n, win_to );
if( lim[1]<=lim[0] ){
errprintf( "The specified limits are funny: %.2f-%.2f (results in %i-%i)\n",
win_from, win_to, lim[0], lim[1] );
}
for( c=0; c<eeg->nbchan; c++ ){
for( i=0; i<eeg->ntrials; i++ ){
mean=dblp_mean( eeg->data[c][i]+lim[0], lim[1]-lim[0] );
// printf(" mean=%f\n", mean);
dblp_minus_scalar( eeg->data[c][i], eeg->n, mean );
}
}
return eeg_out;
#endif
}
