int main( int argc , char *argv[] )
{
THD_3dim_dataset *inset=NULL , *outset ;
THD_3dim_dataset **insar=NULL ; int nsar=0 ;
int iarg=1 , ii,kk , ids ;
MCW_cluster *nbhd=NULL ;
char *prefix="./localhistog" ;
int ntype=0 ; float na=0.0f,nb=0.0f,nc=0.0f ;
int verb=1 , do_prob=0 ;
int nx=0,ny=0,nz=0,nvox=0, rbot,rtop ;
char *labfile=NULL ; NI_element *labnel=NULL ;
int nlab=0 , *labval=NULL ; char **lablab=NULL ; char buf[THD_MAX_SBLABEL] ;
UINT32 *ohist , *mhist=NULL ; char *ohist_name=NULL ; int ohzadd=0 ;
int *rlist , numval ; float mincount=0.0f ; int mcc ;
int *exlist=NULL, numex=0 ;
int do_excNONLAB=0 ;
/*---- for the clueless who wish to become clued-in ----*/
if( argc == 1 ){ usage_3dLocalHistog(1); exit(0); } /* Bob's help shortcut */
/*---- official startup ---*/
#if defined(USING_MCW_MALLOC) && !defined(USE_OMP)
enable_mcw_malloc() ;
#endif
PRINT_VERSION("3dLocalHistog"); mainENTRY("3dLocalHistog main"); machdep();
AFNI_logger("3dLocalHistog",argc,argv);
if( getpid()%2 ) AUTHOR("Bilbo Baggins"); else AUTHOR("Thorin Oakenshield");
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
/*---- loop over options ----*/
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcmp(argv[iarg],"-help") == 0 || strcmp(argv[iarg],"-h") == 0){
usage_3dLocalHistog(strlen(argv[iarg])>3 ? 2:1);
exit(0);
}
if( strncmp(argv[iarg],"-qu",3) == 0 ){
verb = 0 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-verb",5) == 0 ){
verb++ ; iarg++ ; continue ;
}
#ifdef ALLOW_PROB
if( strncmp(argv[iarg],"-prob",5) == 0 ){
do_prob = 1 ; iarg++ ; continue ;
}
#endif
if( strcmp(argv[iarg],"-exclude") == 0 ){
int ebot=-6666666,etop=-6666666 , ee ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-exclude'") ;
sscanf(argv[iarg],"%d..%d",&ebot,&etop) ;
if( ebot >= -TWO15 && ebot <= TWO15 ){
if( etop < -TWO15 || etop > TWO15 || etop < ebot ) etop = ebot ;
exlist = (int *)realloc(exlist,sizeof(int)*(etop-ebot+1+numex+1)) ;
for( ee=ebot ; ee <= etop ; ee++ ){ if( ee != 0 ) exlist[numex++] = ee ; }
}
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-excNONLAB") == 0 ){
do_excNONLAB = 1 ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-prefix") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '-prefix'") ;
prefix = strdup(argv[iarg]) ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Bad -prefix!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-hsave") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '-hsave'") ;
ohist_name = strdup(argv[iarg]) ;
if( !THD_filename_ok(ohist_name) ) ERROR_exit("Bad -hsave!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-mincount") == 0 ){
char *cpt ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-mincount'") ;
mincount = (float)strtod(argv[iarg],&cpt) ;
#if 0
if( mincount > 0.0f && mincount < 50.0f && *cpt == '%' ) /* percentage */
mincount = -0.01f*mincount ;
#endif
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-nbhd") == 0 ){
char *cpt ;
if( ntype > 0 ) ERROR_exit("Can't have 2 '-nbhd' options") ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-nbhd'") ;
cpt = argv[iarg] ;
if( strncasecmp(cpt,"SPHERE",6) == 0 ){
sscanf( cpt+7 , "%f" , &na ) ;
ntype = NTYPE_SPHERE ;
} else if( strncasecmp(cpt,"RECT",4) == 0 ){
sscanf( cpt+5 , "%f,%f,%f" , &na,&nb,&nc ) ;
if( na == 0.0f && nb == 0.0f && nc == 0.0f )
ERROR_exit("'RECT(0,0,0)' is not a legal neighborhood") ;
ntype = NTYPE_RECT ;
} else if( strncasecmp(cpt,"RHDD",4) == 0 ){
sscanf( cpt+5 , "%f" , &na ) ;
if( na == 0.0f ) ERROR_exit("Can't have a RHDD of radius 0") ;
ntype = NTYPE_RHDD ;
} else if( strncasecmp(cpt,"TOHD",4) == 0 ){
sscanf( cpt+5 , "%f" , &na ) ;
if( na == 0.0f ) ERROR_exit("Can't have a TOHD of radius 0") ;
ntype = NTYPE_TOHD ;
} else {
ERROR_exit("Unknown -nbhd shape: '%s'",cpt) ;
}
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-lab_file") == 0 || strcmp(argv[iarg],"-labfile") == 0 ){
char **labnum ; int nbad=0 ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
if( labfile != NULL ) ERROR_exit("Can't use '%s' twice!",argv[iarg-1]) ;
labfile = strdup(argv[iarg]) ;
labnel = THD_string_table_read(labfile,0) ;
if( labnel == NULL || labnel->vec_num < 2 )
ERROR_exit("Can't read label file '%s'",labfile) ;
nlab = labnel->vec_len ;
labnum = (char **)labnel->vec[0] ;
lablab = (char **)labnel->vec[1] ;
labval = (int *)calloc(sizeof(int),nlab) ;
for( ii=0 ; ii < nlab ; ii++ ){
if( labnum[ii] != NULL ){
labval[ii] = (int)strtod(labnum[ii],NULL) ;
if( labval[ii] < -TWO15 || labval[ii] > TWO15 ){ labval[ii] = 0; nbad++; }
}
}
if( nbad > 0 )
ERROR_message("%d label values are outside the range %d..%d :-(" ,
nbad , -TWO15 , TWO15 ) ;
iarg++ ; continue ;
}
ERROR_message("** 3dLocalHistog: Illegal option: '%s'",argv[iarg]) ;
suggest_best_prog_option(argv[0], argv[iarg]);
exit(1) ;
} /*--- end of loop over options ---*/
/*---- check for stupid user inputs ----*/
if( iarg >= argc ) ERROR_exit("No datasets on command line?") ;
if( ohist_name == NULL && strcmp(prefix,"NULL") == 0 )
ERROR_exit("-prefix NULL is only meaningful if you also use -hsave :-(") ;
/*------------ scan input datasets, built overall histogram ------------*/
nsar = argc - iarg ;
insar = (THD_3dim_dataset **)malloc(sizeof(THD_3dim_dataset *)*nsar) ;
if( verb ) fprintf(stderr,"Scanning %d datasets ",nsar) ;
ohist = (UINT32 *)calloc(sizeof(UINT32),TWO16) ;
for( ids=iarg ; ids < argc ; ids++ ){ /* dataset loop */
insar[ids-iarg] = inset = THD_open_dataset(argv[ids]) ;
CHECK_OPEN_ERROR(inset,argv[ids]) ;
if( ids == iarg ){
nx = DSET_NX(inset); ny = DSET_NY(inset); nz = DSET_NZ(inset); nvox = nx*ny*nz;
} else if( nx != DSET_NX(inset) ||
ny != DSET_NY(inset) || nz != DSET_NZ(inset) ){
ERROR_exit("Dataset %s grid doesn't match!",argv[ids]) ;
}
if( !THD_datum_constant(inset->dblk) )
ERROR_exit("Dataset %s doesn't have a fixed data type! :-(",argv[ids]) ;
if( THD_need_brick_factor(inset) )
ERROR_exit("Dataset %s has scale factors! :-(",argv[ids]) ;
if( DSET_BRICK_TYPE(inset,0) != MRI_byte &&
DSET_BRICK_TYPE(inset,0) != MRI_short &&
DSET_BRICK_TYPE(inset,0) != MRI_float )
ERROR_exit("Dataset %s is not byte- or short-valued! :-(",argv[ids]) ;
DSET_load(inset) ; CHECK_LOAD_ERROR(inset) ;
for( ii=0 ; ii < DSET_NVALS(inset) ; ii++ ){ /* add to overall histogram */
if( verb ) fprintf(stderr,".") ;
switch( DSET_BRICK_TYPE(inset,ii) ){
case MRI_short:{
short *sar = (short *)DSET_BRICK_ARRAY(inset,ii) ;
for( kk=0 ; kk < nvox ; kk++ ) ohist[ sar[kk]+TWO15 ]++ ;
}
break ;
case MRI_byte:{
byte *bar = (byte *)DSET_BRICK_ARRAY(inset,ii) ;
for( kk=0 ; kk < nvox ; kk++ ) ohist[ bar[kk]+TWO15 ]++ ;
}
break ;
case MRI_float:{
float *far = (float *)DSET_BRICK_ARRAY(inset,ii) ; short ss ;
for( kk=0 ; kk < nvox ; kk++ ){ ss = SHORTIZE(far[kk]); ohist[ss+TWO15]++; }
}
break ;
}
} /* end of sub-brick loop */
DSET_unload(inset) ; /* will re-load later, as needed */
} /* end of dataset loop */
if( verb ) fprintf(stderr,"\n") ;
/*-------------- process overall histogram for fun and profit -------------*/
/* if we didn't actually find 0, put it in the histogram now */
if( ohist[0+TWO15] == 0 ){ ohist[0+TWO15] = 1 ; ohzadd = 1 ; }
/* excNONLAB? */
if( nlab > 0 && do_excNONLAB ){
byte *klist = (byte *)calloc(sizeof(byte),TWO16) ; int nee ;
for( ii=0 ; ii < nlab ; ii++ ){ if( labval[ii] != 0 ) klist[labval[ii]+TWO15] = 1 ; }
for( nee=ii=0 ; ii < TWO16 ; ii++ ){ if( !klist[ii] ) nee++ ; }
exlist = (int *)realloc(exlist,sizeof(int)*(numex+nee+1)) ;
for( ii=0 ; ii < TWO16 ; ii++ ){ if( ii != TWO15 && !klist[ii] ) exlist[numex++] = ii-TWO15 ; }
free(klist) ;
}
/* make a copy of ohist and edit it for mincount, etc */
mhist = (UINT32 *)malloc(sizeof(UINT32)*TWO16) ;
memcpy(mhist,ohist,sizeof(UINT32)*TWO16) ;
mcc = (mincount < 0.0f) ? (int)(-mincount*nvox) : (int)mincount ;
if( mcc > 1 ){
for( ids=ii=0 ; ii < TWO16 ; ii++ ){
if( ii != TWO15 && mhist[ii] > 0 && mhist[ii] < mcc ){ mhist[ii] = 0; ids++; }
}
if( ids > 0 && verb )
INFO_message("Edited out %d values with overall histogram counts less than %d",ids,mcc) ;
}
if( numex > 0 ){
int ee ;
for( ids=0,ii=0 ; ii < numex ; ii++ ){
ee = exlist[ii] ;
if( mhist[ee+TWO15] > 0 ){ mhist[ee+TWO15] = 0; ids++; }
}
free(exlist) ;
if( ids > 0 && verb )
INFO_message("Edited out %d values from the exclude list",ids) ;
}
/* count number of values with nonzero (edited) counts */
numval = 0 ;
for( ii=0 ; ii < TWO16 ; ii++ ) if( mhist[ii] != 0 ) numval++ ;
if( numval == 0 ) ERROR_exit("Nothing found! WTF?") ; /* should not happen */
/* make list of all values with nonzero (edited) count */
rlist = (int *)malloc(sizeof(int)*numval) ;
if( verb > 1 ) fprintf(stderr,"++ Include list:") ;
for( ii=kk=0 ; ii < TWO16 ; ii++ ){
if( mhist[ii] != 0 ){
rlist[kk++] = ii-TWO15 ;
if( verb > 1 ) fprintf(stderr," %d[%u]",ii-TWO15,mhist[ii]) ;
}
}
if( verb > 1 ) fprintf(stderr,"\n") ;
rbot = rlist[0] ; rtop = rlist[numval-1] ; /* smallest and largest values found */
if( rbot == rtop ) ERROR_exit("Only one value (%d) found in all inputs!",rbot) ;
/* if 0 isn't first in rlist, then
put it in first place and move negative values up by one spot */
if( rbot < 0 ){
for( kk=0 ; kk < numval && rlist[kk] != 0 ; kk++ ) ; /*nada*/
if( kk < numval ){ /* should always be true */
for( ii=kk-1 ; ii >= 0 ; ii-- ) rlist[ii+1] = rlist[ii] ;
rlist[0] = 0 ;
}
}
if( verb )
INFO_message("Value range = %d..%d (%d distinct values)",rbot,rtop,numval );
/* save overall histogram? */
if( ohist_name != NULL ){
FILE *fp = fopen(ohist_name,"w") ; int nl=0 ;
if( fp == NULL ) ERROR_exit("Can't open -hsave '%s' for output!",ohist_name) ;
if( ohzadd ) ohist[0+TWO15] = 0 ;
for( ii=0 ; ii < TWO16 ; ii++ ){
if( ohist[ii] != 0 ){ fprintf(fp,"%6d %u\n",ii-TWO15,ohist[ii]); nl++; }
}
fclose(fp) ;
if( verb ) INFO_message("Wrote %d lines to -hsave file %s",nl,ohist_name) ;
}
free(ohist) ; free(mhist) ; mhist = ohist = NULL ; /* done with this */
if( strcmp(prefix,"NULL") == 0 ) exit(0) ; /* special case */
/*----------- build the neighborhood mask -----------*/
if( ntype <= 0 ){ /* default neighborhood */
ntype = NTYPE_SPHERE ; na = 0.0f ;
if( verb ) INFO_message("Using default neighborhood = self") ;
}
switch( ntype ){
default:
ERROR_exit("WTF? ntype=%d",ntype) ; /* should not happen */
case NTYPE_SPHERE:{
float dx , dy , dz ;
if( na < 0.0f ){ dx = dy = dz = 1.0f ; na = -na ; }
else { dx = fabsf(DSET_DX(insar[0])) ;
dy = fabsf(DSET_DY(insar[0])) ;
dz = fabsf(DSET_DZ(insar[0])) ; }
nbhd = MCW_spheremask( dx,dy,dz , na ) ;
}
break ;
case NTYPE_RECT:{
float dx , dy , dz ;
if( na < 0.0f ){ dx = 1.0f; na = -na; } else dx = fabsf(DSET_DX(insar[0]));
if( nb < 0.0f ){ dy = 1.0f; nb = -nb; } else dy = fabsf(DSET_DY(insar[0]));
if( nc < 0.0f ){ dz = 1.0f; nc = -nc; } else dz = fabsf(DSET_DZ(insar[0]));
nbhd = MCW_rectmask( dx,dy,dz , na,nb,nc ) ;
}
break ;
case NTYPE_RHDD:{
float dx , dy , dz ;
if( na < 0.0f ){ dx = dy = dz = 1.0f ; na = -na ; }
else { dx = fabsf(DSET_DX(insar[0])) ;
dy = fabsf(DSET_DY(insar[0])) ;
dz = fabsf(DSET_DZ(insar[0])) ; }
nbhd = MCW_rhddmask( dx,dy,dz , na ) ;
}
break ;
case NTYPE_TOHD:{
float dx , dy , dz ;
if( na < 0.0f ){ dx = dy = dz = 1.0f ; na = -na ; }
else { dx = fabsf(DSET_DX(insar[0])) ;
dy = fabsf(DSET_DY(insar[0])) ;
dz = fabsf(DSET_DZ(insar[0])) ; }
nbhd = MCW_tohdmask( dx,dy,dz , na ) ;
}
break ;
}
if( verb ) INFO_message("Neighborhood comprises %d voxels",nbhd->num_pt) ;
/*------- actually do some work for a change (is it lunchtime yet?) -------*/
if( verb ) fprintf(stderr,"Voxel-wise histograms ") ;
outset = THD_localhistog( nsar,insar , numval,rlist , nbhd , do_prob,verb ) ;
if( outset == NULL ) ERROR_exit("Function THD_localhistog() fails?!") ;
/*---- save resulting dataset ----*/
EDIT_dset_items( outset , ADN_prefix,prefix , ADN_none ) ;
tross_Copy_History( insar[0] , outset ) ;
tross_Make_History( "3dLocalHistog" , argc,argv , outset ) ;
/* but first attach labels to sub-bricks */
EDIT_BRICK_LABEL(outset,0,"0:Other") ;
for( kk=1 ; kk < numval ; kk++ ){
sprintf(buf,"%d:",rlist[kk]) ;
for( ii=0 ; ii < nlab ; ii++ ){
if( labval[ii] == rlist[kk] && lablab[ii] != NULL ){
ids = strlen(buf) ;
MCW_strncpy(buf+ids,lablab[ii],THD_MAX_SBLABEL-ids) ;
break ;
}
}
EDIT_BRICK_LABEL(outset,kk,buf) ;
}
DSET_write( outset ) ;
if( verb ) WROTE_DSET( outset ) ;
exit(0) ;
}
int main( int argc , char *argv[] )
{
int iarg=1 , ii , do_iwarp=0 ;
char *prefix = "NwarpCat" ;
mat44 wmat , smat , qmat ;
THD_3dim_dataset *oset=NULL ;
char *cwarp_all=NULL ; int ntot=0 ;
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcasecmp(argv[1],"-help") == 0 ) NWC_help() ;
/*-- bureaucracy --*/
mainENTRY("3dNwarpCat"); machdep();
AFNI_logger("3dNwarpCat",argc,argv);
PRINT_VERSION("3dNwarpCat"); AUTHOR("Zhark the Warper");
(void)COX_clock_time() ;
putenv("AFNI_WSINC5_SILENT=YES") ;
/*-- initialization --*/
CW_no_expad = 1 ; /* don't allow automatic padding of input warp */
Hverb = 0 ; /* don't be verbose inside mri_nwarp.c */
for( ii=0 ; ii < NWMAX ; ii++ ) cwarp[ii] = NULL ;
/*-- scan args --*/
while( iarg < argc && argv[iarg][0] == '-' ){
/*---------------*/
if( strcasecmp(argv[iarg],"-iwarp") == 0 ){
do_iwarp = 1 ; iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-space") == 0 ){
sname = strdup(argv[++iarg]) ; iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-NN") == 0 || strncasecmp(argv[iarg],"-nearest",6) == 0 ){
WARNING_message("NN interpolation not legal here -- switched to linear") ;
interp_code = MRI_LINEAR ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-linear",4)==0 || strncasecmp(argv[iarg],"-trilinear",6)==0 ){
interp_code = MRI_LINEAR ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-cubic",4)==0 || strncasecmp(argv[iarg],"-tricubic",6)==0 ){
WARNING_message("cubic interplation not legal here -- switched to quintic") ;
interp_code = MRI_QUINTIC ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-quintic",4)==0 || strncasecmp(argv[iarg],"-triquintic",6)==0 ){
interp_code = MRI_QUINTIC ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-wsinc",5) == 0 ){
interp_code = MRI_WSINC5 ; iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-expad") == 0 ){
int expad ;
if( ++iarg >= argc ) ERROR_exit("no argument after '%s' :-(",argv[iarg-1]) ;
expad = (int)strtod(argv[iarg],NULL) ;
if( expad < 0 ){
WARNING_message("-expad %d is illegal and is set to zero",expad) ;
expad = 0 ;
}
CW_extra_pad = expad ; /* this is how we force extra padding */
iarg++ ; continue ;
}
/*---------------*/
if( strncasecmp(argv[iarg],"-interp",5)==0 ){
char *inam ;
if( ++iarg >= argc ) ERROR_exit("no argument after '%s' :-(",argv[iarg-1]) ;
inam = argv[iarg] ; if( *inam == '-' ) inam++ ;
if( strcasecmp(inam,"NN")==0 || strncasecmp(inam,"nearest",5)==0 ){
WARNING_message("NN interpolation not legal here -- changed to linear") ;
interp_code = MRI_LINEAR ;
} else if( strncasecmp(inam,"linear",3)==0 || strncasecmp(inam,"trilinear",5)==0 ){
interp_code = MRI_LINEAR ;
} else if( strncasecmp(inam,"cubic",3)==0 || strncasecmp(inam,"tricubic",5)==0 ){
WARNING_message("cubic interplation not legal here -- changed to quintic") ;
interp_code = MRI_QUINTIC ;
} else if( strncasecmp(inam,"quintic",3)==0 || strncasecmp(inam,"triquintic",5)==0 ){
interp_code = MRI_QUINTIC ;
} else if( strncasecmp(inam,"wsinc",4)==0 ){
interp_code = MRI_WSINC5 ;
} else {
ERROR_exit("Unknown code '%s' after '%s' :-(",argv[iarg],argv[iarg-1]) ;
}
iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-verb") == 0 ){
verb++ ; NwarpCalcRPN_verb(verb) ; iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-prefix") == 0 ){
if( ++iarg >= argc ) ERROR_exit("no argument after '%s' :-(",argv[iarg-1]) ;
prefix = argv[iarg] ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Illegal name after '%s'",argv[iarg-1]) ;
iarg++ ; continue ;
}
/*---------------*/
if( strncasecmp(argv[iarg],"-warp",5) == 0 ){
int nn ;
if( iarg >= argc-1 ) ERROR_exit("no argument after '%s' :-(",argv[iarg]) ;
if( !isdigit(argv[iarg][5]) ) ERROR_exit("illegal format for '%s' :-(",argv[iarg]) ;
nn = (int)strtod(argv[iarg]+5,NULL) ;
if( nn <= 0 || nn > NWMAX )
ERROR_exit("illegal warp index in '%s' :-(",argv[iarg]) ;
if( cwarp[nn-1] != NULL )
ERROR_exit("'%s': you can't specify warp #%d more than once :-(",argv[iarg],nn) ;
cwarp[nn-1] = strdup(argv[++iarg]) ;
if( nn > nwtop ) nwtop = nn ;
iarg++ ; continue ;
}
/*---------------*/
ERROR_message("Confusingly Unknown option '%s' :-(",argv[iarg]) ;
suggest_best_prog_option(argv[0],argv[iarg]) ;
exit(1) ;
}
/*-- load any warps left on the command line, after options --*/
for( ; iarg < argc && nwtop < NWMAX-1 ; iarg++ )
cwarp[nwtop++] = strdup(argv[iarg]) ;
/*-- check if all warp strings are affine matrices --*/
#undef AFFINE_WARP_STRING
#define AFFINE_WARP_STRING(ss) \
( strstr((ss)," ") == NULL && \
( strcasestr((ss),".1D") != NULL || strcasestr((ss),".txt") != NULL ) )
for( ntot=ii=0 ; ii < nwtop ; ii++ ){
if( cwarp[ii] == NULL ) continue ;
ntot += strlen(cwarp[ii]) ;
if( ! AFFINE_WARP_STRING(cwarp[ii]) ) break ; /* not affine */
}
if( ntot == 0 ) ERROR_exit("No warps on command line?!") ;
if( ii == nwtop ){ /* all are affine (this is for Ziad) */
char *fname = malloc(sizeof(char)*(strlen(prefix)+16)) ; FILE *fp ;
float a11,a12,a13,a14,a21,a22,a23,a24,a31,a32,a33,a34 ;
LOAD_IDENT_MAT44(wmat) ;
for( ii=0 ; ii < nwtop ; ii++ ){
if( cwarp[ii] == NULL ) continue ;
smat = CW_read_affine_warp_OLD(cwarp[ii]) ;
qmat = MAT44_MUL(smat,wmat) ; wmat = qmat ;
}
if( strcmp(prefix,"-") == 0 || strncmp(prefix,"stdout",6) == 0 ){
fp = stdout ; strcpy(fname,"stdout") ;
} else {
strcpy(fname,prefix) ;
if( strstr(fname,".1D") == NULL ) strcat(fname,".aff12.1D") ;
fp = fopen(fname,"w") ;
if( fp == NULL ) ERROR_exit("Can't open output matrix file %s",fname) ;
}
if( do_iwarp ){
qmat = MAT44_INV(wmat) ; wmat = qmat ;
}
UNLOAD_MAT44(wmat,a11,a12,a13,a14,a21,a22,a23,a24,a31,a32,a33,a34) ;
fprintf(fp,
" %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g %13.6g\n",
a11,a12,a13,a14,a21,a22,a23,a24,a31,a32,a33,a34 ) ;
if( verb && fp != stdout ) INFO_message("Wrote matrix to %s",fname) ;
if( fp != stdout ) fclose(fp) ;
exit(0) ;
}
/*** at least one nonlinear warp ==> cat all strings, use library function to read ***/
cwarp_all = (char *)calloc(sizeof(char),(ntot+NWMAX)*2) ;
for( ii=0 ; ii < nwtop ; ii++ ){
if( cwarp[ii] != NULL ){ strcat(cwarp_all,cwarp[ii]) ; strcat(cwarp_all," ") ; }
}
oset = IW3D_read_catenated_warp( cwarp_all ) ; /* process all of them at once */
if( do_iwarp ){ /* 18 Jul 2014 */
THD_3dim_dataset *qwarp ;
if( verb ) fprintf(stderr,"Applying -iwarp option") ;
qwarp = THD_nwarp_invert(oset) ;
DSET_delete(oset) ;
oset = qwarp ;
if( verb ) fprintf(stderr,"\n") ;
}
tross_Make_History( "3dNwarpCat" , argc,argv , oset ) ;
if( sname != NULL ) MCW_strncpy( oset->atlas_space , sname , THD_MAX_NAME ) ;
EDIT_dset_items( oset , ADN_prefix,prefix , ADN_none ) ;
DSET_write(oset) ; WROTE_DSET(oset) ;
/*--- run away screaming into the night, never to be seen again ---*/
INFO_message("total CPU time = %.1f sec Elapsed = %.1f\n",
COX_cpu_time() , COX_clock_time() ) ;
exit(0) ;
}
int main( int argc , char *argv[] )
{
THD_3dim_dataset *xset , *cset, *mset=NULL ;
int nopt=1 , method=PEARSON , do_autoclip=0 ;
int nvox , nvals , ii, jj, kout, kin, polort=1 ;
int ix1,jy1,kz1, ix2, jy2, kz2 ;
char *prefix = "degree_centrality" ;
byte *mask=NULL;
int nmask , abuc=1 ;
int all_source=0; /* output all source voxels 25 Jun 2010 [rickr] */
char str[32] , *cpt ;
int *imap = NULL ; MRI_vectim *xvectim ;
float (*corfun)(int,float *,float*) = NULL ;
/* djc - add 1d file output for similarity matrix */
FILE *fout1D=NULL;
/* CC - we will have two subbricks: binary and weighted centrality */
int nsubbriks = 2;
int subbrik = 0;
float * bodset;
float * wodset;
int nb_ctr = 0;
/* CC - added flags for thresholding correlations */
double thresh = 0.0;
double othresh = 0.0;
int dothresh = 0;
double sparsity = 0.0;
int dosparsity = 0;
/* variables for calculating degree centrality */
long * binaryDC = NULL;
double * weightedDC = NULL;
/* variables for histogram */
hist_node_head* histogram=NULL;
hist_node* hptr=NULL;
hist_node* pptr=NULL;
int bottom_node_idx = 0;
int totNumCor = 0;
long totPosCor = 0;
int ngoal = 0;
int nretain = 0;
float binwidth = 0.0;
int nhistnodes = 50;
/*----*/
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf(
"Usage: 3dDegreeCentrality [options] dset\n"
" Computes voxelwise weighted and binary degree centrality and\n"
" stores the result in a new 3D bucket dataset as floats to\n"
" preserve their values. Degree centrality reflects the strength and\n"
" extent of the correlation of a voxel with every other voxel in\n"
" the brain.\n\n"
" Conceptually the process involves: \n"
" 1. Calculating the correlation between voxel time series for\n"
" every pair of voxels in the brain (as determined by masking)\n"
" 2. Applying a threshold to the resulting correlations to exclude\n"
" those that might have arisen by chance, or to sparsify the\n"
" connectivity graph.\n"
" 3. At each voxel, summarizing its correlation with other voxels\n"
" in the brain, by either counting the number of voxels correlated\n"
" with the seed voxel (binary) or by summing the correlation \n"
" coefficients (weighted).\n"
" Practically the algorithm is ordered differently to optimize for\n"
" computational time and memory usage.\n\n"
" The threshold can be supplied as a correlation coefficient, \n"
" or a sparsity threshold. The sparsity threshold reflects the fraction\n"
" of connections that should be retained after the threshold has been\n"
" applied. To minimize resource consumption, using a sparsity threshold\n"
" involves a two-step procedure. In the first step, a correlation\n"
" coefficient threshold is applied to substantially reduce the number\n"
" of correlations. Next, the remaining correlations are sorted and a\n"
" threshold is calculated so that only the specified fraction of \n"
" possible correlations are above threshold. Due to ties between\n"
" correlations, the fraction of correlations that pass the sparsity\n"
" threshold might be slightly more than the number specified.\n\n"
" Regardless of the thresholding procedure employed, negative \n"
" correlations are excluded from the calculations.\n"
"\n"
"Options:\n"
" -pearson = Correlation is the normal Pearson (product moment)\n"
" correlation coefficient [default].\n"
#if 0
" -spearman = Correlation is the Spearman (rank) correlation\n"
" coefficient.\n"
" -quadrant = Correlation is the quadrant correlation coefficient.\n"
#else
" -spearman AND -quadrant are disabled at this time :-(\n"
#endif
"\n"
" -thresh r = exclude correlations <= r from calculations\n"
" -sparsity s = only use top s percent of correlations in calculations\n"
" s should be an integer between 0 and 100. Uses an\n"
" an adaptive thresholding procedure to reduce memory.\n"
" The speed of determining the adaptive threshold can\n"
" be improved by specifying an initial threshold with\n"
" the -thresh flag.\n"
"\n"
" -polort m = Remove polynomical trend of order 'm', for m=-1..3.\n"
" [default is m=1; removal is by least squares].\n"
" Using m=-1 means no detrending; this is only useful\n"
" for data/information that has been pre-processed.\n"
"\n"
" -autoclip = Clip off low-intensity regions in the dataset,\n"
" -automask = so that the correlation is only computed between\n"
" high-intensity (presumably brain) voxels. The\n"
" mask is determined the same way that 3dAutomask works.\n"
"\n"
" -mask mmm = Mask to define 'in-brain' voxels. Reducing the number\n"
" the number of voxels included in the calculation will\n"
" significantly speedup the calculation. Consider using\n"
" a mask to constrain the calculations to the grey matter\n"
" rather than the whole brain. This is also preferrable\n"
" to using -autoclip or -automask.\n"
"\n"
" -prefix p = Save output into dataset with prefix 'p', this file will\n"
" contain bricks for both 'weighted' or 'degree' centrality\n"
" [default prefix is 'deg_centrality'].\n"
"\n"
" -out1D f = Save information about the above threshold correlations to\n"
" 1D file 'f'. Each row of this file will contain:\n"
" Voxel1 Voxel2 i1 j1 k1 i2 j2 k2 Corr\n"
" Where voxel1 and voxel2 are the 1D indices of the pair of\n"
" voxels, i j k correspond to their 3D coordinates, and Corr\n"
" is the value of the correlation between the voxel time courses.\n"
"\n"
"Notes:\n"
" * The output dataset is a bucket type of floats.\n"
" * The program prints out an estimate of its memory used\n"
" when it ends. It also prints out a progress 'meter'\n"
" to keep you pacified.\n"
"\n"
"-- RWCox - 31 Jan 2002 and 16 Jul 2010\n"
"-- Cameron Craddock - 26 Sept 2015 \n"
) ;
PRINT_AFNI_OMP_USAGE("3dDegreeCentrality",NULL) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
mainENTRY("3dDegreeCentrality main"); machdep(); PRINT_VERSION("3dDegreeCentrality");
AFNI_logger("3dDegreeCentrality",argc,argv);
/*-- option processing --*/
while( nopt < argc && argv[nopt][0] == '-' ){
if( strcmp(argv[nopt],"-time") == 0 ){
abuc = 0 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-autoclip") == 0 ||
strcmp(argv[nopt],"-automask") == 0 ){
do_autoclip = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-mask") == 0 ){
mset = THD_open_dataset(argv[++nopt]);
CHECK_OPEN_ERROR(mset,argv[nopt]);
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-pearson") == 0 ){
method = PEARSON ; nopt++ ; continue ;
}
#if 0
if( strcmp(argv[nopt],"-spearman") == 0 ){
method = SPEARMAN ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-quadrant") == 0 ){
method = QUADRANT ; nopt++ ; continue ;
}
#endif
if( strcmp(argv[nopt],"-eta2") == 0 ){
method = ETA2 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-prefix") == 0 ){
prefix = strdup(argv[++nopt]) ;
if( !THD_filename_ok(prefix) ){
ERROR_exit("Illegal value after -prefix!") ;
}
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-thresh") == 0 ){
double val = (double)strtod(argv[++nopt],&cpt) ;
if( *cpt != '\0' || val >= 1.0 || val < 0.0 ){
ERROR_exit("Illegal value (%f) after -thresh!", val) ;
}
dothresh = 1;
thresh = val ; othresh = val ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-sparsity") == 0 ){
double val = (double)strtod(argv[++nopt],&cpt) ;
if( *cpt != '\0' || val > 100 || val <= 0 ){
ERROR_exit("Illegal value (%f) after -sparsity!", val) ;
}
if( val > 5.0 )
{
WARNING_message("Sparsity %3.2f%% is large and will require alot of memory and time, consider using a smaller value. ", val);
}
dosparsity = 1 ;
sparsity = val ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-polort") == 0 ){
int val = (int)strtod(argv[++nopt],&cpt) ;
if( *cpt != '\0' || val < -1 || val > 3 ){
ERROR_exit("Illegal value after -polort!") ;
}
polort = val ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-mem_stat") == 0 ){
MEM_STAT = 1 ; nopt++ ; continue ;
}
if( strncmp(argv[nopt],"-mem_profile",8) == 0 ){
MEM_PROF = 1 ; nopt++ ; continue ;
}
/* check for 1d argument */
if ( strcmp(argv[nopt],"-out1D") == 0 ){
if (!(fout1D = fopen(argv[++nopt], "w"))) {
ERROR_message("Failed to open %s for writing", argv[nopt]);
exit(1);
}
nopt++ ; continue ;
}
ERROR_exit("Illegal option: %s",argv[nopt]) ;
}
/*-- open dataset, check for legality --*/
if( nopt >= argc ) ERROR_exit("Need a dataset on command line!?") ;
xset = THD_open_dataset(argv[nopt]); CHECK_OPEN_ERROR(xset,argv[nopt]);
if( DSET_NVALS(xset) < 3 )
ERROR_exit("Input dataset %s does not have 3 or more sub-bricks!",argv[nopt]) ;
DSET_load(xset) ; CHECK_LOAD_ERROR(xset) ;
/*-- compute mask array, if desired --*/
nvox = DSET_NVOX(xset) ; nvals = DSET_NVALS(xset) ;
INC_MEM_STATS((nvox * nvals * sizeof(double)), "input dset");
PRINT_MEM_STATS("inset");
/* if a mask was specified make sure it is appropriate */
if( mset ){
if( DSET_NVOX(mset) != nvox )
ERROR_exit("Input and mask dataset differ in number of voxels!") ;
mask = THD_makemask(mset, 0, 1.0, 0.0) ;
/* update running memory statistics to reflect loading the image */
INC_MEM_STATS( mset->dblk->total_bytes, "mask dset" );
PRINT_MEM_STATS( "mset load" );
nmask = THD_countmask( nvox , mask ) ;
INC_MEM_STATS( nmask * sizeof(byte), "mask array" );
PRINT_MEM_STATS( "mask" );
INFO_message("%d voxels in -mask dataset",nmask) ;
if( nmask < 2 ) ERROR_exit("Only %d voxels in -mask, exiting...",nmask);
/* update running memory statistics to reflect loading the image */
DEC_MEM_STATS( mset->dblk->total_bytes, "mask dset" );
DSET_unload(mset) ;
PRINT_MEM_STATS( "mset unload" );
}
/* if automasking is requested, handle that now */
else if( do_autoclip ){
mask = THD_automask( xset ) ;
nmask = THD_countmask( nvox , mask ) ;
INFO_message("%d voxels survive -autoclip",nmask) ;
if( nmask < 2 ) ERROR_exit("Only %d voxels in -automask!",nmask);
}
/* otherwise we use all of the voxels in the image */
else {
nmask = nvox ;
INFO_message("computing for all %d voxels",nmask) ;
}
if( method == ETA2 && polort >= 0 )
WARNING_message("Polort for -eta2 should probably be -1...");
/* djc - 1d file out init */
if (fout1D != NULL) {
/* define affine matrix */
mat44 affine_mat = xset->daxes->ijk_to_dicom;
/* print command line statement */
fprintf(fout1D,"#Similarity matrix from command:\n#");
for(ii=0; ii<argc; ++ii) fprintf(fout1D,"%s ", argv[ii]);
/* Print affine matrix */
fprintf(fout1D,"\n");
fprintf(fout1D,"#[ ");
int mi, mj;
for(mi = 0; mi < 4; mi++) {
for(mj = 0; mj < 4; mj++) {
fprintf(fout1D, "%.6f ", affine_mat.m[mi][mj]);
}
}
fprintf(fout1D, "]\n");
/* Print image extents*/
THD_dataxes *xset_daxes = xset->daxes;
fprintf(fout1D, "#Image dimensions:\n");
fprintf(fout1D, "#[%d, %d, %d]\n",
xset_daxes->nxx, xset_daxes->nyy, xset_daxes->nzz);
/* Similarity matrix headers */
fprintf(fout1D,"#Voxel1 Voxel2 i1 j1 k1 i2 j2 k2 Corr\n");
}
/* CC calculate the total number of possible correlations, will be
usefule down the road */
totPosCor = (.5*((float)nmask))*((float)(nmask-1));
/** For the case of Pearson correlation, we make sure the **/
/** data time series have their mean removed (polort >= 0) **/
/** and are normalized, so that correlation = dot product, **/
/** and we can use function zm_THD_pearson_corr for speed. **/
switch( method ){
default:
case PEARSON: corfun = zm_THD_pearson_corr ; break ;
case ETA2: corfun = my_THD_eta_squared ; break ;
}
/*-- create vectim from input dataset --*/
INFO_message("vectim-izing input dataset") ;
/*-- CC added in mask to reduce the size of xvectim -- */
xvectim = THD_dset_to_vectim( xset , mask , 0 ) ;
if( xvectim == NULL ) ERROR_exit("Can't create vectim?!") ;
/*-- CC update our memory stats to reflect vectim -- */
INC_MEM_STATS((xvectim->nvec*sizeof(int)) +
((xvectim->nvec)*(xvectim->nvals))*sizeof(float) +
sizeof(MRI_vectim), "vectim");
PRINT_MEM_STATS( "vectim" );
/*--- CC the vectim contains a mapping between voxel index and mask index,
tap into that here to avoid duplicating memory usage ---*/
if( mask != NULL )
{
imap = xvectim->ivec;
/* --- CC free the mask */
DEC_MEM_STATS( nmask*sizeof(byte), "mask array" );
free(mask); mask=NULL;
PRINT_MEM_STATS( "mask unload" );
}
/* -- CC unloading the dataset to reduce memory usage ?? -- */
DEC_MEM_STATS((DSET_NVOX(xset) * DSET_NVALS(xset) * sizeof(double)), "input dset");
DSET_unload(xset) ;
PRINT_MEM_STATS("inset unload");
/* -- CC configure detrending --*/
if( polort < 0 && method == PEARSON ){
polort = 0; WARNING_message("Pearson correlation always uses polort >= 0");
}
if( polort >= 0 ){
for( ii=0 ; ii < xvectim->nvec ; ii++ ){ /* remove polynomial trend */
DETREND_polort(polort,nvals,VECTIM_PTR(xvectim,ii)) ;
}
}
/* -- this procedure does not change time series that have zero variance -- */
if( method == PEARSON ) THD_vectim_normalize(xvectim) ; /* L2 norm = 1 */
/* -- CC create arrays to hold degree and weighted centrality while
they are being calculated -- */
if( dosparsity == 0 )
{
if( ( binaryDC = (long*)calloc( nmask, sizeof(long) )) == NULL )
{
ERROR_message( "Could not allocate %d byte array for binary DC calculation\n",
nmask*sizeof(long));
}
/* -- update running memory estimate to reflect memory allocation */
INC_MEM_STATS( nmask*sizeof(long), "binary DC array" );
PRINT_MEM_STATS( "binaryDC" );
if( ( weightedDC = (double*)calloc( nmask, sizeof(double) )) == NULL )
{
if (binaryDC){ free(binaryDC); binaryDC = NULL; }
ERROR_message( "Could not allocate %d byte array for weighted DC calculation\n",
nmask*sizeof(double));
}
/* -- update running memory estimate to reflect memory allocation */
INC_MEM_STATS( nmask*sizeof(double), "weighted DC array" );
PRINT_MEM_STATS( "weightedDC" );
}
/* -- CC if we are using a sparsity threshold, build a histogram to calculate the
threshold */
if (dosparsity == 1)
{
/* make sure that there is a bin for correlation values that == 1.0 */
binwidth = (1.005-thresh)/nhistnodes;
/* calculate the number of correlations we wish to retain */
ngoal = nretain = (int)(((double)totPosCor)*((double)sparsity) / 100.0);
/* allocate memory for the histogram bins */
if(( histogram = (hist_node_head*)malloc(nhistnodes*sizeof(hist_node_head))) == NULL )
{
/* if the allocation fails, free all memory and exit */
if (binaryDC){ free(binaryDC); binaryDC = NULL; }
if (weightedDC){ free(weightedDC); weightedDC = NULL; }
ERROR_message( "Could not allocate %d byte array for histogram\n",
nhistnodes*sizeof(hist_node_head));
}
else {
/* -- update running memory estimate to reflect memory allocation */
INC_MEM_STATS( nhistnodes*sizeof(hist_node_head), "hist bins" );
PRINT_MEM_STATS( "hist1" );
}
/* initialize history bins */
for( kout = 0; kout < nhistnodes; kout++ )
{
histogram[ kout ].bin_low = thresh+kout*binwidth;
histogram[ kout ].bin_high = histogram[ kout ].bin_low+binwidth;
histogram[ kout ].nbin = 0;
histogram[ kout ].nodes = NULL;
/*INFO_message("Hist bin %d [%3.3f, %3.3f) [%d, %p]\n",
kout, histogram[ kout ].bin_low, histogram[ kout ].bin_high,
histogram[ kout ].nbin, histogram[ kout ].nodes );*/
}
}
/*-- tell the user what we are about to do --*/
if (dosparsity == 0 )
{
INFO_message( "Calculating degree centrality with threshold = %f.\n", thresh);
}
else
{
INFO_message( "Calculating degree centrality with threshold = %f and sparsity = %3.2f%% (%d)\n",
thresh, sparsity, nretain);
}
/*---------- loop over mask voxels, correlate ----------*/
AFNI_OMP_START ;
#pragma omp parallel if( nmask > 999 )
{
int lii,ljj,lin,lout,ithr,nthr,vstep,vii ;
float *xsar , *ysar ;
hist_node* new_node = NULL ;
hist_node* tptr = NULL ;
hist_node* rptr = NULL ;
int new_node_idx = 0;
double car = 0.0 ;
/*-- get information about who we are --*/
#ifdef USE_OMP
ithr = omp_get_thread_num() ;
nthr = omp_get_num_threads() ;
if( ithr == 0 ) INFO_message("%d OpenMP threads started",nthr) ;
#else
ithr = 0 ; nthr = 1 ;
#endif
/*-- For the progress tracker, we want to print out 50 numbers,
figure out a number of loop iterations that will make this easy */
vstep = (int)( nmask / (nthr*50.0f) + 0.901f ) ; vii = 0 ;
if((MEM_STAT==0) && (ithr == 0 )) fprintf(stderr,"Looping:") ;
#pragma omp for schedule(static, 1)
for( lout=0 ; lout < xvectim->nvec ; lout++ ){ /*----- outer voxel loop -----*/
if( ithr == 0 && vstep > 2 ) /* allow small dsets 16 Jun 2011 [rickr] */
{ vii++ ; if( vii%vstep == vstep/2 && MEM_STAT == 0 ) vstep_print(); }
/* get ref time series from this voxel */
xsar = VECTIM_PTR(xvectim,lout) ;
/* try to make calculation more efficient by only calculating the unique
correlations */
for( lin=(lout+1) ; lin < xvectim->nvec ; lin++ ){ /*----- inner loop over voxels -----*/
/* extract the voxel time series */
ysar = VECTIM_PTR(xvectim,lin) ;
/* now correlate the time series */
car = (double)(corfun(nvals,xsar,ysar)) ;
if ( car <= thresh )
{
continue ;
}
/* update degree centrality values, hopefully the pragma
will handle mutual exclusion */
#pragma omp critical(dataupdate)
{
/* if the correlation is less than threshold, ignore it */
if ( car > thresh )
{
totNumCor += 1;
if ( dosparsity == 0 )
{
binaryDC[lout] += 1; binaryDC[lin] += 1;
weightedDC[lout] += car; weightedDC[lin] += car;
/* print correlation out to the 1D file */
if ( fout1D != NULL )
{
/* determine the i,j,k coords */
ix1 = DSET_index_to_ix(xset,lii) ;
jy1 = DSET_index_to_jy(xset,lii) ;
kz1 = DSET_index_to_kz(xset,lii) ;
ix2 = DSET_index_to_ix(xset,ljj) ;
jy2 = DSET_index_to_jy(xset,ljj) ;
kz2 = DSET_index_to_kz(xset,ljj) ;
/* add source, dest, correlation to 1D file */
fprintf(fout1D, "%d %d %d %d %d %d %d %d %.6f\n",
lii, ljj, ix1, jy1, kz1, ix2, jy2, kz2, car);
}
}
else
{
/* determine the index in the histogram to add the node */
new_node_idx = (int)floor((double)(car-othresh)/(double)binwidth);
if ((new_node_idx > nhistnodes) || (new_node_idx < bottom_node_idx))
{
/* this error should indicate a programming error and should not happen */
WARNING_message("Node index %d is out of range [%d,%d)!",new_node_idx,
bottom_node_idx, nhistnodes);
}
else
{
/* create a node to add to the histogram */
new_node = (hist_node*)calloc(1,sizeof(hist_node));
if( new_node == NULL )
{
/* allocate memory for this node, rather than fiddling with
error handling here, lets just move on */
WARNING_message("Could not allocate a new node!");
}
else
{
/* populate histogram node */
new_node->i = lout;
new_node->j = lin;
new_node->corr = car;
new_node->next = NULL;
/* -- update running memory estimate to reflect memory allocation */
INC_MEM_STATS( sizeof(hist_node), "hist nodes" );
if ((totNumCor % (1024*1024)) == 0) PRINT_MEM_STATS( "hist nodes" );
/* populate histogram */
new_node->next = histogram[new_node_idx].nodes;
histogram[new_node_idx].nodes = new_node;
histogram[new_node_idx].nbin++;
/* see if there are enough correlations in the histogram
for the sparsity */
if ((totNumCor - histogram[bottom_node_idx].nbin) > nretain)
{
/* delete the list of nodes */
rptr = histogram[bottom_node_idx].nodes;
while(rptr != NULL)
{
tptr = rptr;
rptr = rptr->next;
/* check that the ptr is not null before freeing it*/
if(tptr!= NULL)
{
DEC_MEM_STATS( sizeof(hist_node), "hist nodes" );
free(tptr);
}
}
PRINT_MEM_STATS( "unloaded hist nodes - thresh increase" );
histogram[bottom_node_idx].nodes = NULL;
totNumCor -= histogram[bottom_node_idx].nbin;
histogram[bottom_node_idx].nbin=0;
/* get the new threshold */
thresh = (double)histogram[++bottom_node_idx].bin_low;
if(MEM_STAT == 1) INFO_message("Increasing threshold to %3.2f (%d)\n",
thresh,bottom_node_idx);
}
} /* else, newptr != NULL */
} /* else, new_node_idx in range */
} /* else, do_sparsity == 1 */
} /* car > thresh */
} /* this is the end of the critical section */
} /* end of inner loop over voxels */
} /* end of outer loop over ref voxels */
if( ithr == 0 ) fprintf(stderr,".\n") ;
} /* end OpenMP */
AFNI_OMP_END ;
/* update the user so that they know what we are up to */
INFO_message ("AFNI_OMP finished\n");
INFO_message ("Found %d (%3.2f%%) correlations above threshold (%f)\n",
totNumCor, 100.0*((float)totNumCor)/((float)totPosCor), thresh);
/*---------- Finish up ---------*/
/*if( dosparsity == 1 )
{
for( kout = 0; kout < nhistnodes; kout++ )
{
INFO_message("Hist bin %d [%3.3f, %3.3f) [%d, %p]\n",
kout, histogram[ kout ].bin_low, histogram[ kout ].bin_high,
histogram[ kout ].nbin, histogram[ kout ].nodes );
}
}*/
/*-- create output dataset --*/
cset = EDIT_empty_copy( xset ) ;
/*-- configure the output dataset */
if( abuc ){
EDIT_dset_items( cset ,
ADN_prefix , prefix ,
ADN_nvals , nsubbriks , /* 2 subbricks, degree and weighted centrality */
ADN_ntt , 0 , /* no time axis */
ADN_type , HEAD_ANAT_TYPE ,
ADN_func_type , ANAT_BUCK_TYPE ,
ADN_datum_all , MRI_float ,
ADN_none ) ;
} else {
EDIT_dset_items( cset ,
ADN_prefix , prefix ,
ADN_nvals , nsubbriks , /* 2 subbricks, degree and weighted centrality */
ADN_ntt , nsubbriks , /* num times */
ADN_ttdel , 1.0 , /* fake TR */
ADN_nsl , 0 , /* no slice offsets */
ADN_type , HEAD_ANAT_TYPE ,
ADN_func_type , ANAT_EPI_TYPE ,
ADN_datum_all , MRI_float ,
ADN_none ) ;
}
/* add history information to the hearder */
tross_Make_History( "3dDegreeCentrality" , argc,argv , cset ) ;
ININFO_message("creating output dataset in memory") ;
/* -- Configure the subbriks: Binary Degree Centrality */
subbrik = 0;
EDIT_BRICK_TO_NOSTAT(cset,subbrik) ; /* stat params */
/* CC this sets the subbrik scaling factor, which we will probably want
to do again after we calculate the voxel values */
EDIT_BRICK_FACTOR(cset,subbrik,1.0) ; /* scale factor */
sprintf(str,"Binary Degree Centrality") ;
EDIT_BRICK_LABEL(cset,subbrik,str) ;
EDIT_substitute_brick(cset,subbrik,MRI_float,NULL) ; /* make array */
/* copy measure data into the subbrik */
bodset = DSET_ARRAY(cset,subbrik);
/* -- Configure the subbriks: Weighted Degree Centrality */
subbrik = 1;
EDIT_BRICK_TO_NOSTAT(cset,subbrik) ; /* stat params */
/* CC this sets the subbrik scaling factor, which we will probably want
to do again after we calculate the voxel values */
EDIT_BRICK_FACTOR(cset,subbrik,1.0) ; /* scale factor */
sprintf(str,"Weighted Degree Centrality") ;
EDIT_BRICK_LABEL(cset,subbrik,str) ;
EDIT_substitute_brick(cset,subbrik,MRI_float,NULL) ; /* make array */
/* copy measure data into the subbrik */
wodset = DSET_ARRAY(cset,subbrik);
/* increment memory stats */
INC_MEM_STATS( (DSET_NVOX(cset)*DSET_NVALS(cset)*sizeof(float)), "output dset");
PRINT_MEM_STATS( "outset" );
/* pull the values out of the histogram */
if( dosparsity == 0 )
{
for( kout = 0; kout < nmask; kout++ )
{
if ( imap != NULL )
{
ii = imap[kout] ; /* ii= source voxel (we know that ii is in the mask) */
}
else
{
ii = kout ;
}
if( ii >= DSET_NVOX(cset) )
{
WARNING_message("Avoiding bodset, wodset overflow %d > %d (%s,%d)\n",
ii,DSET_NVOX(cset),__FILE__,__LINE__ );
}
else
{
bodset[ ii ] = (float)(binaryDC[kout]);
wodset[ ii ] = (float)(weightedDC[kout]);
}
}
/* we are done with this memory, and can kill it now*/
if(binaryDC)
{
free(binaryDC);
binaryDC=NULL;
/* -- update running memory estimate to reflect memory allocation */
DEC_MEM_STATS( nmask*sizeof(long), "binary DC array" );
PRINT_MEM_STATS( "binaryDC" );
}
if(weightedDC)
{
free(weightedDC);
weightedDC=NULL;
/* -- update running memory estimate to reflect memory allocation */
DEC_MEM_STATS( nmask*sizeof(double), "weighted DC array" );
PRINT_MEM_STATS( "weightedDC" );
}
}
else
{
/* add in the values from the histogram, this is a two stage procedure:
at first we add in values a whole bin at the time until we get to a point
where we need to add in a partial bin, then we create a new histogram
to sort the values in the bin and then add those bins at a time */
kout = nhistnodes - 1;
while (( histogram[kout].nbin < nretain ) && ( kout >= 0 ))
{
hptr = pptr = histogram[kout].nodes;
while( hptr != NULL )
{
/* determine the indices corresponding to this node */
if ( imap != NULL )
{
ii = imap[hptr->i] ; /* ii= source voxel (we know that ii is in the mask) */
}
else
{
ii = hptr->i ;
}
if ( imap != NULL )
{
jj = imap[hptr->j] ; /* ii= source voxel (we know that ii is in the mask) */
}
else
{
jj = hptr->j ;
}
/* add in the values */
if(( ii >= DSET_NVOX(cset) ) || ( jj >= DSET_NVOX(cset)))
{
if( ii >= DSET_NVOX(cset))
{
WARNING_message("Avoiding bodset, wodset overflow (ii) %d > %d\n (%s,%d)\n",
ii,DSET_NVOX(cset),__FILE__,__LINE__ );
}
if( jj >= DSET_NVOX(cset))
{
WARNING_message("Avoiding bodset, wodset overflow (jj) %d > %d\n (%s,%d)\n",
jj,DSET_NVOX(cset),__FILE__,__LINE__ );
}
}
else
{
bodset[ ii ] += 1.0 ;
wodset[ ii ] += (float)(hptr->corr);
bodset[ jj ] += 1.0 ;
wodset[ jj ] += (float)(hptr->corr);
}
if( fout1D != NULL )
{
/* add source, dest, correlation to 1D file */
ix1 = DSET_index_to_ix(cset,ii) ;
jy1 = DSET_index_to_jy(cset,ii) ;
kz1 = DSET_index_to_kz(cset,ii) ;
ix2 = DSET_index_to_ix(cset,jj) ;
jy2 = DSET_index_to_jy(cset,jj) ;
kz2 = DSET_index_to_kz(cset,jj) ;
fprintf(fout1D, "%d %d %d %d %d %d %d %d %.6f\n",
ii, jj, ix1, jy1, kz1, ix2, jy2, kz2, (float)(hptr->corr));
}
/* increment node pointers */
pptr = hptr;
hptr = hptr->next;
/* delete the node */
if(pptr)
{
/* -- update running memory estimate to reflect memory allocation */
DEC_MEM_STATS(sizeof( hist_node ), "hist nodes" );
/* free the mem */
free(pptr);
pptr=NULL;
}
}
/* decrement the number of correlations we wish to retain */
nretain -= histogram[kout].nbin;
histogram[kout].nodes = NULL;
/* go on to the next bin */
kout--;
}
PRINT_MEM_STATS( "hist1 bins free - inc into output" );
/* if we haven't used all of the correlations that are available, go through and
add a subset of the voxels from the remaining bin */
if(( nretain > 0 ) && (kout >= 0))
{
hist_node_head* histogram2 = NULL;
hist_node_head* histogram2_save = NULL;
int h2nbins = 100;
float h2binwidth = 0.0;
int h2ndx=0;
h2binwidth = (((1.0+binwidth/((float)h2nbins))*histogram[kout].bin_high) - histogram[kout].bin_low) /
((float)h2nbins);
/* allocate the bins */
if(( histogram2 = (hist_node_head*)malloc(h2nbins*sizeof(hist_node_head))) == NULL )
{
if (binaryDC){ free(binaryDC); binaryDC = NULL; }
if (weightedDC){ free(weightedDC); weightedDC = NULL; }
if (histogram){ histogram = free_histogram(histogram, nhistnodes); }
ERROR_message( "Could not allocate %d byte array for histogram2\n",
h2nbins*sizeof(hist_node_head));
}
else {
/* -- update running memory estimate to reflect memory allocation */
histogram2_save = histogram2;
INC_MEM_STATS(( h2nbins*sizeof(hist_node_head )), "hist bins");
PRINT_MEM_STATS( "hist2" );
}
/* initiatize the bins */
for( kin = 0; kin < h2nbins; kin++ )
{
histogram2[ kin ].bin_low = histogram[kout].bin_low + kin*h2binwidth;
histogram2[ kin ].bin_high = histogram2[ kin ].bin_low + h2binwidth;
histogram2[ kin ].nbin = 0;
histogram2[ kin ].nodes = NULL;
/*INFO_message("Hist2 bin %d [%3.3f, %3.3f) [%d, %p]\n",
kin, histogram2[ kin ].bin_low, histogram2[ kin ].bin_high,
histogram2[ kin ].nbin, histogram2[ kin ].nodes );*/
}
/* move correlations from histogram to histgram2 */
INFO_message ("Adding %d nodes from histogram to histogram2",histogram[kout].nbin);
while ( histogram[kout].nodes != NULL )
{
hptr = histogram[kout].nodes;
h2ndx = (int)floor((double)(hptr->corr - histogram[kout].bin_low)/(double)h2binwidth);
if(( h2ndx < h2nbins ) && ( h2ndx >= 0 ))
{
histogram[kout].nodes = hptr->next;
hptr->next = histogram2[h2ndx].nodes;
histogram2[h2ndx].nodes = hptr;
histogram2[h2ndx].nbin++;
histogram[kout].nbin--;
}
else
{
WARNING_message("h2ndx %d is not in range [0,%d) :: %.10f,%.10f\n",h2ndx,h2nbins,hptr->corr, histogram[kout].bin_low);
}
}
/* free the remainder of histogram */
{
int nbins_rem = 0;
for(ii = 0; ii < nhistnodes; ii++) nbins_rem+=histogram[ii].nbin;
histogram = free_histogram(histogram, nhistnodes);
PRINT_MEM_STATS( "free remainder of histogram1" );
}
kin = h2nbins - 1;
while (( nretain > 0 ) && ( kin >= 0 ))
{
hptr = pptr = histogram2[kin].nodes;
while( hptr != NULL )
{
/* determine the indices corresponding to this node */
if ( imap != NULL )
{
ii = imap[hptr->i] ;
}
else
{
ii = hptr->i ;
}
if ( imap != NULL )
{
jj = imap[hptr->j] ;
}
else
{
jj = hptr->j ;
}
/* add in the values */
if(( ii >= DSET_NVOX(cset) ) || ( jj >= DSET_NVOX(cset)))
{
if( ii >= DSET_NVOX(cset))
{
WARNING_message("Avoiding bodset, wodset overflow (ii) %d > %d\n (%s,%d)\n",
ii,DSET_NVOX(cset),__FILE__,__LINE__ );
}
if( jj >= DSET_NVOX(cset))
{
WARNING_message("Avoiding bodset, wodset overflow (jj) %d > %d\n (%s,%d)\n",
jj,DSET_NVOX(cset),__FILE__,__LINE__ );
}
}
else
{
bodset[ ii ] += 1.0 ;
wodset[ ii ] += (float)(hptr->corr);
bodset[ jj ] += 1.0 ;
wodset[ jj ] += (float)(hptr->corr);
}
if( fout1D != NULL )
{
/* add source, dest, correlation to 1D file */
ix1 = DSET_index_to_ix(cset,ii) ;
jy1 = DSET_index_to_jy(cset,ii) ;
kz1 = DSET_index_to_kz(cset,ii) ;
ix2 = DSET_index_to_ix(cset,jj) ;
jy2 = DSET_index_to_jy(cset,jj) ;
kz2 = DSET_index_to_kz(cset,jj) ;
fprintf(fout1D, "%d %d %d %d %d %d %d %d %.6f\n",
ii, jj, ix1, jy1, kz1, ix2, jy2, kz2, (float)(hptr->corr));
}
/* increment node pointers */
pptr = hptr;
hptr = hptr->next;
/* delete the node */
if(pptr)
{
free(pptr);
DEC_MEM_STATS(( sizeof(hist_node) ), "hist nodes");
pptr=NULL;
}
}
/* decrement the number of correlations we wish to retain */
nretain -= histogram2[kin].nbin;
histogram2[kin].nodes = NULL;
/* go on to the next bin */
kin--;
}
PRINT_MEM_STATS("hist2 nodes free - incorporated into output");
/* we are finished with histogram2 */
{
histogram2 = free_histogram(histogram2, h2nbins);
/* -- update running memory estimate to reflect memory allocation */
PRINT_MEM_STATS( "free hist2" );
}
if (nretain < 0 )
{
WARNING_message( "Went over sparsity goal %d by %d, with a resolution of %f",
ngoal, -1*nretain, h2binwidth);
}
}
if (nretain > 0 )
{
WARNING_message( "Was not able to meet goal of %d (%3.2f%%) correlations, %d (%3.2f%%) correlations passed the threshold of %3.2f, maybe you need to change the threshold or the desired sparsity?",
ngoal, 100.0*((float)ngoal)/((float)totPosCor), totNumCor, 100.0*((float)totNumCor)/((float)totPosCor), thresh);
}
}
INFO_message("Done..\n") ;
/* update running memory statistics to reflect freeing the vectim */
DEC_MEM_STATS(((xvectim->nvec*sizeof(int)) +
((xvectim->nvec)*(xvectim->nvals))*sizeof(float) +
sizeof(MRI_vectim)), "vectim");
/* toss some trash */
VECTIM_destroy(xvectim) ;
DSET_delete(xset) ;
if(fout1D!=NULL)fclose(fout1D);
PRINT_MEM_STATS( "vectim unload" );
if (weightedDC) free(weightedDC) ; weightedDC = NULL;
if (binaryDC) free(binaryDC) ; binaryDC = NULL;
/* finito */
INFO_message("Writing output dataset to disk [%s bytes]",
commaized_integer_string(cset->dblk->total_bytes)) ;
/* write the dataset */
DSET_write(cset) ;
WROTE_DSET(cset) ;
/* increment our memory stats, since we are relying on the header for this
information, we update the stats before actually freeing the memory */
DEC_MEM_STATS( (DSET_NVOX(cset)*DSET_NVALS(cset)*sizeof(float)), "output dset");
/* free up the output dataset memory */
DSET_unload(cset) ;
DSET_delete(cset) ;
/* force a print */
MEM_STAT = 1;
PRINT_MEM_STATS( "Fin" );
exit(0) ;
}
int main( int argc , char *argv[] )
{
int iarg=1 , verb=0 , interp_code=MRI_QUINTIC , ainterp_code=-666 ;
char *expr ; int nexpr , narg ;
THD_3dim_dataset *oset ;
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcasecmp(argv[1],"-help") == 0 ) NWC_help() ;
mainENTRY("3dNwarpCalc"); machdep();
AFNI_logger("3dNwarpCalc",argc,argv);
PRINT_VERSION("3dNwarpCalc"); AUTHOR("Bob the Warped");
(void)COX_clock_time() ;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcasecmp(argv[iarg],"-NN") == 0 || strncasecmp(argv[iarg],"-nearest",6) == 0 ){
WARNING_message("NN interpolation not legal here -- switched to linear") ;
interp_code = MRI_LINEAR ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-linear",4)==0 || strncasecmp(argv[iarg],"-trilinear",6)==0 ){
interp_code = MRI_LINEAR ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-cubic",4)==0 || strncasecmp(argv[iarg],"-tricubic",6)==0 ){
WARNING_message("cubic interplation not legal here -- switched to quintic") ;
interp_code = MRI_QUINTIC ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-quintic",4)==0 || strncasecmp(argv[iarg],"-triquintic",6)==0 ){
interp_code = MRI_QUINTIC ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-wsinc",5) == 0 ){
interp_code = MRI_WSINC5 ; iarg++ ; continue ;
}
if( strncasecmp(argv[iarg],"-interp",5)==0 ){
char *inam ;
if( ++iarg >= argc ) ERROR_exit("no argument after '%s' :-(",argv[iarg-1]) ;
inam = argv[iarg] ; if( *inam == '-' ) inam++ ;
if( strcasecmp(inam,"NN")==0 || strncasecmp(inam,"nearest",5)==0 ){
WARNING_message("NN interpolation not legal here -- changed to linear") ;
interp_code = MRI_LINEAR ;
} else if( strncasecmp(inam,"linear",3)==0 || strncasecmp(inam,"trilinear",5)==0 ){
interp_code = MRI_LINEAR ;
} else if( strncasecmp(inam,"cubic",3)==0 || strncasecmp(inam,"tricubic",5)==0 ){
WARNING_message("cubic interplation not legal here -- changed to quintic") ;
interp_code = MRI_QUINTIC ;
} else if( strncasecmp(inam,"quintic",3)==0 || strncasecmp(inam,"triquintic",5)==0 ){
interp_code = MRI_QUINTIC ;
} else if( strncasecmp(inam,"wsinc",4)==0 ){
interp_code = MRI_WSINC5 ;
} else {
ERROR_exit("Unknown code '%s' after '%s' :-(",argv[iarg],argv[iarg-1]) ;
}
iarg++ ; continue ;
}
/*---------------*/
if( strncasecmp(argv[iarg],"-ainterp",6)==0 ){
char *inam ;
if( ++iarg >= argc ) ERROR_exit("no argument after '%s' :-(",argv[iarg-1]) ;
inam = argv[iarg] ; if( *inam == '-' ) inam++ ;
if( strcasecmp(inam,"NN")==0 || strncasecmp(inam,"nearest",5)==0 ){
ainterp_code = MRI_NN ;
} else if( strncasecmp(inam,"linear",3)==0 || strncasecmp(inam,"trilinear",5)==0 ){
ainterp_code = MRI_LINEAR ;
} else if( strncasecmp(inam,"cubic",3)==0 || strncasecmp(inam,"tricubic",5)==0 ){
ainterp_code = MRI_CUBIC ;
} else if( strncasecmp(inam,"quintic",3)==0 || strncasecmp(inam,"triquintic",5)==0 ){
ainterp_code = MRI_QUINTIC ;
} else if( strncasecmp(inam,"wsinc",4)==0 ){
ainterp_code = MRI_WSINC5 ;
} else {
ERROR_exit("Unknown code '%s' after '%s' :-(",argv[iarg],argv[iarg-1]) ;
}
iarg++ ; continue ;
}
/*---------------*/
if( strcasecmp(argv[iarg],"-verb") == 0 ){
verb++ ; iarg++ ; continue ;
}
/*---------------*/
ERROR_message("Bizarre and Unknown option '%s' :-(",argv[iarg]) ;
suggest_best_prog_option(argv[0],argv[iarg]) ;
exit(1) ;
}
if( iarg >= argc ) ERROR_exit("No command line expression :-(") ;
/*--- Assemble all remaining args into the expression ---*/
expr = strdup(argv[iarg++]) ;
for( ; iarg < argc ; iarg++ ){
nexpr = strlen(expr) ;
narg = strlen(argv[iarg]) ; if( narg == 0 ) continue ;
expr = (char *)realloc( expr , sizeof(char)*(nexpr+narg+4) ) ;
strcat(expr," ") ; strcat(expr,argv[iarg]) ;
}
if( ainterp_code < 0 ) ainterp_code = interp_code ;
/*--- All the work is done herein ---*/
NwarpCalcRPN_verb(verb) ;
oset = NwarpCalcRPN( expr , NULL , interp_code , ainterp_code ) ;
/*--- run away screaming into the night, never to be seen again ---*/
free(expr) ; if( oset != NULL ) DSET_delete(oset) ;
INFO_message("total CPU time = %.1f sec Elapsed = %.1f\n",
COX_cpu_time() , COX_clock_time() ) ;
exit(0) ;
}
int main( int argc , char * argv[] )
{
int do_norm=0 , qdet=2 , have_freq=0 , do_automask=0 ;
float dt=0.0f , fbot=0.0f,ftop=999999.9f , blur=0.0f ;
MRI_IMARR *ortar=NULL ; MRI_IMAGE *ortim=NULL ;
THD_3dim_dataset **ortset=NULL ; int nortset=0 ;
THD_3dim_dataset *inset=NULL , *outset ;
char *prefix="bandpass" ;
byte *mask=NULL ;
int mask_nx=0,mask_ny=0,mask_nz=0,nmask , verb=1 ,
nx,ny,nz,nvox , nfft=0 , kk ;
float **vec , **ort=NULL ; int nort=0 , vv , nopt , ntime ;
MRI_vectim *mrv ;
float pvrad=0.0f ; int nosat=0 ;
int do_despike=0 ;
/*-- help? --*/
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf(
"\n"
"** NOTA BENE: For the purpose of preparing resting-state FMRI datasets **\n"
"** for analysis (e.g., with 3dGroupInCorr), this program is now mostly **\n"
"** superseded by the afni_proc.py script. See the 'afni_proc.py -help' **\n"
"** section 'Resting state analysis (modern)' to get our current rs-FMRI **\n"
"** pre-processing recommended sequence of steps. -- RW Cox, et alii. **\n"
"\n"
"Usage: 3dBandpass [options] fbot ftop dataset\n"
"\n"
"* One function of this program is to prepare datasets for input\n"
" to 3dSetupGroupInCorr. Other uses are left to your imagination.\n"
"\n"
"* 'dataset' is a 3D+time sequence of volumes\n"
" ++ This must be a single imaging run -- that is, no discontinuities\n"
" in time from 3dTcat-ing multiple datasets together.\n"
"\n"
"* fbot = lowest frequency in the passband, in Hz\n"
" ++ fbot can be 0 if you want to do a lowpass filter only;\n"
" HOWEVER, the mean and Nyquist freq are always removed.\n"
"\n"
"* ftop = highest frequency in the passband (must be > fbot)\n"
" ++ if ftop > Nyquist freq, then it's a highpass filter only.\n"
"\n"
"* Set fbot=0 and ftop=99999 to do an 'allpass' filter.\n"
" ++ Except for removal of the 0 and Nyquist frequencies, that is.\n"
"\n"
"* You cannot construct a 'notch' filter with this program!\n"
" ++ You could use 3dBandpass followed by 3dcalc to get the same effect.\n"
" ++ If you are understand what you are doing, that is.\n"
" ++ Of course, that is the AFNI way -- if you don't want to\n"
" understand what you are doing, use Some other PrograM, and\n"
" you can still get Fine StatisticaL maps.\n"
"\n"
"* 3dBandpass will fail if fbot and ftop are too close for comfort.\n"
" ++ Which means closer than one frequency grid step df,\n"
" where df = 1 / (nfft * dt) [of course]\n"
"\n"
"* The actual FFT length used will be printed, and may be larger\n"
" than the input time series length for the sake of efficiency.\n"
" ++ The program will use a power-of-2, possibly multiplied by\n"
" a power of 3 and/or 5 (up to and including the 3rd power of\n"
" each of these: 3, 9, 27, and 5, 25, 125).\n"
"\n"
"* Note that the results of combining 3dDetrend and 3dBandpass will\n"
" depend on the order in which you run these programs. That's why\n"
" 3dBandpass has the '-ort' and '-dsort' options, so that the\n"
" time series filtering can be done properly, in one place.\n"
"\n"
"* The output dataset is stored in float format.\n"
"\n"
"* The order of processing steps is the following (most are optional):\n"
" (0) Check time series for initial transients [does not alter data]\n"
" (1) Despiking of each time series\n"
" (2) Removal of a constant+linear+quadratic trend in each time series\n"
" (3) Bandpass of data time series\n"
" (4) Bandpass of -ort time series, then detrending of data\n"
" with respect to the -ort time series\n"
" (5) Bandpass and de-orting of the -dsort dataset,\n"
" then detrending of the data with respect to -dsort\n"
" (6) Blurring inside the mask [might be slow]\n"
" (7) Local PV calculation [WILL be slow!]\n"
" (8) L2 normalization [will be fast.]\n"
"\n"
"--------\n"
"OPTIONS:\n"
"--------\n"
" -despike = Despike each time series before other processing.\n"
" ++ Hopefully, you don't actually need to do this,\n"
" which is why it is optional.\n"
" -ort f.1D = Also orthogonalize input to columns in f.1D\n"
" ++ Multiple '-ort' options are allowed.\n"
" -dsort fset = Orthogonalize each voxel to the corresponding\n"
" voxel time series in dataset 'fset', which must\n"
" have the same spatial and temporal grid structure\n"
" as the main input dataset.\n"
" ++ At present, only one '-dsort' option is allowed.\n"
" -nodetrend = Skip the quadratic detrending of the input that\n"
" occurs before the FFT-based bandpassing.\n"
" ++ You would only want to do this if the dataset\n"
" had been detrended already in some other program.\n"
" -dt dd = set time step to 'dd' sec [default=from dataset header]\n"
" -nfft N = set the FFT length to 'N' [must be a legal value]\n"
" -norm = Make all output time series have L2 norm = 1\n"
" ++ i.e., sum of squares = 1\n"
" -mask mset = Mask dataset\n"
" -automask = Create a mask from the input dataset\n"
" -blur fff = Blur (inside the mask only) with a filter\n"
" width (FWHM) of 'fff' millimeters.\n"
" -localPV rrr = Replace each vector by the local Principal Vector\n"
" (AKA first singular vector) from a neighborhood\n"
" of radius 'rrr' millimiters.\n"
" ++ Note that the PV time series is L2 normalized.\n"
" ++ This option is mostly for Bob Cox to have fun with.\n"
"\n"
" -input dataset = Alternative way to specify input dataset.\n"
" -band fbot ftop = Alternative way to specify passband frequencies.\n"
"\n"
" -prefix ppp = Set prefix name of output dataset.\n"
" -quiet = Turn off the fun and informative messages. (Why?)\n"
"\n"
" -notrans = Don't check for initial positive transients in the data:\n"
" *OR* ++ The test is a little slow, so skipping it is OK,\n"
" -nosat if you KNOW the data time series are transient-free.\n"
" ++ Or set AFNI_SKIP_SATCHECK to YES.\n"
" ++ Initial transients won't be handled well by the\n"
" bandpassing algorithm, and in addition may seriously\n"
" contaminate any further processing, such as inter-voxel\n"
" correlations via InstaCorr.\n"
" ++ No other tests are made [yet] for non-stationary behavior\n"
" in the time series data.\n"
) ;
PRINT_AFNI_OMP_USAGE(
"3dBandpass" ,
"* At present, the only part of 3dBandpass that is parallelized is the\n"
" '-blur' option, which processes each sub-brick independently.\n"
) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
/*-- startup --*/
mainENTRY("3dBandpass"); machdep();
AFNI_logger("3dBandpass",argc,argv);
PRINT_VERSION("3dBandpass"); AUTHOR("RW Cox");
nosat = AFNI_yesenv("AFNI_SKIP_SATCHECK") ;
nopt = 1 ;
while( nopt < argc && argv[nopt][0] == '-' ){
if( strcmp(argv[nopt],"-despike") == 0 ){ /* 08 Oct 2010 */
do_despike++ ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-nfft") == 0 ){
int nnup ;
if( ++nopt >= argc ) ERROR_exit("need an argument after -nfft!") ;
nfft = (int)strtod(argv[nopt],NULL) ;
nnup = csfft_nextup_even(nfft) ;
if( nfft < 16 || nfft != nnup )
ERROR_exit("value %d after -nfft is illegal! Next legal value = %d",nfft,nnup) ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-blur") == 0 ){
if( ++nopt >= argc ) ERROR_exit("need an argument after -blur!") ;
blur = strtod(argv[nopt],NULL) ;
if( blur <= 0.0f ) WARNING_message("non-positive blur?!") ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-localPV") == 0 ){
if( ++nopt >= argc ) ERROR_exit("need an argument after -localpv!") ;
pvrad = strtod(argv[nopt],NULL) ;
if( pvrad <= 0.0f ) WARNING_message("non-positive -localpv?!") ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-prefix") == 0 ){
if( ++nopt >= argc ) ERROR_exit("need an argument after -prefix!") ;
prefix = strdup(argv[nopt]) ;
if( !THD_filename_ok(prefix) ) ERROR_exit("bad -prefix option!") ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-automask") == 0 ){
if( mask != NULL ) ERROR_exit("Can't use -mask AND -automask!") ;
do_automask = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-mask") == 0 ){
THD_3dim_dataset *mset ;
if( ++nopt >= argc ) ERROR_exit("Need argument after '-mask'") ;
if( mask != NULL || do_automask ) ERROR_exit("Can't have two mask inputs") ;
mset = THD_open_dataset( argv[nopt] ) ;
CHECK_OPEN_ERROR(mset,argv[nopt]) ;
DSET_load(mset) ; CHECK_LOAD_ERROR(mset) ;
mask_nx = DSET_NX(mset); mask_ny = DSET_NY(mset); mask_nz = DSET_NZ(mset);
mask = THD_makemask( mset , 0 , 0.5f, 0.0f ) ; DSET_delete(mset) ;
if( mask == NULL ) ERROR_exit("Can't make mask from dataset '%s'",argv[nopt]) ;
nmask = THD_countmask( mask_nx*mask_ny*mask_nz , mask ) ;
if( verb ) INFO_message("Number of voxels in mask = %d",nmask) ;
if( nmask < 1 ) ERROR_exit("Mask is too small to process") ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-norm") == 0 ){
do_norm = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-quiet") == 0 ){
verb = 0 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-notrans") == 0 || strcmp(argv[nopt],"-nosat") == 0 ){
nosat = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-ort") == 0 ){
if( ++nopt >= argc ) ERROR_exit("need an argument after -ort!") ;
if( ortar == NULL ) INIT_IMARR(ortar) ;
ortim = mri_read_1D( argv[nopt] ) ;
if( ortim == NULL ) ERROR_exit("can't read from -ort '%s'",argv[nopt]) ;
mri_add_name(argv[nopt],ortim) ;
ADDTO_IMARR(ortar,ortim) ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-dsort") == 0 ){
THD_3dim_dataset *qset ;
if( ++nopt >= argc ) ERROR_exit("need an argument after -dsort!") ;
if( nortset > 0 ) ERROR_exit("only 1 -dsort option is allowed!") ;
qset = THD_open_dataset(argv[nopt]) ;
CHECK_OPEN_ERROR(qset,argv[nopt]) ;
ortset = (THD_3dim_dataset **)realloc(ortset,
sizeof(THD_3dim_dataset *)*(nortset+1)) ;
ortset[nortset++] = qset ;
nopt++ ; continue ;
}
if( strncmp(argv[nopt],"-nodetrend",6) == 0 ){
qdet = 0 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-dt") == 0 ){
if( ++nopt >= argc ) ERROR_exit("need an argument after -dt!") ;
dt = (float)strtod(argv[nopt],NULL) ;
if( dt <= 0.0f ) WARNING_message("value after -dt illegal!") ;
nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-input") == 0 ){
if( inset != NULL ) ERROR_exit("Can't have 2 -input options!") ;
if( ++nopt >= argc ) ERROR_exit("need an argument after -input!") ;
inset = THD_open_dataset(argv[nopt]) ;
CHECK_OPEN_ERROR(inset,argv[nopt]) ;
nopt++ ; continue ;
}
if( strncmp(argv[nopt],"-band",5) == 0 ){
if( ++nopt >= argc-1 ) ERROR_exit("need 2 arguments after -band!") ;
if( have_freq ) WARNING_message("second -band option replaces first one!") ;
fbot = strtod(argv[nopt++],NULL) ;
ftop = strtod(argv[nopt++],NULL) ;
have_freq = 1 ; continue ;
}
ERROR_exit("Unknown option: '%s'",argv[nopt]) ;
}
/** check inputs for reasonablositiness **/
if( !have_freq ){
if( nopt+1 >= argc )
ERROR_exit("Need frequencies on command line after options!") ;
fbot = (float)strtod(argv[nopt++],NULL) ;
ftop = (float)strtod(argv[nopt++],NULL) ;
}
if( inset == NULL ){
if( nopt >= argc )
ERROR_exit("Need input dataset name on command line after options!") ;
inset = THD_open_dataset(argv[nopt]) ;
CHECK_OPEN_ERROR(inset,argv[nopt]) ; nopt++ ;
}
DSET_UNMSEC(inset) ;
if( fbot < 0.0f ) ERROR_exit("fbot value can't be negative!") ;
if( ftop <= fbot ) ERROR_exit("ftop value %g must be greater than fbot value %g!",ftop,fbot) ;
ntime = DSET_NVALS(inset) ;
if( ntime < 9 ) ERROR_exit("Input dataset is too short!") ;
if( nfft <= 0 ){
nfft = csfft_nextup_even(ntime) ;
if( verb ) INFO_message("Data length = %d FFT length = %d",ntime,nfft) ;
(void)THD_bandpass_set_nfft(nfft) ;
} else if( nfft < ntime ){
ERROR_exit("-nfft %d is less than data length = %d",nfft,ntime) ;
} else {
kk = THD_bandpass_set_nfft(nfft) ;
if( kk != nfft && verb )
INFO_message("Data length = %d FFT length = %d",ntime,kk) ;
}
if( dt <= 0.0f ){
dt = DSET_TR(inset) ;
if( dt <= 0.0f ){
WARNING_message("Setting dt=1.0 since input dataset lacks a time axis!") ;
dt = 1.0f ;
}
}
if( !THD_bandpass_OK(ntime,dt,fbot,ftop,1) ) ERROR_exit("Can't continue!") ;
nx = DSET_NX(inset); ny = DSET_NY(inset); nz = DSET_NZ(inset); nvox = nx*ny*nz;
/* check mask, or create it */
if( verb ) INFO_message("Loading input dataset time series" ) ;
DSET_load(inset) ;
if( mask != NULL ){
if( mask_nx != nx || mask_ny != ny || mask_nz != nz )
ERROR_exit("-mask dataset grid doesn't match input dataset") ;
} else if( do_automask ){
mask = THD_automask( inset ) ;
if( mask == NULL )
ERROR_message("Can't create -automask from input dataset?") ;
nmask = THD_countmask( DSET_NVOX(inset) , mask ) ;
if( verb ) INFO_message("Number of voxels in automask = %d",nmask);
if( nmask < 1 ) ERROR_exit("Automask is too small to process") ;
} else {
mask = (byte *)malloc(sizeof(byte)*nvox) ; nmask = nvox ;
memset(mask,1,sizeof(byte)*nvox) ;
if( verb ) INFO_message("No mask ==> processing all %d voxels",nvox);
}
/* A simple check of dataset quality [08 Feb 2010] */
if( !nosat ){
float val ;
INFO_message(
"Checking dataset for initial transients [use '-notrans' to skip this test]") ;
val = THD_saturation_check(inset,mask,0,0) ; kk = (int)(val+0.54321f) ;
if( kk > 0 )
ININFO_message(
"Looks like there %s %d non-steady-state initial time point%s :-(" ,
((kk==1) ? "is" : "are") , kk , ((kk==1) ? " " : "s") ) ;
else if( val > 0.3210f ) /* don't ask where this threshold comes from! */
ININFO_message(
"MAYBE there's an initial positive transient of 1 point, but it's hard to tell\n") ;
else
ININFO_message("No widespread initial positive transient detected :-)") ;
}
/* check -dsort inputs for match to inset */
for( kk=0 ; kk < nortset ; kk++ ){
if( DSET_NX(ortset[kk]) != nx ||
DSET_NY(ortset[kk]) != ny ||
DSET_NZ(ortset[kk]) != nz ||
DSET_NVALS(ortset[kk]) != ntime )
ERROR_exit("-dsort %s doesn't match input dataset grid" ,
DSET_BRIKNAME(ortset[kk]) ) ;
}
/* convert input dataset to a vectim, which is more fun */
mrv = THD_dset_to_vectim( inset , mask , 0 ) ;
if( mrv == NULL ) ERROR_exit("Can't load time series data!?") ;
DSET_unload(inset) ;
/* similarly for the ort vectors */
if( ortar != NULL ){
for( kk=0 ; kk < IMARR_COUNT(ortar) ; kk++ ){
ortim = IMARR_SUBIM(ortar,kk) ;
if( ortim->nx < ntime )
ERROR_exit("-ort file %s is shorter than input dataset time series",
ortim->name ) ;
ort = (float **)realloc( ort , sizeof(float *)*(nort+ortim->ny) ) ;
for( vv=0 ; vv < ortim->ny ; vv++ )
ort[nort++] = MRI_FLOAT_PTR(ortim) + ortim->nx * vv ;
}
}
/* check whether processing leaves any DoF remaining 18 Mar 2015 [rickr] */
{
int nbprem = THD_bandpass_remain_dim(ntime, dt, fbot, ftop, 1);
int bpused, nremain;
int wlimit; /* warning limit */
bpused = ntime - nbprem; /* #dim lost in bandpass step */
nremain = nbprem - nort; /* #dim left in output */
if( nortset == 1 ) nremain--;
nremain -= (qdet+1);
if( verb ) INFO_message("%d dimensional data reduced to %d by:\n"
" %d (bandpass), %d (-ort), %d (-dsort), %d (detrend)",
ntime, nremain, bpused, nort, nortset?1:0, qdet+1);
/* possibly warn (if 95% lost) user or fail */
wlimit = ntime/20;
if( wlimit < 3 ) wlimit = 3;
if( nremain < wlimit && nremain > 0 )
WARNING_message("dimensionality reduced from %d to %d, be careful!",
ntime, nremain);
if( nremain <= 0 ) /* FAILURE */
ERROR_exit("dimensionality reduced from %d to %d, failing!",
ntime, nremain);
}
/* all the real work now */
if( do_despike ){
int_pair nsp ;
if( verb ) INFO_message("Testing data time series for spikes") ;
nsp = THD_vectim_despike9( mrv ) ;
if( verb ) ININFO_message(" -- Squashed %d spikes from %d voxels",nsp.j,nsp.i) ;
}
if( verb ) INFO_message("Bandpassing data time series") ;
(void)THD_bandpass_vectim( mrv , dt,fbot,ftop , qdet , nort,ort ) ;
/* OK, maybe a little more work */
if( nortset == 1 ){
MRI_vectim *orv ;
orv = THD_dset_to_vectim( ortset[0] , mask , 0 ) ;
if( orv == NULL ){
ERROR_message("Can't load -dsort %s",DSET_BRIKNAME(ortset[0])) ;
} else {
float *dp , *mvv , *ovv , ff ;
if( verb ) INFO_message("Orthogonalizing to bandpassed -dsort") ;
(void)THD_bandpass_vectim( orv , dt,fbot,ftop , qdet , nort,ort ) ;
THD_vectim_normalize( orv ) ;
dp = malloc(sizeof(float)*mrv->nvec) ;
THD_vectim_vectim_dot( mrv , orv , dp ) ;
for( vv=0 ; vv < mrv->nvec ; vv++ ){
ff = dp[vv] ;
if( ff != 0.0f ){
mvv = VECTIM_PTR(mrv,vv) ; ovv = VECTIM_PTR(orv,vv) ;
for( kk=0 ; kk < ntime ; kk++ ) mvv[kk] -= ff*ovv[kk] ;
}
}
VECTIM_destroy(orv) ; free(dp) ;
}
}
if( blur > 0.0f ){
if( verb )
INFO_message("Blurring time series data spatially; FWHM=%.2f",blur) ;
mri_blur3D_vectim( mrv , blur ) ;
}
if( pvrad > 0.0f ){
if( verb )
INFO_message("Local PV-ing time series data spatially; radius=%.2f",pvrad) ;
THD_vectim_normalize( mrv ) ;
THD_vectim_localpv( mrv , pvrad ) ;
}
if( do_norm && pvrad <= 0.0f ){
if( verb ) INFO_message("L2 normalizing time series data") ;
THD_vectim_normalize( mrv ) ;
}
/* create output dataset, populate it, write it, then quit */
if( verb ) INFO_message("Creating output dataset in memory, then writing it") ;
outset = EDIT_empty_copy(inset) ;
/* do not copy scalars 11 Sep 2015 [rickr] */
EDIT_dset_items( outset , ADN_prefix,prefix ,
ADN_brick_fac,NULL ,
ADN_none ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dBandpass" , argc,argv , outset ) ;
for( vv=0 ; vv < ntime ; vv++ )
EDIT_substitute_brick( outset , vv , MRI_float , NULL ) ;
#if 1
THD_vectim_to_dset( mrv , outset ) ;
#else
AFNI_OMP_START ;
#pragma omp parallel
{ float *far , *var ; int *ivec=mrv->ivec ; int vv,kk ;
#pragma omp for
for( vv=0 ; vv < ntime ; vv++ ){
far = DSET_BRICK_ARRAY(outset,vv) ; var = mrv->fvec + vv ;
for( kk=0 ; kk < nmask ; kk++ ) far[ivec[kk]] = var[kk*ntime] ;
}
}
AFNI_OMP_END ;
#endif
VECTIM_destroy(mrv) ;
DSET_write(outset) ; if( verb ) WROTE_DSET(outset) ;
exit(0) ;
}
int main( int argc , char *argv[] )
{
THD_3dim_dataset *xset=NULL , *cset ;
int nopt=1, datum=MRI_float, nvals, ii;
MRI_IMAGE *ysim=NULL ;
char *prefix = "Tcorr1D", *smethod="pearson";
char *xnam=NULL , *ynam=NULL ;
byte *mask=NULL ; int mask_nx,mask_ny,mask_nz , nmask=0 ;
int do_atanh = 0 ; /* 12 Jan 2018 */
/*----*/
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf("Usage: 3dTcorr1D [options] xset y1D\n"
"Computes the correlation coefficient between each voxel time series\n"
"in the input 3D+time dataset 'xset' and each column in the 1D time\n"
"series file 'y1D', and stores the output values in a new dataset.\n"
"\n"
"OPTIONS:\n"
" -pearson = Correlation is the normal Pearson (product moment)\n"
" correlation coefficient [this is the default method].\n"
" -spearman = Correlation is the Spearman (rank) correlation\n"
" coefficient.\n"
" -quadrant = Correlation is the quadrant correlation coefficient.\n"
" -ktaub = Correlation is Kendall's tau_b coefficient.\n"
" ++ For 'continuous' or finely-discretized data, tau_b and\n"
" rank correlation are nearly equivalent (but not equal).\n"
" -dot = Doesn't actually compute a correlation coefficient; just\n"
" calculates the dot product between the y1D vector(s)\n"
" and the dataset time series.\n"
"\n"
" -Fisher = Apply the 'Fisher' (inverse hyperbolic tangent) transformation\n"
" to the results.\n"
" ++ It does not make sense to use this with '-ktaub', but if\n"
" you want to do it, the program will not stop you.\n"
" ++ Cannot be used with '-dot'!\n"
"\n"
" -prefix p = Save output into dataset with prefix 'p'\n"
" [default prefix is 'Tcorr1D'].\n"
"\n"
" -mask mmm = Only process voxels from 'xset' that are nonzero\n"
" in the 3D mask dataset 'mmm'.\n"
" ++ Other voxels in the output will be set to zero.\n"
"\n"
" -float = Save results in float format [the default format].\n"
" -short = Save results in scaled short format [to save disk space].\n"
" ++ Cannot be used with '-dot'!\n"
"\n"
"NOTES:\n"
"* The output dataset is functional bucket type, with one sub-brick\n"
" per column of the input y1D file.\n"
"* No detrending, blurring, or other pre-processing options are available;\n"
" if you want these things, see 3dDetrend or 3dTproject or 3dcalc.\n"
" [In other words, this program presumes you know what you are doing!]\n"
"* Also see 3dTcorrelate to do voxel-by-voxel correlation of TWO\n"
" 3D+time datasets' time series, with similar options.\n"
"* You can extract the time series from a single voxel with given\n"
" spatial indexes using 3dmaskave, and then run it with 3dTcorr1D:\n"
" 3dmaskave -quiet -ibox 40 30 20 epi_r1+orig > r1_40_30_20.1D\n"
" 3dTcorr1D -pearson -Fisher -prefix c_40_30_20 epi_r1+orig r1_40_30_20.1D\n"
"* http://en.wikipedia.org/wiki/Correlation\n"
"* http://en.wikipedia.org/wiki/Pearson_product-moment_correlation_coefficient\n"
"* http://en.wikipedia.org/wiki/Spearman%%27s_rank_correlation_coefficient\n"
"* http://en.wikipedia.org/wiki/Kendall_tau_rank_correlation_coefficient\n"
"\n"
"-- RWCox - Apr 2010\n"
" - Jun 2010: Multiple y1D columns; OpenMP; -short; -mask.\n"
) ;
PRINT_AFNI_OMP_USAGE("3dTcorr1D",NULL) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
mainENTRY("3dTcorr1D main"); machdep(); AFNI_logger("3dTcorr1D",argc,argv);
PRINT_VERSION("3dTcorr1D") ; THD_check_AFNI_version("3dTcorr1D") ;
/*-- option processing --*/
while( nopt < argc && argv[nopt][0] == '-' ){
if( strcmp(argv[nopt],"-mask") == 0 ){ /* 28 Jun 2010 */
THD_3dim_dataset *mset ;
if( ++nopt >= argc ) ERROR_exit("Need argument after '-mask'") ;
if( mask != NULL ) ERROR_exit("Can't have two mask inputs") ;
mset = THD_open_dataset( argv[nopt] ) ;
CHECK_OPEN_ERROR(mset,argv[nopt]) ;
DSET_load(mset) ; CHECK_LOAD_ERROR(mset) ;
mask_nx = DSET_NX(mset); mask_ny = DSET_NY(mset); mask_nz = DSET_NZ(mset);
mask = THD_makemask( mset , 0 , 0.5f, 0.0f ) ; DSET_delete(mset) ;
if( mask == NULL ) ERROR_exit("Can't make mask from dataset '%s'",argv[nopt]) ;
nmask = THD_countmask( mask_nx*mask_ny*mask_nz , mask ) ;
INFO_message("Number of voxels in mask = %d",nmask) ;
if( nmask < 2 ) ERROR_exit("Mask is too small to process") ;
nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-float") == 0 ){ /* 27 Jun 2010 */
datum = MRI_float ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-short") == 0 ){
datum = MRI_short ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-pearson") == 0 ){
smethod = "pearson" ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-dot") == 0 ){
smethod = "dot" ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-spearman") == 0 || strcasecmp(argv[nopt],"-rank") == 0 ){
smethod = "spearman" ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-quadrant") == 0 ){
smethod = "quadrant" ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-ktaub") == 0 || strcasecmp(argv[nopt],"-taub") == 0 ){
smethod = "ktaub" ; nopt++ ; continue ;
}
if( strcasecmp(argv[nopt],"-fisher") == 0 ){ /* 12 Jan 2018 */
do_atanh = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-prefix") == 0 ){
prefix = argv[++nopt] ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Illegal value after -prefix!") ;
nopt++ ; continue ;
}
ERROR_exit("Unknown option: %s",argv[nopt]) ;
}
/*------------ open datasets, check for legality ------------*/
if( nopt+1 >= argc )
ERROR_exit("Need 2 non-option arguments on command line!?") ;
/* despite what the help says, if the 1D file is first, that's OK */
if( STRING_HAS_SUFFIX(argv[nopt],"1D") ){
ININFO_message("reading 1D file %s",argv[nopt]) ;
ysim = mri_read_1D( argv[nopt] ) ; ynam = argv[nopt] ;
if( ysim == NULL ) ERROR_exit("Can't read 1D file %s",argv[nopt]) ;
} else {
ININFO_message("reading dataset file %s",argv[nopt]) ;
xset = THD_open_dataset( argv[nopt] ) ; xnam = argv[nopt] ;
if( xset == NULL ) ERROR_exit("Can't open dataset %s",argv[nopt]) ;
}
/* read whatever type of file (3D or 1D) we don't already have */
nopt++ ;
if( xset != NULL ){
ININFO_message("reading 1D file %s",argv[nopt]) ;
ysim = mri_read_1D( argv[nopt] ) ; ynam = argv[nopt] ;
if( ysim == NULL ) ERROR_exit("Can't read 1D file %s",argv[nopt]) ;
} else {
ININFO_message("reading dataset file %s",argv[nopt]) ;
xset = THD_open_dataset( argv[nopt] ) ; xnam = argv[nopt] ;
if( xset == NULL ) ERROR_exit("Can't open dataset %s",argv[nopt]) ;
}
nvals = DSET_NVALS(xset) ; /* number of time points */
ii = (strcmp(smethod,"dot")==0) ? 2 : 3 ;
if( nvals < ii )
ERROR_exit("Input dataset %s length is less than ii?!",xnam,ii) ;
if( ysim->nx < nvals )
ERROR_exit("1D file %s has %d time points, but dataset has %d values",
ynam,ysim->nx,nvals) ;
else if( ysim->nx > nvals )
WARNING_message("1D file %s has %d time points, dataset has %d",
ynam,ysim->nx,nvals) ;
if( mri_allzero(ysim) )
ERROR_exit("1D file %s is all zero!",ynam) ;
if( ysim->ny > 1 )
INFO_message("1D file %s has %d columns: correlating with ALL of them!",
ynam,ysim->ny) ;
if( strcmp(smethod,"dot") == 0 && do_atanh ){
WARNING_message("'-dot' turns off '-Fisher'") ; do_atanh = 0 ;
}
if( strcmp(smethod,"dot") == 0 && datum == MRI_short ){
WARNING_message("'-dot' turns off '-short'") ; datum = MRI_float ;
}
cset = THD_Tcorr1D( xset, mask, nmask, ysim, smethod,
prefix, (datum==MRI_short) , do_atanh );
tross_Make_History( "3dTcorr1D" , argc,argv , cset ) ;
DSET_unload(xset) ; /* no longer needful */
/* finito */
DSET_write(cset) ;
INFO_message("Wrote dataset: %s\n",DSET_BRIKNAME(cset)) ;
exit(0) ;
}
int main( int argc , char *argv[] )
{
int iarg , ct , do_GM=0 ;
int do_T2=0 ; float T2_uperc=98.5f ; byte *T2_mask=NULL ;
char *prefix = "Unifized" ;
THD_3dim_dataset *inset=NULL , *outset=NULL ;
MRI_IMAGE *imin , *imout ;
float clfrac=0.2f ;
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf("\n"
"Usage: 3dUnifize [options] inputdataset\n\n"
"* The input dataset is supposed to be a T1-weighted volume,\n"
" possibly already skull-stripped (e.g., via 3dSkullStrip).\n"
" ++ However, this program can be a useful step to take BEFORE\n"
" 3dSkullStrip, since the latter program can fail if the input\n"
" volume is strongly shaded -- 3dUnifize will (mostly) remove\n"
" such shading artifacts.\n"
"* The output dataset has the white matter (WM) intensity approximately\n"
" uniformized across space, and scaled to peak at about 1000.\n"
"* The output dataset is always stored in float format!\n"
"* If the input dataset has more than 1 sub-brick, only sub-brick\n"
" #0 will be processed!\n"
"* Method: Obi-Wan's personal variant of Ziad's sneaky trick.\n"
" (If you want to know what his trick is, you'll have to ask him, or\n"
" read Obi-Wan's source code, which is a world of ecstasy and exaltation,\n"
" or just read all the way to the end of this help output.)\n"
"* The principal motive for this program is for use in an image\n"
" registration script, and it may or may not be useful otherwise.\n"
"\n"
"--------\n"
"Options:\n"
"--------\n"
" -prefix pp = Use 'pp' for prefix of output dataset.\n"
" -input dd = Alternative way to specify input dataset.\n"
" -T2 = Treat the input as if it were T2-weighted, rather than\n"
" T1-weighted. This processing is done simply by inverting\n"
" the image contrast, processing it as if that result were\n"
" T1-weighted, and then re-inverting the results.\n"
" ++ This option is NOT guaranteed to be useful for anything!\n"
" ++ Of course, nothing in AFNI comes with a guarantee :-)\n"
" ++ If you want to be REALLY sneaky, giving this option twice\n"
" will skip the second inversion step, so the result will\n"
" look like a T1-weighted volume (except at the edges and\n"
" near blood vessels).\n"
" ++ Might be useful for skull-stripping T2-weighted datasets.\n"
" ++ Don't try the '-T2 -T2' trick on FLAIR-T2-weighted datasets.\n"
" The results aren't pretty!\n"
" -GM = Also scale to unifize 'gray matter' = lower intensity voxels\n"
" (to aid in registering images from different scanners).\n"
" ++ This option is recommended for use with 3dQwarp when\n"
" aligning 2 T1-weighted volumes, in order to make the\n"
" WM-GM contrast about the same for the datasets, even\n"
" if they don't come from the same scanner/pulse-sequence.\n"
" ++ Note that standardizing the contrasts with 3dUnifize will help\n"
" 3dQwarp match the source dataset to the base dataset. If you\n"
" later want the original source dataset to be warped, you can\n"
" do so using the 3dNwarpApply program.\n"
" -Urad rr = Sets the radius (in voxels) of the ball used for the sneaky trick.\n"
" ++ Default value is %.1f, and should be changed proportionally\n"
" if the dataset voxel size differs significantly from 1 mm.\n"
" -ssave ss = Save the scale factor used at each voxel into a dataset 'ss'.\n"
" ++ This is the white matter scale factor, and does not include\n"
" the factor from the '-GM' option (if that was included).\n"
" ++ The input dataset is multiplied by the '-ssave' image\n"
" (voxel-wise) to get the WM-unifized image.\n"
" ++ Another volume (with the same grid dimensions) could be\n"
" scaled the same way using 3dcalc, if that is needed.\n"
" -quiet = Don't print the fun fun fun progress messages (but whyyyy?).\n"
" ++ For the curious, the codes used are:\n"
" A = Automask\n"
" D = Duplo down (process a half-size volume)\n"
" V = Voxel-wise histograms to get local scale factors\n"
" U = duplo Up (convert local scale factors to full-size volume)\n"
" W = multiply by White matter factors\n"
" G = multiply by Gray matter factors [cf the -GM option]\n"
" I = contrast inversion [cf the -T2 option]\n"
" ++ 'Duplo down' means to scale the input volume to be half the\n"
" grid size in each direction for speed when computing the\n"
" voxel-wise histograms. The sub-sampling is done using the\n"
" median of the central voxel value and its 6 nearest neighbors.\n"
"\n"
"------------------------------------------\n"
"Special options for Jedi AFNI Masters ONLY:\n"
"------------------------------------------\n"
" -rbt R b t = Specify the 3 parameters for the algorithm, as 3 numbers\n"
" following the '-rbt':\n"
" R = radius; same as given by option '-Urad' [default=%.1f]\n"
" b = bottom percentile of normalizing data range [default=%.1f]\n"
" r = top percentile of normalizing data range [default=%.1f]\n"
"\n"
" -T2up uu = Set the upper percentile point used for T2-T1 inversion.\n"
" The default value is 98.5 (for no good reason), and 'uu' is\n"
" allowed to be anything between 90 and 100 (inclusive).\n"
" ++ The histogram of the data is built, and the uu-th percentile\n"
" point value is called 'U'. The contrast inversion is simply\n"
" given by output_value = max( 0 , U - input_value ).\n"
"\n"
" -clfrac cc = Set the automask 'clip level fraction' to 'cc', which\n"
" must be a number between 0.1 and 0.9.\n"
" A small 'cc' means to make the initial threshold\n"
" for clipping (a la 3dClipLevel) smaller, which\n"
" will tend to make the mask larger. [default=0.1]\n"
" ++ [22 May 2013] The previous version of this program used a\n"
" clip level fraction of 0.5, which proved to be too large\n"
" for some users, who had images with very strong shading issues.\n"
" Thus, the default value for this parameter was lowered to 0.1.\n"
" ++ [24 May 2016] The default value for this parameter was\n"
" raised to 0.2, since the lower value often left a lot of\n"
" noise outside the head on non-3dSkullStrip-ed datasets.\n"
" You can still manually set -clfrac to 0.1 if you need to\n"
" correct for very large shading artifacts.\n"
" ++ If the results of 3dUnifize have a lot of noise outside the head,\n"
" then using '-clfrac 0.5' value will probably help.\n"
#ifndef USE_ALL_VALS
"\n"
" -useall = The 'old' way of operating was to use all dataset values\n"
" in the local WM histogram. The 'new' way [May 2016] is to\n"
" only use positive values. If you want to use the 'old' way,\n"
" then this option is what you want.\n"
#endif
"\n"
"-- Feb 2013 - by Obi-Wan Unifobi\n"
#ifdef USE_OMP
"-- This code uses OpenMP to speed up the slowest part (voxel-wise histograms).\n"
#endif
, Uprad , Uprad , Upbot , Uptop ) ;
printf("\n"
"----------------------------------------------------------------------------\n"
"HOW IT WORKS (Ziad's sneaky trick is revealed at last! And more.)\n"
"----------------------------------------------------------------------------\n"
"The basic idea is that white matter in T1-weighted images is reasonably\n"
"uniform in intensity, at least when averaged over 'large-ish' regions.\n"
"\n"
"The first step is to create a local white matter intensity volume.\n"
"Around each voxel (inside the volume 'automask'), the ball of values\n"
"within a fixed radius (default=18.3 voxels) is extracted and these\n"
"numbers are sorted. The values in the high-intensity range of the\n"
"histogram (default=70%% to 80%%) are averaged. The result from this\n"
"step is a smooth 3D map of the 'white matter intensity' (WMI).\n"
"\n"
" [The parameters of the above process can be altered with the '-rbt' option.]\n"
" [For speed, the WMI map is produced on an image that is half-size in all ]\n"
" [directions ('Duplo down'), and then is expanded back to the full-size ]\n"
" [volume ('Duplo up'). The automask procedure can be somewhat controlled ]\n"
" [via the '-clfrac' option. The default setting is designed to deal with ]\n"
" [heavily shaded images, where the WMI varies by a factor of 5 or more over ]\n"
" [the image volume. ]\n"
"\n"
"The second step is to scale the value at every voxel location x in the input\n"
"volume by the factor 1000/WMI(x), so that the 'white matter intensity' is\n"
"now uniform-ized to be 1000 everywhere. (This is Ziad's 'trick'; it is easy,\n"
"works well, and doesn't require fitting some spatial model to the data: the\n"
"data provides its own model.)\n"
"\n"
"If the '-GM' option is used, then this scaled volume is further processed\n"
"to make the lower intensity values (presumably gray matter) have a contrast\n"
"similar to that from a collection of 3 Tesla MP-RAGE images that were\n"
"acquired at the NIH. (This procedure is not Ziad's fault, and should be\n"
"blamed on the reclusive Obi-Wan Unifobi.)\n"
"\n"
"From the WM-uniform-ized volume, the median of all values larger than 1000\n"
"is computed; call this value P. P-1000 represents the upward dispersion\n"
"of the high-intensity (white matter) voxels in the volume. This value is\n"
"'reflected' below 1000 to Q = 1000 - 2*(P-1000), and Q is taken to be the\n"
"upper bound for gray matter voxel intensities. A lower bound for gray\n"
"matter voxel values is estimated via the 'clip fraction' algorithm as\n"
"implemented in program 3dClipLevel; call this lower bound R. The median\n"
"of all values between R and Q is computed; call this value G, which is taken\n"
"to be a 'typical' gray matter voxel instensity. Then the values z in the\n"
"entire volume are linearly scaled by the formula\n"
" z_out = (1000-666)/(1000-G) * (z_in-1000) + 1000\n"
"so that the WM uniform-ized intensity of 1000 remains at 1000, and the gray\n"
"matter median intensity of G is mapped to 666. (Values z_out that end up\n"
"negative are set to 0; as a result, some of CSF might end up as 0.)\n"
"The value 666 was chosen because it gave results visually comparable to\n"
"various NIH-generated 3 Tesla T1-weighted datasets. (Any suggestions that\n"
"this value was chosen for other reasons will be treated as 'beastly'.)\n"
"\n"
"To recap: the WM uniform-ization process provides a linear scaling factor\n"
"that varies for each voxel ('local'), while the GM normalization process\n"
"uses a global linear scaling. The GM process is optional, and is simply\n"
"designed to make the various T1-weighted images look similar.\n"
"\n"
"-----** CAVEAT **-----\n"
"This procedure was primarily developed to aid in 3D registration, especially\n"
"when using 3dQwarp, so that the registration algorithms are trying to match\n"
"images that are alike. It is *NOT* intended to be used for quantification\n"
"purposes, such as Voxel Based Morphometry! That would better be done via\n"
"the 3dSeg program, which is far more complicated.\n"
"----------------------------------------------------------------------------\n"
) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
mainENTRY("3dUnifize main"); machdep(); AFNI_logger("3dUnifize",argc,argv);
PRINT_VERSION("3dUnifize") ;
ct = NI_clock_time() ;
/*-- scan command line --*/
THD_automask_set_clipfrac(0.1f) ; /* 22 May 2013 */
THD_automask_extclip(1) ; /* 19 Dec 2014 */
iarg = 1 ;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcmp(argv[iarg],"-clfrac") == 0 || strcmp(argv[iarg],"-mfrac") == 0 ){ /* 22 May 2013 */
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
clfrac = (float)strtod( argv[iarg] , NULL ) ;
if( clfrac < 0.1f || clfrac > 0.9f )
ERROR_exit("-clfrac value %f is illegal!",clfrac) ;
THD_automask_set_clipfrac(clfrac) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-prefix") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
prefix = argv[iarg] ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Illegal value after -prefix!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ssave") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
sspref = strdup(argv[iarg]) ;
if( !THD_filename_ok(sspref) ) ERROR_exit("Illegal value after -ssave!") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-input") == 0 || strcmp(argv[iarg],"-inset") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
if( inset != NULL ) ERROR_exit("Can't use '%s' twice" ,argv[iarg-1]) ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-Urad") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]) ;
Uprad = (float)strtod(argv[iarg],NULL) ;
if( Uprad < 5.0f || Uprad > 40.0f )
ERROR_exit("Illegal value %f after option -Urad",Uprad) ;
iarg++ ; continue ;
}
#ifndef USE_ALL_VALS
if( strcmp(argv[iarg],"-useall") == 0 ){ /* 17 May 2016 */
USE_ALL_VALS = 1 ; iarg++ ; continue ;
}
#else
if( strcmp(argv[iarg],"-useall") == 0 ){
WARNING_message("-useall option is disabled in this version") ;
iarg++ ; continue ;
}
#endif
if( strcmp(argv[iarg],"-param") == 0 || /*--- HIDDEN OPTION ---*/
strcmp(argv[iarg],"-rbt" ) == 0 ){
if( ++iarg >= argc-2 ) ERROR_exit("Need 3 arguments (R pb pt) after '%s'",argv[iarg-1]) ;
Uprad = (float)strtod(argv[iarg++],NULL) ;
Upbot = (float)strtod(argv[iarg++],NULL) ;
Uptop = (float)strtod(argv[iarg++],NULL) ;
if( Uprad < 5.0f || Uprad > 40.0f ||
Upbot < 30.0f || Upbot > 80.0f ||
Uptop <= Upbot || Uptop > 90.0f )
ERROR_exit("Illegal values (R pb pt) after '%s'",argv[iarg-4]) ;
continue ;
}
if( strcasecmp(argv[iarg],"-GM") == 0 ){
do_GM++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-T2") == 0 ){ /* 18 Dec 2014 */
do_T2++ ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-T2up") == 0 ){ /* 18 Dec 2014 */
T2_uperc = (float)strtod( argv[++iarg] , NULL ) ;
if( T2_uperc < 90.0f || T2_uperc > 100.0f )
ERROR_exit("-T2up value is out of range 90..100 :-(") ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-quiet") == 0 ){
verb = 0 ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-verb") == 0 ){
verb++ ; iarg++ ; continue ;
}
ERROR_exit("Unknown option: %s\n",argv[iarg]);
}
/* read input dataset, if not already there */
if( inset == NULL ){
if( iarg >= argc ) ERROR_exit("No dataset name on command line?\n") ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
}
if( verb ) fprintf(stderr," + Pre-processing: ") ;
/* load input from disk */
DSET_load( inset ) ; CHECK_LOAD_ERROR(inset) ;
if( DSET_NVALS(inset) > 1 )
WARNING_message("Only processing sub-brick #0 (out of %d)",DSET_NVALS(inset)) ;
/* make a float copy for processing */
imin = mri_to_float( DSET_BRICK(inset,0) ) ; DSET_unload(inset) ;
if( imin == NULL ) ERROR_exit("Can't copy input dataset brick?!") ;
#if 0
THD_cliplevel_search(imin) ; exit(0) ; /* experimentation only */
#endif
THD_automask_set_clipfrac(clfrac) ;
/* invert T2? */
if( do_T2 ){
if( verb ) fprintf(stderr,"I") ;
T2_mask = mri_automask_image(imin) ;
mri_invertcontrast_inplace( imin , T2_uperc , T2_mask ) ;
}
/* do the actual work */
imout = mri_WMunifize(imin) ; /* local WM scaling */
free(imin) ;
if( sspref != NULL && sclim != NULL ){ /* 25 Jun 2013 */
STATUS("output -ssave") ;
outset = EDIT_empty_copy( inset ) ;
EDIT_dset_items( outset ,
ADN_prefix , sspref ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(sclim) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dUnifize" , argc,argv , outset ) ;
DSET_write(outset) ; outset = NULL ;
}
if( sclim != NULL ){ mri_free(sclim) ; sclim = NULL ; }
if( imout == NULL ){ /* this is bad-ositiness */
if( verb ) fprintf(stderr,"\n") ;
ERROR_exit("Can't compute Unifize-d dataset for some reason :-(") ;
}
if( do_GM ) mri_GMunifize(imout) ; /* global GM scaling */
if( do_T2 == 1 ){ /* re-invert T2? */
if( verb ) fprintf(stderr,"I") ;
mri_invertcontrast_inplace( imout , T2_uperc , T2_mask ) ;
} else if( do_T2 == 2 ){ /* don't re-invert, but clip off bright edges */
mri_clipedges_inplace( imout , PKVAL*1.111f , PKVAL*1.055f ) ;
}
if( verb ) fprintf(stderr,"\n") ;
/* create output dataset, and write it into the historical record */
outset = EDIT_empty_copy( inset ) ;
EDIT_dset_items( outset ,
ADN_prefix , prefix ,
ADN_nvals , 1 ,
ADN_ntt , 0 ,
ADN_none ) ;
EDIT_substitute_brick( outset , 0 , MRI_float , MRI_FLOAT_PTR(imout) ) ;
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dUnifize" , argc,argv , outset ) ;
DSET_write(outset) ;
WROTE_DSET(outset) ;
DSET_delete(outset) ; DSET_delete(inset) ;
/* vamoose the ranch */
if( verb ){
double cput = COX_cpu_time() ;
if( cput > 0.05 )
INFO_message("===== CPU time = %.1f sec Elapsed = %.1f\n",
COX_cpu_time() , 0.001*(NI_clock_time()-ct) ) ;
else
INFO_message("===== Elapsed = %.1f sec\n", 0.001*(NI_clock_time()-ct) ) ;
}
exit(0) ;
}
int main(int argc, char *argv[]) {
int i,j,k,m,n,mm;
int iarg;
THD_3dim_dataset *insetTIME = NULL;
THD_3dim_dataset *MASK=NULL;
THD_3dim_dataset *ROIS=NULL;
char *prefix="NETCORR" ;
char in_name[300];
char in_mask[300];
char in_rois[300];
char OUT_grid[300];
char OUT_indiv[300];
char OUT_indiv0[300];
// int *SELROI=NULL; // if selecting subset of ROIs
// int HAVE_SELROI=0;
int NIFTI_OUT = 0;
byte ***mskd=NULL; // define mask of where time series are nonzero
byte *mskd2=NULL; // not great, but another format of mask
int HAVE_MASK=0;
int HAVE_ROIS=0;
int FISH_OUT=0;
int PART_CORR=0;
int TS_OUT=0;
int TS_LABEL=0;
int TS_INDIV=0;
int TS_WBCORR_r=0;
int TS_WBCORR_Z=0;
int *NROI_REF=NULL,*INVROI_REF=NULL;
int **ROI_LABELS_REF=NULL, **INV_LABELS_REF=NULL,**ROI_COUNT=NULL;
int ***ROI_LISTS=NULL;
double ***ROI_AVE_TS=NULL; // double because of GSL
float ***Corr_Matr=NULL;
float ***PCorr_Matr=NULL, ***PBCorr_Matr=NULL;
int Nvox=-1; // tot number vox
int *Dim=NULL;
int *Nlist=NULL;
Dtable *roi_dtable=NULL;
char *LabTabStr=NULL;
char ***ROI_STR_LABELS=NULL;
// for niml.dset -> graph viewing in SUMA
char ***gdset_roi_names=NULL;
SUMA_DSET *gset=NULL;
float ***flat_matr=NULL;
float *xyz=NULL;
char OUT_gdset[300];
NI_group *GDSET_netngrlink=NULL;
char *NAME_gdset=NULL;
int Noutmat = 1; // num of matr to output: start with CC for sure
char **ParLab=NULL;
int FM_ctr = 0; // for counting through flatmatr entries
int OLD_LABEL=0; // ooollld style format of regions: Nnumber:Rnumber
int IGNORE_LT=0; // ignore label table
int idx = 0;
int Nmask = 0;
FILE *fout1,*fin,*fout2;
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
mainENTRY("3dNetCorr"); machdep();
// ****************************************************************
// ****************************************************************
// load AFNI stuff
// ****************************************************************
// ****************************************************************
// INFO_message("version: BETA");
/** scan args **/
if (argc == 1) { usage_NetCorr(1); exit(0); }
iarg = 1;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcmp(argv[iarg],"-help") == 0 ||
strcmp(argv[iarg],"-h") == 0 ) {
usage_NetCorr(strlen(argv[iarg])>3 ? 2:1);
exit(0);
}
if( strcmp(argv[iarg],"-prefix") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-prefix'");
prefix = strdup(argv[iarg]) ;
if( !THD_filename_ok(prefix) )
ERROR_exit("Illegal name after '-prefix'");
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-inset") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-input'");
sprintf(in_name,"%s", argv[iarg]);
insetTIME = THD_open_dataset(in_name) ;
if( (insetTIME == NULL ))
ERROR_exit("Can't open time series dataset '%s'.",in_name);
// just 0th time point for output...
Dim = (int *)calloc(4,sizeof(int));
DSET_load(insetTIME); CHECK_LOAD_ERROR(insetTIME);
Nvox = DSET_NVOX(insetTIME) ;
Dim[0] = DSET_NX(insetTIME); Dim[1] = DSET_NY(insetTIME);
Dim[2] = DSET_NZ(insetTIME); Dim[3]= DSET_NVALS(insetTIME);
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-mask") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-mask'");
HAVE_MASK= 1;
sprintf(in_mask,"%s", argv[iarg]);
MASK = THD_open_dataset(in_mask) ;
if( (MASK == NULL ))
ERROR_exit("Can't open time series dataset '%s'.",in_mask);
DSET_load(MASK); CHECK_LOAD_ERROR(MASK);
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-in_rois") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-in_rois'");
sprintf(in_rois,"%s", argv[iarg]);
ROIS = THD_open_dataset(in_rois) ;
if( (ROIS == NULL ))
ERROR_exit("Can't open time series dataset '%s'.",in_rois);
DSET_load(ROIS); CHECK_LOAD_ERROR(ROIS);
HAVE_ROIS=DSET_NVALS(ROIS); //number of subbricks
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-fish_z") == 0) {
FISH_OUT=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-nifti") == 0) {
NIFTI_OUT=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-part_corr") == 0) {
PART_CORR=2; // because we calculate two matrices here
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ts_out") == 0) {
TS_OUT=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ts_label") == 0) {
TS_LABEL=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ts_indiv") == 0) {
TS_INDIV=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ts_wb_corr") == 0) {
TS_WBCORR_r=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ts_wb_Z") == 0) {
TS_WBCORR_Z=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-old_labels") == 0) {
OLD_LABEL=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-ignore_LT") == 0) {
IGNORE_LT=1;
iarg++ ; continue ;
}
/* if( strcmp(argv[iarg],"-sel_roi") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-in_rois'");
SELROI = (int *)calloc(MAX_SELROI,sizeof(int));
if( (fin = fopen(argv[iarg], "r")) == NULL) {
fprintf(stderr, "Error opening file %s.",argv[iarg]);
exit(1);
}
idx=0;
while( !feof(fin) && (idx<MAX_SELROI-1) ){
fscanf(fin, "%d",&SELROI[idx]);
fscanf(fin," ");
idx++;
}
HAVE_SELROI=idx;
printf("HAVE_SELROI=%d\n",HAVE_SELROI);
if(HAVE_SELROI<=0) {
ERROR_message("Error reading in `-sel_roi'-- appears to have no ROIs listed.\n");
exit(1);
}
iarg++ ; continue ;
}*/
ERROR_message("Bad option '%s'\n",argv[iarg]) ;
suggest_best_prog_option(argv[0], argv[iarg]);
exit(1);
}
INFO_message("Reading in.");
if( !TS_OUT && TS_LABEL) {
ERROR_message("with '-ts_label', you also need '-ts_out'.\n");
exit(1);
}
if (iarg < 3) {
ERROR_message("Too few options. Try -help for details.\n");
exit(1);
}
if(!HAVE_ROIS) {
ERROR_message("Need to load ROIs with >=1 subbrick...\n");
exit(1);
}
if(Nvox != DSET_NVOX(ROIS)) {
ERROR_message("Data sets of `-inset' and `in_rois' have "
"different numbers of voxels per brik!\n");
exit(1);
}
if( (HAVE_MASK>0) && (Nvox != DSET_NVOX(MASK)) ) {
ERROR_message("Data sets of `-inset' and `mask' have "
"different numbers of voxels per brik!\n");
exit(1);
}
// ****************************************************************
// ****************************************************************
// make storage
// ****************************************************************
// ****************************************************************
Nlist = (int *)calloc(1,sizeof(int));
mskd2 = (byte *)calloc(Nvox,sizeof(byte));
mskd = (byte ***) calloc( Dim[0], sizeof(byte **) );
for ( i = 0 ; i < Dim[0] ; i++ )
mskd[i] = (byte **) calloc( Dim[1], sizeof(byte *) );
for ( i = 0 ; i < Dim[0] ; i++ )
for ( j = 0 ; j < Dim[1] ; j++ )
mskd[i][j] = (byte *) calloc( Dim[2], sizeof(byte) );
if( (mskd == NULL) || (Nlist == NULL) || (mskd2 == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure (masks).\n\n");
exit(122);
}
// *************************************************************
// *************************************************************
// Beginning of main loops
// *************************************************************
// *************************************************************
INFO_message("Allocating...");
// go through once: define data vox, and calc rank for each
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
if( HAVE_MASK ) {
if( THD_get_voxel(MASK,idx,0)>0 ) {
mskd[i][j][k] = 1;
mskd2[idx] = 1;
Nmask++;
}
}
else // simple automask attempt
if( fabs(THD_get_voxel(insetTIME,idx,0))+
fabs(THD_get_voxel(insetTIME,idx,1))+
fabs(THD_get_voxel(insetTIME,idx,2))+
fabs(THD_get_voxel(insetTIME,idx,3))+
fabs(THD_get_voxel(insetTIME,idx,4)) > EPS_V) {
mskd[i][j][k] = 1;
mskd2[idx] = 1;
Nmask++;
}
idx+= 1; // skip, and mskd and KW are both still 0 from calloc
}
if (HAVE_MASK) {
DSET_delete(MASK);
free(MASK);
}
// obviously, this should always be TRUE at this point...
if(HAVE_ROIS>0) {
NROI_REF = (int *)calloc(HAVE_ROIS, sizeof(int));
INVROI_REF = (int *)calloc(HAVE_ROIS, sizeof(int));
if( (NROI_REF == NULL) || (INVROI_REF == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(122);
}
for( i=0 ; i<HAVE_ROIS ; i++)
INVROI_REF[i] = (int) THD_subbrick_max(ROIS, i, 1);
ROI_LABELS_REF = calloc( HAVE_ROIS,sizeof(ROI_LABELS_REF));
for(i=0 ; i<HAVE_ROIS ; i++)
ROI_LABELS_REF[i] = calloc(INVROI_REF[i]+1,sizeof(int));
INV_LABELS_REF = calloc( HAVE_ROIS,sizeof(INV_LABELS_REF));
for(i=0 ; i<HAVE_ROIS ; i++)
INV_LABELS_REF[i] = calloc(INVROI_REF[i]+1,sizeof(int));
if( (ROI_LABELS_REF == NULL) || (INV_LABELS_REF == NULL)
) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
INFO_message("Labelling regions internally.");
// Step 3A-2: find out the labels in the ref, organize them
// both backwards and forwards.
i = ViveLeRoi(ROIS,
ROI_LABELS_REF, // ordered list of ROILABEL ints, [1..M];
// maxval is N.
INV_LABELS_REF, // ith values at the actual input locs;
// maxval is M.
NROI_REF, // M: # of ROIs per brik
INVROI_REF); // N: max ROI label per brik
if( i != 1)
ERROR_exit("Problem loading/assigning ROI labels");
ROI_STR_LABELS = (char ***) calloc( HAVE_ROIS, sizeof(char **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
ROI_STR_LABELS[i] = (char **) calloc( NROI_REF[i]+1, sizeof(char *) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i]+1 ; j++ )
ROI_STR_LABELS[i][j] = (char *) calloc( 100 , sizeof(char) );
if( (ROI_STR_LABELS == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
// Sept 2014: Labeltable stuff
if( IGNORE_LT ) {
INFO_message("Ignoring any '-in_rois' label table (if there is one).");
}
else{
if ((ROIS->Label_Dtable = DSET_Label_Dtable(ROIS))) {
if ((LabTabStr = Dtable_to_nimlstring( DSET_Label_Dtable(ROIS),
"VALUE_LABEL_DTABLE"))) {
//fprintf(stdout,"%s", LabTabStr);
if (!(roi_dtable = Dtable_from_nimlstring(LabTabStr))) {
ERROR_exit("Could not parse labeltable.");
}
}
else {
INFO_message("No label table from '-in_rois'.");
}
}
}
i = Make_ROI_Output_Labels( ROI_STR_LABELS,
ROI_LABELS_REF,
HAVE_ROIS,
NROI_REF,
roi_dtable,
1 );//!!!opts.DUMP_with_LABELS
ROI_COUNT = calloc( HAVE_ROIS,sizeof(ROI_COUNT));
for(i=0 ; i<HAVE_ROIS ; i++)
ROI_COUNT[i] = calloc(NROI_REF[i],sizeof(int));
if( (ROI_COUNT == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
// find num of vox per ROI
for( m=0 ; m<HAVE_ROIS ; m++ ) {
idx=0;
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
if( (THD_get_voxel(ROIS,idx,m) > 0 ) && mskd[i][j][k] ) {
ROI_COUNT[m][INV_LABELS_REF[m][(int)
THD_get_voxel(ROIS,idx,m)]-1]++;
}
idx++;
}
}
// make list of vox per ROI
ROI_LISTS = (int ***) calloc( HAVE_ROIS, sizeof(int **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
ROI_LISTS[i] = (int **) calloc( NROI_REF[i], sizeof(int *) );
for ( i=0 ; i <HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i] ; j++ )
ROI_LISTS[i][j] = (int *) calloc( ROI_COUNT[i][j], sizeof(int) );
// make average time series per voxel
ROI_AVE_TS = (double ***) calloc( HAVE_ROIS, sizeof(double **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
ROI_AVE_TS[i] = (double **) calloc( NROI_REF[i], sizeof(double *) );
for ( i=0 ; i <HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i] ; j++ )
ROI_AVE_TS[i][j] = (double *) calloc( Dim[3], sizeof(double) );
// store corr coefs
Corr_Matr = (float ***) calloc( HAVE_ROIS, sizeof(float **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
Corr_Matr[i] = (float **) calloc( NROI_REF[i], sizeof(float *) );
for ( i=0 ; i <HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i] ; j++ )
Corr_Matr[i][j] = (float *) calloc( NROI_REF[i], sizeof(float) );
if( (ROI_LISTS == NULL) || (ROI_AVE_TS == NULL)
|| (Corr_Matr == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
if(PART_CORR) {
PCorr_Matr = (float ***) calloc( HAVE_ROIS, sizeof(float **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
PCorr_Matr[i] = (float **) calloc( NROI_REF[i], sizeof(float *) );
for ( i=0 ; i <HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i] ; j++ )
PCorr_Matr[i][j] = (float *) calloc( NROI_REF[i], sizeof(float));
PBCorr_Matr = (float ***) calloc( HAVE_ROIS, sizeof(float **) );
for ( i=0 ; i<HAVE_ROIS ; i++ )
PBCorr_Matr[i] = (float **) calloc( NROI_REF[i], sizeof(float *) );
for ( i=0 ; i <HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i] ; j++ )
PBCorr_Matr[i][j] = (float *) calloc( NROI_REF[i], sizeof(float));
if( (PCorr_Matr == NULL) || (PBCorr_Matr == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
}
// reuse this to help place list indices
for( i=0 ; i<HAVE_ROIS ; i++ )
for( j=0 ; j<NROI_REF[i] ; j++ )
ROI_COUNT[i][j] = 0;
INFO_message("Getting volumes.");
for( m=0 ; m<HAVE_ROIS ; m++ ) {
idx=0;
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
if( (THD_get_voxel(ROIS,idx,m) > 0) && mskd[i][j][k] ) {
mm = INV_LABELS_REF[m][(int) THD_get_voxel(ROIS,idx,m)]-1;
ROI_LISTS[m][mm][ROI_COUNT[m][mm]] = idx;
ROI_COUNT[m][mm]++;
}
idx++;
}
}
}
// bit of freeing
for( i=0 ; i<Dim[0] ; i++)
for( j=0 ; j<Dim[1] ; j++) {
free(mskd[i][j]);
}
for( i=0 ; i<Dim[0] ; i++) {
free(mskd[i]);
}
free(mskd);
INFO_message("Calculating average time series.");
// ROI values
for(i=0 ; i<HAVE_ROIS ; i++)
for( j=0 ; j<NROI_REF[i] ; j++ ) {
Nlist[0]=ROI_COUNT[i][j];
k = CalcAveRTS(ROI_LISTS[i][j], ROI_AVE_TS[i][j],
insetTIME, Dim, Nlist);
}
INFO_message("Calculating correlation matrix.");
if(PART_CORR)
INFO_message("... and calculating partial correlation matrix.");
for(i=0 ; i<HAVE_ROIS ; i++) {
for( j=0 ; j<NROI_REF[i] ; j++ )
for( k=j ; k<NROI_REF[i] ; k++ ) {
Corr_Matr[i][j][k] = Corr_Matr[i][k][j] = (float)
CORR_FUN(ROI_AVE_TS[i][j], ROI_AVE_TS[i][k], Dim[3]);
}
if(PART_CORR)
mm = CalcPartCorrMatr(PCorr_Matr[i], PBCorr_Matr[i],
Corr_Matr[i], NROI_REF[i]);
}
// **************************************************************
// **************************************************************
// Store and output
// **************************************************************
// **************************************************************
INFO_message("Writing output: %s ...", prefix);
// - - - - - - - - NIML prep - - - - - - - - - - - - - -
if(FISH_OUT)
Noutmat++;
if(PART_CORR)
Noutmat+=2;
ParLab = (char **)calloc(Noutmat, sizeof(char *));
for (j=0; j<Noutmat; ++j)
ParLab[j] = (char *)calloc(32, sizeof(char));
if( (ParLab == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(121);
}
// NIML output
flat_matr = (float ***) calloc( HAVE_ROIS, sizeof(float **) );
for ( i = 0 ; i < HAVE_ROIS ; i++ )
flat_matr[i] = (float **) calloc( Noutmat, sizeof(float *) );
for ( i = 0 ; i < HAVE_ROIS ; i++ )
for ( j = 0 ; j < Noutmat ; j++ )
flat_matr[i][j] = (float *) calloc( NROI_REF[i]*NROI_REF[i],
sizeof(float));
gdset_roi_names = (char ***)calloc(HAVE_ROIS, sizeof(char **));
for (i=0; i< HAVE_ROIS ; i++ ) {
gdset_roi_names[i] = (char **)calloc(NROI_REF[i], sizeof(char *));
for (j=0; j<NROI_REF[i]; ++j) {
gdset_roi_names[i][j] = (char *)calloc(32, sizeof(char));
if( OLD_LABEL )
snprintf(gdset_roi_names[i][j],31,"N%03d:R%d", i,
ROI_LABELS_REF[i][j]);
else{
snprintf(gdset_roi_names[i][j],31,"%s",
ROI_STR_LABELS[i][j+1]);
//fprintf(stderr," %s ",
// ROI_STR_LABELS[i][j+1]);
}
}
}
if( (flat_matr == NULL) || ( gdset_roi_names == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(14);
}
for( k=0 ; k<HAVE_ROIS ; k++) { // each netw gets own file
sprintf(OUT_grid,"%s_%03d.netcc",prefix,k); // zero counting now
if( (fout1 = fopen(OUT_grid, "w")) == NULL) {
fprintf(stderr, "Error opening file %s.",OUT_grid);
exit(19);
}
// same format as .grid files now
fprintf(fout1,"# %d # Number of network ROIs\n",NROI_REF[k]); // NROIs
fprintf(fout1,"# %d # Number of netcc matrices\n",
FISH_OUT+PART_CORR+1); // Num of params
// Sept 2014: label_table stuff
// don't need labeltable to make them, can do anyways
fprintf(fout1, "# WITH_ROI_LABELS\n");
for( i=1 ; i<NROI_REF[k] ; i++ )
fprintf(fout1," %10s \t",ROI_STR_LABELS[k][i]);
fprintf(fout1," %10s\n",ROI_STR_LABELS[k][i]);
// THIS IS FOR KNOWING WHICH MATR WE'RE AT
// it's always zero for CC; they match one-to-one with later vars
FM_ctr = 0;
ParLab[FM_ctr] = strdup("CC");
for( i=1 ; i<NROI_REF[k] ; i++ ) // labels of ROIs
fprintf(fout1," %10d \t",ROI_LABELS_REF[k][i]);// at =NROI, have '\n'
fprintf(fout1," %10d\n# %s\n",ROI_LABELS_REF[k][i],"CC");
for( i=0 ; i<NROI_REF[k] ; i++ ) {
for( j=0 ; j<NROI_REF[k]-1 ; j++ ) {// b/c we put '\n' after last one.
fprintf(fout1,"%12.4f\t",Corr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = Corr_Matr[k][i][j];
}
fprintf(fout1,"%12.4f\n",Corr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = Corr_Matr[k][i][j];
}
if(FISH_OUT) {
FM_ctr++;
ParLab[FM_ctr] = strdup("FZ");
fprintf(fout1,"# %s\n", "FZ");
for( i=0 ; i<NROI_REF[k] ; i++ ) {
for( j=0 ; j<NROI_REF[k]-1 ; j++ ) {// b/c we put '\n' after last
fprintf(fout1,"%12.4f\t",BOBatanhf(Corr_Matr[k][i][j]));
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] =
BOBatanhf(Corr_Matr[k][i][j]);
/* fprintf(fout1,"%12.4f\t",FisherZ(Corr_Matr[k][i][j]));
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] =
FisherZ(Corr_Matr[k][i][j]);*/
}
fprintf(fout1,"%12.4f\n",BOBatanhf(Corr_Matr[k][i][j]));
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] =
BOBatanhf(Corr_Matr[k][i][j]);
/*fprintf(fout1,"%12.4f\n",FisherZ(Corr_Matr[k][i][j]));
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] =
FisherZ(Corr_Matr[k][i][j]);*/
}
}
if(PART_CORR) {
FM_ctr++;
ParLab[FM_ctr] = strdup("PC");
fprintf(fout1,"# %s\n", "PC");
for( i=0 ; i<NROI_REF[k] ; i++ ) {
for( j=0 ; j<NROI_REF[k]-1 ; j++ ) {// b/c we put '\n' after last
fprintf(fout1,"%12.4f\t",PCorr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = PCorr_Matr[k][i][j];
}
fprintf(fout1,"%12.4f\n",PCorr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = PCorr_Matr[k][i][j];
}
FM_ctr++;
ParLab[FM_ctr] = strdup("PCB");
fprintf(fout1,"# %s\n", "PCB");
for( i=0 ; i<NROI_REF[k] ; i++ ) {
for( j=0 ; j<NROI_REF[k]-1 ; j++ ) {// b/c we put '\n' after last
fprintf(fout1,"%12.4f\t",PBCorr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = PBCorr_Matr[k][i][j];
}
fprintf(fout1,"%12.4f\n",PBCorr_Matr[k][i][j]);
flat_matr[k][FM_ctr][i*NROI_REF[k]+j] = PBCorr_Matr[k][i][j];
}
}
fclose(fout1);
// more nimling
gset = SUMA_FloatVec_to_GDSET(flat_matr[k], Noutmat,
NROI_REF[k]*NROI_REF[k],
"full", ParLab,
NULL, NULL, NULL);
if( xyz = THD_roi_cmass(ROIS, k, ROI_LABELS_REF[k]+1, NROI_REF[k]) ) {
if (!(SUMA_AddGDsetNodeListElement(gset, NULL,
xyz, NULL, NULL,
gdset_roi_names[k],
NULL, NULL,
NROI_REF[k]))) {
ERROR_message("Failed to add node list");
exit(1);
}
free(xyz);
}
else {
ERROR_message("Failed in THD_roi_cmass"); exit(1);
}
sprintf(OUT_gdset,"%s_%03d",prefix,k);
GDSET_netngrlink =
Network_link(SUMA_FnameGet( OUT_gdset, "f",NULL));
NI_add_to_group(gset->ngr, GDSET_netngrlink);
NAME_gdset = SUMA_WriteDset_ns( OUT_gdset,
gset, SUMA_ASCII_NIML, 1, 0);
if (!NAME_gdset && !SUMA_IS_DSET_STDXXX_FORMAT(SUMA_ASCII_NIML)) {
ERROR_message("Failed to write dataset."); exit(1);
} else {
if (NAME_gdset) SUMA_free(NAME_gdset); NAME_gdset = NULL;
}
SUMA_FreeDset(gset);
gset=NULL;
}
if(TS_OUT) {
for( k=0 ; k<HAVE_ROIS ; k++) { // each netw gets own file
sprintf(OUT_grid,"%s_%03d.netts",prefix,k);
if( (fout1 = fopen(OUT_grid, "w")) == NULL) {
fprintf(stderr, "Error opening file %s.",OUT_grid);
exit(19);
}
for( i=0 ; i<NROI_REF[k] ; i++ ) {
if(TS_LABEL)
fprintf(fout1,"%d\t",ROI_LABELS_REF[k][i+1]); // labels go 1...M
for( j=0 ; j<Dim[3]-1 ; j++ ) // b/c we put '\n' after last one.
fprintf(fout1,"%.3e\t",ROI_AVE_TS[k][i][j]);
fprintf(fout1,"%.3e\n",ROI_AVE_TS[k][i][j]);
}
fclose(fout1);
}
}
if( TS_INDIV ) {
for( k=0 ; k<HAVE_ROIS ; k++) { // each netw gets own file
sprintf(OUT_indiv0,"%s_%03d_INDIV", prefix, k);
mkdir(OUT_indiv0, 0777);
for( i=0 ; i<NROI_REF[k] ; i++ ) {
sprintf(OUT_indiv,"%s/ROI_%03d.netts",
OUT_indiv0,ROI_LABELS_REF[k][i+1]);
if( (fout2 = fopen(OUT_indiv, "w")) == NULL) {
fprintf(stderr, "\nError opening file '%s'.\n",OUT_indiv);
exit(19);
}
for( j=0 ; j<Dim[3]-1 ; j++ ) // b/c we put '\n' after last one.
fprintf(fout2,"%.3e\t",ROI_AVE_TS[k][i][j]);
fprintf(fout2,"%.3e\n",ROI_AVE_TS[k][i][j]);
fclose(fout2);
}
}
}
if( TS_WBCORR_r || TS_WBCORR_Z ) {
INFO_message("Starting whole brain correlations.");
i = WB_netw_corr( TS_WBCORR_r,
TS_WBCORR_Z,
HAVE_ROIS,
prefix,
NIFTI_OUT,
NROI_REF,
Dim,
ROI_AVE_TS,
ROI_LABELS_REF,
insetTIME,
mskd2,
Nmask,
argc,
argv);
}
// ************************************************************
// ************************************************************
// Freeing
// ************************************************************
// ************************************************************
DSET_delete(ROIS);
free(ROIS);
for ( i = 0 ; i < HAVE_ROIS ; i++ ) {
for (j = 0; j < NROI_REF[i]; ++j)
free(gdset_roi_names[i][j]);
free(gdset_roi_names[i]);
}
free(gdset_roi_names);
for ( i = 0 ; i < HAVE_ROIS ; i++ )
for ( j = 0 ; j < Noutmat ; j++ )
free(flat_matr[i][j]);
for ( i = 0 ; i < HAVE_ROIS ; i++ )
free(flat_matr[i]);
free(flat_matr);
for( i=0 ; i<Noutmat ; i++)
free(ParLab[i]);
free(ParLab);
if(LabTabStr)
free(LabTabStr);
if(roi_dtable)
free(roi_dtable);
for ( i=0 ; i<HAVE_ROIS ; i++ )
for ( j=0 ; j<NROI_REF[i]+1 ; j++ )
free(ROI_STR_LABELS[i][j]);
for ( i=0 ; i<HAVE_ROIS ; i++ )
free(ROI_STR_LABELS[i]);
free(ROI_STR_LABELS);
DSET_delete(insetTIME);
free(insetTIME);
free(mskd2);
free(Nlist);
free(Dim); // need to free last because it's used for other arrays...
free(prefix);
// if(HAVE_SELROI)
// free(SELROI);
if(HAVE_ROIS >0) {
for( i=0 ; i<HAVE_ROIS ; i++) {
for( j=0 ; j<NROI_REF[i] ; j++) {
free(ROI_LISTS[i][j]);
free(ROI_AVE_TS[i][j]);
free(Corr_Matr[i][j]);
if(PART_CORR) {
free(PCorr_Matr[i][j]);
free(PBCorr_Matr[i][j]);
}
}
free(ROI_LISTS[i]);
free(ROI_AVE_TS[i]);
free(Corr_Matr[i]);
if(PART_CORR){
free(PCorr_Matr[i]);
free(PBCorr_Matr[i]);
}
free(ROI_LABELS_REF[i]);
free(INV_LABELS_REF[i]);
free(ROI_COUNT[i]);
}
free(ROI_LISTS);
free(ROI_AVE_TS);
free(Corr_Matr);
if(PART_CORR) {
free(PCorr_Matr);
free(PBCorr_Matr);
}
free(ROI_LABELS_REF);
free(INV_LABELS_REF);
free(ROI_COUNT);
free(NROI_REF);
free(INVROI_REF);
}
return 0;
}
int main( int argc , char *argv[] )
{
int iarg=1 , ii,nvox , nvals ;
THD_3dim_dataset *inset=NULL, *outset=NULL , *mset=NULL ;
char *prefix="./blurinmask" ;
float fwhm_goal=0.0f ; int fwhm_2D=0 ;
byte *mask=NULL ; int mask_nx=0,mask_ny=0,mask_nz=0 , automask=0 , nmask=0 ;
float dx,dy,dz=0.0f , *bar , val ;
int floatize=0 ; /* 18 May 2009 */
MRI_IMAGE *immask=NULL ; /* 07 Oct 2009 */
short *mmask=NULL ;
short *unval_mmask=NULL ; int nuniq_mmask=0 ;
int do_preserve=0 , use_qsar ; /* 19 Oct 2009 */
THD_3dim_dataset *fwhmset=NULL ;
MRI_IMAGE *fxim=NULL, *fyim=NULL, *fzim=NULL ; /* 13 Jun 2016 */
int niter_fxyz=0 ; float dmax=0.0f , dmin=0.0f ;
/*------- help the pitifully ignorant luser? -------*/
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf(
"Usage: ~1~\n"
"3dBlurInMask [options]\n"
"Blurs a dataset spatially inside a mask. That's all. Experimental.\n"
"\n"
"OPTIONS ~1~\n"
"-------\n"
" -input ddd = This required 'option' specifies the dataset\n"
" that will be smoothed and output.\n"
" -FWHM f = Add 'f' amount of smoothness to the dataset (in mm).\n"
" **N.B.: This is also a required 'option'.\n"
" -FWHMdset d = Read in dataset 'd' and add the amount of smoothness\n"
" given at each voxel -- spatially variable blurring.\n"
" ** EXPERIMENTAL EXPERIMENTAL EXPERIMENTAL **\n"
" -mask mmm = Mask dataset, if desired. Blurring will\n"
" occur only within the mask. Voxels NOT in\n"
" the mask will be set to zero in the output.\n"
" -Mmask mmm = Multi-mask dataset -- each distinct nonzero\n"
" value in dataset 'mmm' will be treated as\n"
" a separate mask for blurring purposes.\n"
" **N.B.: 'mmm' must be byte- or short-valued!\n"
" -automask = Create an automask from the input dataset.\n"
" **N.B.: only 1 masking option can be used!\n"
" -preserve = Normally, voxels not in the mask will be\n"
" set to zero in the output. If you want the\n"
" original values in the dataset to be preserved\n"
" in the output, use this option.\n"
" -prefix ppp = Prefix for output dataset will be 'ppp'.\n"
" **N.B.: Output dataset is always in float format.\n"
" -quiet = Don't be verbose with the progress reports.\n"
" -float = Save dataset as floats, no matter what the\n"
" input data type is.\n"
" **N.B.: If the input dataset is unscaled shorts, then\n"
" the default is to save the output in short\n"
" format as well. In EVERY other case, the\n"
" program saves the output as floats. Thus,\n"
" the ONLY purpose of the '-float' option is to\n"
" force an all-shorts input dataset to be saved\n"
" as all-floats after blurring.\n"
"\n"
"NOTES ~1~\n"
"-----\n"
" * If you don't provide a mask, then all voxels will be included\n"
" in the blurring. (But then why are you using this program?)\n"
" * Note that voxels inside the mask that are not contiguous with\n"
" any other voxels inside the mask will not be modified at all!\n"
" * Works iteratively, similarly to 3dBlurToFWHM, but without\n"
" the extensive overhead of monitoring the smoothness.\n"
" * But this program will be faster than 3dBlurToFWHM, and probably\n"
" slower than 3dmerge.\n"
" * Since the blurring is done iteratively, rather than all-at-once as\n"
" in 3dmerge, the results will be slightly different than 3dmerge's,\n"
" even if no mask is used here (3dmerge, of course, doesn't take a mask).\n"
" * If the original FWHM of the dataset was 'S' and you input a value\n"
" 'F' with the '-FWHM' option, then the output dataset's smoothness\n"
" will be about sqrt(S*S+F*F). The number of iterations will be\n"
" about (F*F/d*d) where d=grid spacing; this means that a large value\n"
" of F might take a lot of CPU time!\n"
" * The spatial smoothness of a 3D+time dataset can be estimated with a\n"
" command similar to the following:\n"
" 3dFWHMx -detrend -mask mmm+orig -input ddd+orig\n"
) ;
printf(
" * The minimum number of voxels in the mask is %d\n",MASK_MIN) ;
printf(
" * Isolated voxels will be removed from the mask!\n") ;
PRINT_AFNI_OMP_USAGE("3dBlurInMask",NULL) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
/*---- official startup ---*/
PRINT_VERSION("3dBlurInMask"); mainENTRY("3dBlurInMask main"); machdep();
AFNI_logger("3dBlurInMask",argc,argv); AUTHOR("RW Cox") ;
/*---- loop over options ----*/
while( iarg < argc && argv[iarg][0] == '-' ){
if( strncmp(argv[iarg],"-preserve",5) == 0 ){ /* 19 Oct 2009 */
do_preserve = 1 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-qui",4) == 0 ){
verb = 0 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-ver",4) == 0 ){
verb++ ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-input") == 0 || strcmp(argv[iarg],"-dset") == 0 ){
if( inset != NULL ) ERROR_exit("Can't have two -input options") ;
if( ++iarg >= argc ) ERROR_exit("Need argument after '-input'") ;
inset = THD_open_dataset( argv[iarg] );
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-prefix") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '-prefix'") ;
prefix = strdup(argv[iarg]) ;
if( !THD_filename_ok(prefix) ) ERROR_exit("Bad name after '-prefix'") ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-Mmask") == 0 ){ /* 07 Oct 2009 */
if( ++iarg >= argc ) ERROR_exit("Need argument after '-Mmask'") ;
if( mmask != NULL || mask != NULL || automask ) ERROR_exit("Can't have two mask inputs") ;
mset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(mset,argv[iarg]) ;
DSET_load(mset) ; CHECK_LOAD_ERROR(mset) ;
mask_nx = DSET_NX(mset); mask_ny = DSET_NY(mset); mask_nz = DSET_NZ(mset);
#if 0
if( !MRI_IS_INT_TYPE(DSET_BRICK_TYPE(mset,0)) )
ERROR_exit("-Mmask dataset is not integer type!") ;
#endif
immask = mri_to_short( 1.0 , DSET_BRICK(mset,0) ) ;
mmask = MRI_SHORT_PTR(immask) ;
unval_mmask = UniqueShort( mmask, mask_nx*mask_ny*mask_nz, &nuniq_mmask, 0 ) ;
if( unval_mmask == NULL || nuniq_mmask == 0 )
ERROR_exit("-Mmask dataset cannot be processed!?") ;
if( nuniq_mmask == 1 && unval_mmask[0] == 0 )
ERROR_exit("-Mmask dataset is all zeros!?") ;
if( verb ){
int qq , ww ;
for( ii=qq=0 ; ii < nuniq_mmask ; ii++ ) if( unval_mmask[ii] != 0 ) qq++ ;
for( ii=ww=0 ; ii < immask->nvox ; ii++ ) if( mmask[ii] != 0 ) ww++ ;
INFO_message("%d unique nonzero values in -Mmask; %d nonzero voxels",qq,ww) ;
}
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-mask") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '-mask'") ;
if( mmask != NULL || mask != NULL || automask ) ERROR_exit("Can't have two mask inputs") ;
mset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(mset,argv[iarg]) ;
DSET_load(mset) ; CHECK_LOAD_ERROR(mset) ;
mask_nx = DSET_NX(mset); mask_ny = DSET_NY(mset); mask_nz = DSET_NZ(mset);
mask = THD_makemask( mset , 0 , 0.5f, 0.0f ) ; DSET_unload(mset) ;
if( mask == NULL ) ERROR_exit("Can't make mask from dataset '%s'",argv[iarg]) ;
ii = THD_mask_remove_isolas( mask_nx,mask_ny,mask_nz , mask ) ;
if( verb && ii > 0 ) INFO_message("Removed %d isola%s from mask dataset",ii,(ii==1)?"\0":"s") ;
nmask = THD_countmask( mask_nx*mask_ny*mask_nz , mask ) ;
if( verb ) INFO_message("Number of voxels in mask = %d",nmask) ;
if( nmask < MASK_MIN ) ERROR_exit("Mask is too small to process") ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-automask") == 0 ){
if( mmask != NULL || mask != NULL ) ERROR_exit("Can't have 2 mask inputs") ;
automask = 1 ; iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-FWHM") == 0 || strcasecmp(argv[iarg],"-FHWM") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]);
val = (float)strtod(argv[iarg],NULL) ;
if( val <= 0.0f ) ERROR_exit("Illegal value after '%s': '%s'",
argv[iarg-1],argv[iarg]) ;
fwhm_goal = val ; fwhm_2D = 0 ;
iarg++ ; continue ;
}
if( strcasecmp(argv[iarg],"-FWHMdset") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]);
if( fwhmset != NULL ) ERROR_exit("You can't use option '-FWHMdset' twice :(") ;
fwhmset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(fwhmset,argv[iarg]) ;
do_preserve = 1 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-float",6) == 0 ){ /* 18 May 2009 */
floatize = 1 ; iarg++ ; continue ;
}
#if 0
if( strcmp(argv[iarg],"-FWHMxy") == 0 || strcmp(argv[iarg],"-FHWMxy") == 0 ){
if( ++iarg >= argc ) ERROR_exit("Need argument after '%s'",argv[iarg-1]);
val = (float)strtod(argv[iarg],NULL) ;
if( val <= 0.0f ) ERROR_exit("Illegal value after '%s': '%s'",
argv[iarg-1],argv[iarg]) ;
fwhm_goal = val ; fwhm_2D = 1 ;
iarg++ ; continue ;
}
#endif
ERROR_exit("Uknown option '%s'",argv[iarg]) ;
} /*--- end of loop over options ---*/
/*----- check for stupid inputs, load datasets, et cetera -----*/
if( fwhmset == NULL && fwhm_goal == 0.0f )
ERROR_exit("No -FWHM option given! What do you want?") ;
if( fwhmset != NULL && fwhm_goal > 0.0f ){
WARNING_message("-FWHMdset option replaces -FWHM value") ;
fwhm_goal = 0.0f ;
}
if( fwhmset != NULL && mmask != NULL )
ERROR_exit("Sorry: -FWHMdset and -Mmask don't work together (yet)") ;
if( inset == NULL ){
if( iarg >= argc ) ERROR_exit("No input dataset on command line?") ;
inset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(inset,argv[iarg]) ;
}
nvox = DSET_NVOX(inset) ;
dx = fabs(DSET_DX(inset)) ; if( dx == 0.0f ) dx = 1.0f ;
dy = fabs(DSET_DY(inset)) ; if( dy == 0.0f ) dy = 1.0f ;
dz = fabs(DSET_DZ(inset)) ; if( dz == 0.0f ) dz = 1.0f ;
dmax = MAX(dx,dy) ; if( dmax < dz ) dmax = dz ; /* 13 Jun 2016 */
dmin = MIN(dx,dy) ; if( dmin > dz ) dmin = dz ;
if( !floatize ){ /* 18 May 2009 */
if( !THD_datum_constant(inset->dblk) ||
THD_need_brick_factor(inset) ||
DSET_BRICK_TYPE(inset,0) != MRI_short ){
if( verb ) INFO_message("forcing output to be stored in float format") ;
floatize = 1 ;
} else {
if( verb ) INFO_message("output dataset will be stored as shorts") ;
}
} else {
if( verb ) INFO_message("output dataset will be stored as floats") ;
}
#if 0
if( DSET_NZ(inset) == 1 && !fwhm_2D ){
WARNING_message("Dataset is 2D ==> switching from -FWHM to -FWHMxy") ;
fwhm_2D = 1 ;
}
#endif
/*--- deal with mask or automask ---*/
if( mask != NULL ){
if( mask_nx != DSET_NX(inset) ||
mask_ny != DSET_NY(inset) ||
mask_nz != DSET_NZ(inset) )
ERROR_exit("-mask dataset grid doesn't match input dataset") ;
} else if( automask ){
mask = THD_automask( inset ) ;
if( mask == NULL )
ERROR_message("Can't create -automask from input dataset?") ;
nmask = THD_countmask( DSET_NVOX(inset) , mask ) ;
if( verb ) INFO_message("Number of voxels in automask = %d",nmask);
if( nmask < MASK_MIN ) ERROR_exit("Automask is too small to process") ;
} else if( mmask != NULL ){
if( mask_nx != DSET_NX(inset) ||
mask_ny != DSET_NY(inset) ||
mask_nz != DSET_NZ(inset) )
ERROR_exit("-Mmask dataset grid doesn't match input dataset") ;
} else {
mask = (byte *)malloc(sizeof(byte)*nvox) ; nmask = nvox ;
memset(mask,1,sizeof(byte)*nvox) ;
if( verb ) INFO_message("No mask ==> processing all %d voxels",nvox);
}
/*--- process FWHMdset [13 Jun 2016] ---*/
if( fwhmset != NULL ){
float *fxar,*fyar,*fzar , *fwar ; MRI_IMAGE *fwim ;
float fwmax=0.0f , fsx,fsy,fsz ; int ii, nfpos=0 ;
if( DSET_NX(inset) != DSET_NX(fwhmset) ||
DSET_NY(inset) != DSET_NY(fwhmset) ||
DSET_NZ(inset) != DSET_NZ(fwhmset) )
ERROR_exit("grid dimensions for FWHMdset and input dataset do not match :(") ;
STATUS("get fwim") ;
DSET_load(fwhmset) ;
fwim = mri_scale_to_float(DSET_BRICK_FACTOR(fwhmset,0),DSET_BRICK(fwhmset,0));
fwar = MRI_FLOAT_PTR(fwim);
DSET_unload(fwhmset) ;
STATUS("process fwar") ;
for( ii=0 ; ii < nvox ; ii++ ){
if( mask[ii] && fwar[ii] > 0.0f ){
nfpos++ ;
if( fwar[ii] > fwmax ) fwmax = fwar[ii] ;
} else {
fwar[ii] = 0.0f ; mask[ii] = 0 ;
}
}
if( nfpos < 100 )
ERROR_exit("Cannot proceed: too few (%d) voxels are positive in -FWHMdset!",nfpos) ;
niter_fxyz = (int)rintf(2.0f*fwmax*fwmax*FFAC/(0.05f*dmin*dmin)) + 1 ;
if( verb ) INFO_message("-FWHMdset: niter=%d npos=%d",niter_fxyz,nfpos) ;
STATUS("create fxim etc.") ;
fxim = mri_new_conforming(fwim,MRI_float); fxar = MRI_FLOAT_PTR(fxim);
fyim = mri_new_conforming(fwim,MRI_float); fyar = MRI_FLOAT_PTR(fyim);
fzim = mri_new_conforming(fwim,MRI_float); fzar = MRI_FLOAT_PTR(fzim);
fsx = FFAC/(dx*dx*niter_fxyz) ;
fsy = FFAC/(dy*dy*niter_fxyz) ;
fsz = FFAC/(dz*dz*niter_fxyz) ;
/** INFO_message("fsx=%g fsy=%g fsz=%g",fsx,fsy,fsz) ; **/
for( ii=0 ; ii < nvox ; ii++ ){
if( fwar[ii] > 0.0f ){
fxar[ii] = fwar[ii]*fwar[ii] * fsx ;
fyar[ii] = fwar[ii]*fwar[ii] * fsy ;
fzar[ii] = fwar[ii]*fwar[ii] * fsz ;
} else {
fxar[ii] = fyar[ii] = fzar[ii] = 0.0f ;
}
}
STATUS("free(fwim)") ;
mri_free(fwim) ;
}
/*--- process input dataset ---*/
STATUS("load input") ;
DSET_load(inset) ; CHECK_LOAD_ERROR(inset) ;
outset = EDIT_empty_copy( inset ) ; /* moved here 04 Jun 2007 */
EDIT_dset_items( outset , ADN_prefix , prefix , ADN_none ) ;
EDIT_dset_items( outset , ADN_brick_fac , NULL , ADN_none ) ; /* 11 Sep 2007 */
tross_Copy_History( inset , outset ) ;
tross_Make_History( "3dBlurInMask" , argc,argv , outset ) ;
nvals = DSET_NVALS(inset) ;
use_qsar = (do_preserve || mmask != NULL) ; /* 19 Oct 20090 */
AFNI_OMP_START ;
#pragma omp parallel if( nvals > 1 )
{
MRI_IMAGE *dsim ; int ids,qit ; byte *qmask=NULL ; register int vv ;
MRI_IMAGE *qim=NULL, *qsim=NULL; float *qar=NULL, *dsar, *qsar=NULL;
#pragma omp critical (MALLOC)
{ if( use_qsar ){
qsim = mri_new_conforming(DSET_BRICK(inset,0),MRI_float); qsar = MRI_FLOAT_PTR(qsim);
}
if( mmask != NULL ){
qmask = (byte *)malloc(sizeof(byte)*nvox) ;
qim = mri_new_conforming(immask,MRI_float); qar = MRI_FLOAT_PTR(qim);
qim->dx = dx ; qim->dy = dy ; qim->dz = dz ;
}
}
#pragma omp for
for( ids=0 ; ids < nvals ; ids++ ){
#pragma omp critical (MALLOC)
{ dsim = mri_scale_to_float(DSET_BRICK_FACTOR(inset,ids),DSET_BRICK(inset,ids));
DSET_unload_one(inset,ids) ;
}
dsim->dx = dx ; dsim->dy = dy ; dsim->dz = dz ; dsar = MRI_FLOAT_PTR(dsim) ;
/* if needed, initialize qsar with data to be preserved in output */
if( do_preserve ){
for( vv=0 ; vv < nvox ; vv++ ) qsar[vv] = dsar[vv] ;
} else if( mmask != NULL ){
for( vv=0 ; vv < nvox ; vv++ ) qsar[vv] = 0.0f ;
}
if( fwhmset != NULL ){ /* 13 Jun 2016: spatially variable blurring */
for( qit=0 ; qit < niter_fxyz ; qit++ ){
mri_blur3D_variable( dsim , mask , fxim,fyim,fzim ) ;
}
if( do_preserve ){
for( vv=0 ; vv < nvox ; vv++ ) if( mask[vv] ) qsar[vv] = dsar[vv] ;
}
} else if( mmask != NULL ){ /* 07 Oct 2009: multiple masks */
int qq ; register short uval ;
for( qq=0 ; qq < nuniq_mmask ; qq++ ){
uval = unval_mmask[qq] ; if( uval == 0 ) continue ;
for( vv=0 ; vv < nvox ; vv++ ) qmask[vv] = (mmask[vv]==uval) ; /* make mask */
(void)THD_mask_remove_isolas( mask_nx,mask_ny,mask_nz , qmask ) ;
nmask = THD_countmask( nvox , qmask ) ;
if( verb && ids==0 ) ININFO_message("voxels in Mmask[%d] = %d",uval,nmask) ;
if( nmask >= MASK_MIN ){
/* copy data from dataset to qar */
for( vv=0 ; vv < nvox ; vv++ ) if( qmask[vv] ) qar[vv] = dsar[vv] ;
/* blur qar (output will be zero where qmask==0) */
mri_blur3D_addfwhm( qim , qmask , fwhm_goal ) ; /** the real work **/
/* copy results back to qsar */
for( vv=0 ; vv < nvox ; vv++ ) if( qmask[vv] ) qsar[vv] = qar[vv] ;
}
}
} else { /* the olden way: 1 mask */
mri_blur3D_addfwhm( dsim , mask , fwhm_goal ) ; /** all the work **/
/* dsim will be zero where mask==0;
if we want to preserve the input values, copy dsar into qsar now
at all mask!=0 voxels, since qsar contains the original data values */
if( do_preserve ){
for( vv=0 ; vv < nvox ; vv++ ) if( mask[vv] ) qsar[vv] = dsar[vv] ;
}
}
/* if necessary, copy combined results in qsar to dsar for output */
if( use_qsar ){
for( vv=0 ; vv < nvox ; vv++ ) dsar[vv] = qsar[vv] ;
}
if( floatize ){
EDIT_substitute_brick( outset , ids , MRI_float , dsar ) ;
} else {
#pragma omp critical (MALLOC)
{ EDIT_substscale_brick( outset , ids , MRI_float , dsar ,
MRI_short , 1.0f ) ;
mri_free(dsim) ;
}
}
} /* end of loop over sub-bricks */
#pragma omp critical (MALLOC)
{ if( qsim != NULL ) mri_free(qsim);
if( immask != NULL ){ free(qmask); mri_free(qim); }
}
} /* end OpenMP */
AFNI_OMP_END ;
if( mask != NULL ) free( mask) ;
if( immask != NULL ) mri_free(immask) ;
DSET_unload(inset) ;
DSET_write(outset) ;
WROTE_DSET(outset) ;
exit(0) ;
}
int main( int argc , char *argv[] )
{
THD_3dim_dataset *dset , *oset=NULL , *tset=NULL ;
int nvals , iv , nxyz , ii,jj,kk , iarg , kz,kzold ;
float cut1=2.5,cut2=4.0 , sq2p,sfac , fq ;
MRI_IMAGE *flim ;
char *prefix="despike" , *tprefix=NULL ;
int corder=-1 , nref , ignore=0 , polort=2 , nuse , nomask=0 ;
int nspike, nbig, nproc ;
float **ref ;
float c21,ic21 , pspike,pbig ;
short *sar , *qar ;
byte *tar , *mask=NULL ;
float *zar , *yar ;
int datum ;
int localedit=0 ; /* 04 Apr 2007 */
int verb=1 ;
int do_NEW = 0 ; /* 29 Nov 2013 */
MRI_IMAGE *NEW_psinv=NULL ;
int dilate = 4 ; /* 04 Dec 2013 */
int ctim = 0 ;
/*----- Read command line -----*/
AFNI_SETUP_OMP(0) ; /* 24 Jun 2013 */
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf("Usage: 3dDespike [options] dataset\n"
"Removes 'spikes' from the 3D+time input dataset and writes\n"
"a new dataset with the spike values replaced by something\n"
"more pleasing to the eye.\n"
"\n"
"Method:\n"
" * L1 fit a smooth-ish curve to each voxel time series\n"
" [see -corder option for description of the curve]\n"
" [see -NEW option for a different & faster fitting method]\n"
" * Compute the MAD of the difference between the curve and\n"
" the data time series (the residuals).\n"
" * Estimate the standard deviation 'sigma' of the residuals\n"
" as sqrt(PI/2)*MAD.\n"
" * For each voxel value, define s = (value-curve)/sigma.\n"
" * Values with s > c1 are replaced with a value that yields\n"
" a modified s' = c1+(c2-c1)*tanh((s-c1)/(c2-c1)).\n"
" * c1 is the threshold value of s for a 'spike' [default c1=2.5].\n"
" * c2 is the upper range of the allowed deviation from the curve:\n"
" s=[c1..infinity) is mapped to s'=[c1..c2) [default c2=4].\n"
"\n"
"Options:\n"
" -ignore I = Ignore the first I points in the time series:\n"
" these values will just be copied to the\n"
" output dataset [default I=0].\n"
" -corder L = Set the curve fit order to L:\n"
" the curve that is fit to voxel data v(t) is\n"
"\n"
" k=L [ (2*PI*k*t) (2*PI*k*t) ]\n"
" f(t) = a+b*t+c*t*t + SUM [ d * sin(--------) + e * cos(--------) ]\n"
" k=1 [ k ( T ) k ( T ) ]\n"
"\n"
" where T = duration of time series;\n"
" the a,b,c,d,e parameters are chosen to minimize\n"
" the sum over t of |v(t)-f(t)| (L1 regression);\n"
" this type of fitting is is insensitive to large\n"
" spikes in the data. The default value of L is\n"
" NT/30, where NT = number of time points.\n"
"\n"
" -cut c1 c2 = Alter default values for the spike cut values\n"
" [default c1=2.5, c2=4.0].\n"
" -prefix pp = Save de-spiked dataset with prefix 'pp'\n"
" [default pp='despike']\n"
" -ssave ttt = Save 'spikiness' measure s for each voxel into a\n"
" 3D+time dataset with prefix 'ttt' [default=no save]\n"
" -nomask = Process all voxels\n"
" [default=use a mask of high-intensity voxels, ]\n"
" [as created via '3dAutomask -dilate 4 dataset'].\n"
" -dilate nd = Dilate 'nd' times (as in 3dAutomask). The default\n"
" value of 'nd' is 4.\n"
" -q[uiet] = Don't print '++' informational messages.\n"
"\n"
" -localedit = Change the editing process to the following:\n"
" If a voxel |s| value is >= c2, then replace\n"
" the voxel value with the average of the two\n"
" nearest non-spike (|s| < c2) values; the first\n"
" one previous and the first one after.\n"
" Note that the c1 cut value is not used here.\n"
"\n"
" -NEW = Use the 'new' method for computing the fit, which\n"
" should be faster than the L1 method for long time\n"
" series (200+ time points); however, the results\n"
" are similar but NOT identical. [29 Nov 2013]\n"
" * You can also make the program use the 'new'\n"
" method by setting the environment variable\n"
" AFNI_3dDespike_NEW\n"
" to the value YES; as in\n"
" setenv AFNI_3dDespike_NEW YES (csh)\n"
" export AFNI_3dDespike_NEW=YES (bash)\n"
" * If this variable is set to YES, you can turn off\n"
" the '-NEW' processing by using the '-OLD' option.\n"
" -->>* For time series more than 500 points long, the\n"
" '-OLD' algorithm is tremendously slow. You should\n"
" use the '-NEW' algorith in such cases.\n"
" ** At some indeterminate point in the future, the '-NEW'\n"
" method will become the default!\n"
" -->>* As of 29 Sep 2016, '-NEW' is the default if there\n"
" is more than 500 points in the time series dataset.\n"
"\n"
" -NEW25 = A slightly more aggressive despiking approach than\n"
" the '-NEW' method.\n"
"\n"
"Caveats:\n"
"* Despiking may interfere with image registration, since head\n"
" movement may produce 'spikes' at the edge of the brain, and\n"
" this information would be used in the registration process.\n"
" This possibility has not been explored or calibrated.\n"
"* [LATER] Actually, it seems like the registration problem\n"
" does NOT happen, and in fact, despiking seems to help!\n"
"* Check your data visually before and after despiking and\n"
" registration!\n"
" [Hint: open 2 AFNI controllers, and turn Time Lock on.]\n"
) ;
PRINT_AFNI_OMP_USAGE("3dDespike",NULL) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
/** AFNI package setup and logging **/
mainENTRY("3dDespike main"); machdep(); AFNI_logger("3dDespike",argc,argv);
PRINT_VERSION("3dDespike") ; AUTHOR("RW Cox") ;
/** parse options **/
if( AFNI_yesenv("AFNI_3dDespike_NEW") ) do_NEW = 1 ; /* 29 Nov 2013 */
iarg = 1 ;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strncmp(argv[iarg],"-q",2) == 0 ){ /* 04 Apr 2007 */
verb = 0 ; iarg++ ; continue ;
}
if( strncmp(argv[iarg],"-v",2) == 0 ){
verb++ ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-NEW") == 0 ){ /* 29 Nov 2013 */
do_NEW = 1 ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-NEW25") == 0 ){ /* 29 Sep 2016 */
do_NEW = 1 ; use_des25 = 1 ; cut1 = 2.5f ; cut2 = 3.2f ; iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-OLD") == 0 ){
do_NEW = 0 ; iarg++ ; continue ;
}
/** -localedit **/
if( strcmp(argv[iarg],"-localedit") == 0 ){ /* 04 Apr 2007 */
localedit = 1 ; iarg++ ; continue ;
}
/** don't use masking **/
if( strcmp(argv[iarg],"-nomask") == 0 ){
nomask = 1 ; iarg++ ; continue ;
}
/** dilation count [04 Dec 2013] **/
if( strcmp(argv[iarg],"-dilate") == 0 ){
dilate = (int)strtod(argv[++iarg],NULL) ;
if( dilate <= 0 ) dilate = 1 ;
else if( dilate > 99 ) dilate = 99 ;
iarg++ ; continue ;
}
/** output dataset prefix **/
if( strcmp(argv[iarg],"-prefix") == 0 ){
prefix = argv[++iarg] ;
if( !THD_filename_ok(prefix) ) ERROR_exit("-prefix is not good");
iarg++ ; continue ;
}
/** ratio dataset prefix **/
if( strcmp(argv[iarg],"-ssave") == 0 ){
tprefix = argv[++iarg] ;
if( !THD_filename_ok(tprefix) ) ERROR_exit("-ssave prefix is not good");
iarg++ ; continue ;
}
/** trigonometric polynomial order **/
if( strcmp(argv[iarg],"-corder") == 0 ){
corder = strtol( argv[++iarg] , NULL , 10 ) ;
if( corder < 0 ) ERROR_exit("Illegal value of -corder");
iarg++ ; continue ;
}
/** how much to ignore at start **/
if( strcmp(argv[iarg],"-ignore") == 0 ){
ignore = strtol( argv[++iarg] , NULL , 10 ) ;
if( ignore < 0 ) ERROR_exit("Illegal value of -ignore");
iarg++ ; continue ;
}
/** thresholds for s ratio **/
if( strcmp(argv[iarg],"-cut") == 0 ){
cut1 = strtod( argv[++iarg] , NULL ) ;
cut2 = strtod( argv[++iarg] , NULL ) ;
if( cut1 < 1.0 || cut2 < cut1+0.5 )
ERROR_exit("Illegal values after -cut");
iarg++ ; continue ;
}
ERROR_exit("Unknown option: %s",argv[iarg]) ;
}
c21 = cut2-cut1 ; ic21 = 1.0/c21 ;
/*----- read input dataset -----*/
if( iarg >= argc ) ERROR_exit("No input dataset!!??");
dset = THD_open_dataset( argv[iarg] ) ;
CHECK_OPEN_ERROR(dset,argv[iarg]) ;
datum = DSET_BRICK_TYPE(dset,0) ;
if( (datum != MRI_short && datum != MRI_float) || !DSET_datum_constant(dset) )
ERROR_exit("Can't process non-short, non-float dataset!") ;
if( verb ) INFO_message("Input data type = %s\n",MRI_TYPE_name[datum]) ;
nvals = DSET_NUM_TIMES(dset) ; nuse = nvals - ignore ;
if( nuse < 15 )
ERROR_exit("Can't use dataset with < 15 time points per voxel!") ;
if( nuse > 500 && !do_NEW ){
INFO_message("Switching to '-NEW' method since number of time points = %d > 500",nuse) ;
do_NEW = 1 ;
}
if( use_des25 && nuse < 99 ) use_des25 = 0 ;
if( verb ) INFO_message("ignoring first %d time points, using last %d",ignore,nuse);
if( corder > 0 && 4*corder+2 > nuse ){
ERROR_exit("-corder %d is too big for NT=%d",corder,nvals) ;
} else if( corder < 0 ){
corder = rint(nuse/30.0) ; if( corder > 50 && !do_NEW ) corder = 50 ;
if( verb ) INFO_message("using %d time points => -corder %d",nuse,corder) ;
} else {
if( verb ) INFO_message("-corder %d set from command line",corder) ;
}
nxyz = DSET_NVOX(dset) ;
if( verb ) INFO_message("Loading dataset %s",argv[iarg]) ;
DSET_load(dset) ; CHECK_LOAD_ERROR(dset) ;
/*-- create automask --*/
if( !nomask ){
mask = THD_automask( dset ) ;
if( verb ){
ii = THD_countmask( DSET_NVOX(dset) , mask ) ;
INFO_message("%d voxels in the automask [out of %d in dataset]",ii,DSET_NVOX(dset)) ;
}
for( ii=0 ; ii < dilate ; ii++ )
THD_mask_dilate( DSET_NX(dset), DSET_NY(dset), DSET_NZ(dset), mask, 3 ) ;
if( verb ){
ii = THD_countmask( DSET_NVOX(dset) , mask ) ;
INFO_message("%d voxels in the dilated automask [out of %d in dataset]",ii,DSET_NVOX(dset)) ;
}
} else {
if( verb ) INFO_message("processing all %d voxels in dataset",DSET_NVOX(dset)) ;
}
/*-- create empty despiked dataset --*/
oset = EDIT_empty_copy( dset ) ;
EDIT_dset_items( oset ,
ADN_prefix , prefix ,
ADN_brick_fac , NULL ,
ADN_datum_all , datum ,
ADN_none ) ;
if( THD_deathcon() && THD_is_file(DSET_HEADNAME(oset)) )
ERROR_exit("output dataset already exists: %s",DSET_HEADNAME(oset));
tross_Copy_History( oset , dset ) ;
tross_Make_History( "3dDespike" , argc , argv , oset ) ;
/* create bricks (will be filled with zeros) */
for( iv=0 ; iv < nvals ; iv++ )
EDIT_substitute_brick( oset , iv , datum , NULL ) ;
/* copy the ignored bricks */
switch( datum ){
case MRI_short:
for( iv=0 ; iv < ignore ; iv++ ){
sar = DSET_ARRAY(oset,iv) ;
qar = DSET_ARRAY(dset,iv) ;
memcpy( sar , qar , DSET_BRICK_BYTES(dset,iv) ) ;
DSET_unload_one(dset,iv) ;
}
break ;
case MRI_float:
for( iv=0 ; iv < ignore ; iv++ ){
zar = DSET_ARRAY(oset,iv) ;
yar = DSET_ARRAY(dset,iv) ;
memcpy( zar , yar , DSET_BRICK_BYTES(dset,iv) ) ;
DSET_unload_one(dset,iv) ;
}
break ;
}
/*-- setup to save a threshold statistic dataset, if desired --*/
if( tprefix != NULL ){
float *fac ;
tset = EDIT_empty_copy( dset ) ;
fac = (float *) malloc( sizeof(float) * nvals ) ;
for( ii=0 ; ii < nvals ; ii++ ) fac[ii] = TFAC ;
EDIT_dset_items( tset ,
ADN_prefix , tprefix ,
ADN_brick_fac , fac ,
ADN_datum_all , MRI_byte ,
ADN_func_type , FUNC_FIM_TYPE ,
ADN_none ) ;
free(fac) ;
tross_Copy_History( tset , dset ) ;
tross_Make_History( "3dDespike" , argc , argv , tset ) ;
#if 0
if( THD_is_file(DSET_HEADNAME(tset)) )
ERROR_exit("-ssave dataset already exists");
#endif
tross_Copy_History( tset , dset ) ;
tross_Make_History( "3dDespike" , argc , argv , tset ) ;
for( iv=0 ; iv < nvals ; iv++ )
EDIT_substitute_brick( tset , iv , MRI_byte , NULL ) ;
}
/*-- setup to find spikes --*/
sq2p = sqrt(0.5*PI) ;
sfac = sq2p / 1.4826f ;
/* make ref functions */
nref = 2*corder+3 ;
ref = (float **) malloc( sizeof(float *) * nref ) ;
for( jj=0 ; jj < nref ; jj++ )
ref[jj] = (float *) malloc( sizeof(float) * nuse ) ;
/* r(t) = 1 */
for( iv=0 ; iv < nuse ; iv++ ) ref[0][iv] = 1.0 ;
jj = 1 ;
/* r(t) = t - tmid */
{ float tm = 0.5 * (nuse-1.0) ; float fac = 2.0 / nuse ;
for( iv=0 ; iv < nuse ; iv++ ) ref[1][iv] = (iv-tm)*fac ;
jj = 2 ;
/* r(t) = (t-tmid)**jj */
for( ; jj <= polort ; jj++ )
for( iv=0 ; iv < nuse ; iv++ )
ref[jj][iv] = pow( (iv-tm)*fac , (double)jj ) ;
}
for( kk=1 ; kk <= corder ; kk++ ){
fq = (2.0*PI*kk)/nuse ;
/* r(t) = sin(2*PI*k*t/N) */
for( iv=0 ; iv < nuse ; iv++ )
ref[jj][iv] = sin(fq*iv) ;
jj++ ;
/* r(t) = cos(2*PI*k*t/N) */
for( iv=0 ; iv < nuse ; iv++ )
ref[jj][iv] = cos(fq*iv) ;
jj++ ;
}
/****** setup for the NEW solution method [29 Nov 2013] ******/
if( do_NEW ){
NEW_psinv = DES_get_psinv(nuse,nref,ref) ;
INFO_message("Procesing time series with NEW model fit algorithm") ;
} else {
INFO_message("Procesing time series with OLD model fit algorithm") ;
}
/*--- loop over voxels and do work ---*/
#define Laplace_t2p(val) ( 1.0 - nifti_stat2cdf( (val), 15, 0.0, 1.4427 , 0.0 ) )
if( verb ){
if( !localedit ){
INFO_message("smash edit thresholds: %.1f .. %.1f MADs",cut1*sq2p,cut2*sq2p) ;
ININFO_message(" [ %.3f%% .. %.3f%% of normal distribution]",
200.0*qg(cut1*sfac) , 200.0*qg(cut2*sfac) ) ;
ININFO_message(" [ %.3f%% .. %.3f%% of Laplace distribution]" ,
100.0*Laplace_t2p(cut1) , 100.0*Laplace_t2p(cut2) ) ;
} else {
INFO_message("local edit threshold: %.1f MADS",cut2*sq2p) ;
ININFO_message(" [ %.3f%% of normal distribution]",
200.0*qg(cut2*sfac) ) ;
ININFO_message(" [ %.3f%% of Laplace distribution]",
100.0*Laplace_t2p(cut1) ) ;
}
INFO_message("%d slices to process",DSET_NZ(dset)) ;
}
kzold = -1 ;
nspike = 0 ; nbig = 0 ; nproc = 0 ; ctim = NI_clock_time() ;
AFNI_OMP_START ;
#pragma omp parallel if( nxyz > 6666 )
{ int ii , iv , iu , id , jj ;
float *far , *dar , *var , *fitar , *ssp , *fit , *zar ;
short *sar , *qar ; byte *tar ;
float fsig , fq , cls , snew , val ;
float *NEW_wks=NULL ;
#pragma omp critical (DESPIKE_malloc)
{ far = (float *) malloc( sizeof(float) * nvals ) ;
dar = (float *) malloc( sizeof(float) * nvals ) ;
var = (float *) malloc( sizeof(float) * nvals ) ;
fitar = (float *) malloc( sizeof(float) * nvals ) ;
ssp = (float *) malloc( sizeof(float) * nvals ) ;
fit = (float *) malloc( sizeof(float) * nref ) ;
if( do_NEW ) NEW_wks = (float *)malloc(sizeof(float)*DES_workspace_size(nuse,nref)) ;
}
#ifdef USE_OMP
INFO_message("start OpenMP thread #%d",omp_get_thread_num()) ;
#endif
#pragma omp for
for( ii=0 ; ii < nxyz ; ii++ ){ /* ii = voxel index */
if( mask != NULL && mask[ii] == 0 ) continue ; /* skip this voxel */
#ifndef USE_OMP
kz = DSET_index_to_kz(dset,ii) ; /* starting a new slice */
if( kz != kzold ){
if( verb ){
fprintf(stderr, "++ start slice %2d",kz ) ;
if( nproc > 0 ){
pspike = (100.0*nspike)/nproc ;
pbig = (100.0*nbig )/nproc ;
fprintf(stderr,
"; so far %d data points, %d edits [%.3f%%], %d big edits [%.3f%%]",
nproc,nspike,pspike,nbig,pbig ) ;
}
fprintf(stderr,"\n") ;
}
kzold = kz ;
}
#else
if( verb && ii % 2345 == 1234 ) fprintf(stderr,".") ;
#endif
/*** extract ii-th time series into far[] ***/
switch( datum ){
case MRI_short:
for( iv=0 ; iv < nuse ; iv++ ){
qar = DSET_ARRAY(dset,iv+ignore) ; /* skip ignored data */
far[iv] = (float)qar[ii] ;
}
break ;
case MRI_float:
for( iv=0 ; iv < nuse ; iv++ ){
zar = DSET_ARRAY(dset,iv+ignore) ;
far[iv] = zar[ii] ;
}
break ;
}
AAmemcpy(dar,far,sizeof(float)*nuse) ; /* copy time series into dar[] */
/*** solve for L1 fit ***/
if( do_NEW )
cls = DES_solve( NEW_psinv , far , fit , NEW_wks ) ; /* 29 Nov 2013 */
else
cls = cl1_solve( nuse , nref , far , ref , fit,0 ) ; /* the slow part */
if( cls < 0.0f ){ /* fit failed! */
#if 0
fprintf(stderr,"curve fit fails at voxel %d %d %d\n",
DSET_index_to_ix(dset,ii) ,
DSET_index_to_jy(dset,ii) ,
DSET_index_to_kz(dset,ii) ) ;
#endif
continue ; /* skip this voxel */
}
for( iv=0 ; iv < nuse ; iv++ ){ /* detrend */
val = fit[0]
+ fit[1]*ref[1][iv] /* quadratic part of curve fit */
+ fit[2]*ref[2][iv] ;
for( jj=3 ; jj < nref ; jj++ ) /* rest of curve fit */
val += fit[jj] * ref[jj][iv] ;
fitar[iv] = val ; /* save curve fit value */
var[iv] = dar[iv]-val ; /* remove fitted value = resid */
far[iv] = fabsf(var[iv]) ; /* abs value of resid */
}
/*** compute estimate standard deviation of detrended data ***/
fsig = sq2p * qmed_float(nuse,far) ; /* also mangles far array */
/*** process time series for spikes, editing data in dar[] ***/
if( fsig > 0.0f ){ /* data wasn't fit perfectly */
/* find spikiness for each point in time */
fq = 1.0f / fsig ;
for( iv=0 ; iv < nuse ; iv++ ){
ssp[iv] = fq * var[iv] ; /* spikiness s = how many sigma out */
}
/* save spikiness in -ssave datset */
if( tset != NULL ){
for( iv=0 ; iv < nuse ; iv++ ){
tar = DSET_ARRAY(tset,iv+ignore) ;
snew = ITFAC*fabsf(ssp[iv]) ; /* scale for byte storage */
tar[ii] = BYTEIZE(snew) ; /* cf. mrilib.h */
}
}
/* process values of |s| > cut1, editing dar[] */
for( iv=0 ; iv < nuse ; iv++ ){ /* loop over time points */
if( !localedit ){ /** classic 'smash' edit **/
if( ssp[iv] > cut1 ){
snew = cut1 + c21*mytanh((ssp[iv]-cut1)*ic21) ; /* edit s down */
dar[iv] = fitar[iv] + snew*fsig ;
#pragma omp critical (DESPIKE_counter)
{ nspike++ ; if( ssp[iv] > cut2 ) nbig++ ; }
} else if( ssp[iv] < -cut1 ){
snew = -cut1 + c21*mytanh((ssp[iv]+cut1)*ic21) ; /* edit s up */
dar[iv] = fitar[iv] + snew*fsig ;
#pragma omp critical (DESPIKE_counter)
{ nspike++ ; if( ssp[iv] < -cut2 ) nbig++ ; }
}
} else { /** local edit: 04 Apr 2007 **/
if( ssp[iv] >= cut2 || ssp[iv] <= -cut2 ){
for( iu=iv+1 ; iu < nuse ; iu++ ) /* find non-spike above */
if( ssp[iu] < cut2 && ssp[iu] > -cut2 ) break ;
for( id=iv-1 ; id >= 0 ; id-- ) /* find non-spike below */
if( ssp[id] < cut2 && ssp[id] > -cut2 ) break ;
switch( (id>=0) + 2*(iu<nuse) ){ /* compute replacement val */
case 3: val = 0.5*(dar[iu]+dar[id]); break; /* iu and id OK */
case 2: val = dar[iu] ; break; /* only iu OK */
case 1: val = dar[id] ; break; /* only id OK */
default: val = fitar[iv] ; break; /* shouldn't be */
}
dar[iv] = val ;
#pragma omp critical (DESPIKE_counter)
{ nspike++ ; nbig++ ; }
}
}
} /* end of loop over time points */
#pragma omp atomic
nproc += nuse ; /* number data points processed */
} /* end of processing time series when fsig is positive */
/* put dar[] time series (possibly edited above) into output bricks */
switch( datum ){
case MRI_short:
for( iv=0 ; iv < nuse ; iv++ ){
sar = DSET_ARRAY(oset,iv+ignore) ; /* output brick */
sar[ii] = (short)dar[iv] ; /* original or mutated data */
}
break ;
case MRI_float:
for( iv=0 ; iv < nuse ; iv++ ){
zar = DSET_ARRAY(oset,iv+ignore) ; /* output brick */
zar[ii] = dar[iv] ; /* original or mutated data */
}
break ;
}
} /* end of loop over voxels #ii */
#pragma omp critical (DESPIKE_malloc)
{ free(fit); free(ssp); free(fitar); free(var); free(dar); free(far);
if( do_NEW ) free(NEW_wks) ; }
} /* end OpenMP */
AFNI_OMP_END ;
#ifdef USE_OMP
if( verb ) fprintf(stderr,"\n") ;
#endif
ctim = NI_clock_time() - ctim ;
INFO_message( "Elapsed despike time = %s" , nice_time_string(ctim) ) ;
if( ctim > 345678 && !do_NEW )
ININFO_message("That was SLOW -- try the '-NEW' option for a speedup") ;
#ifdef USE_OMP
if( verb ) fprintf(stderr,"\n") ;
#endif
/*--- finish up ---*/
if( do_NEW ) mri_free(NEW_psinv) ;
DSET_delete(dset) ; /* delete input dataset */
if( verb ){
if( nproc > 0 ){
pspike = (100.0*nspike)/nproc ;
pbig = (100.0*nbig )/nproc ;
INFO_message("FINAL: %d data points, %d edits [%.3f%%], %d big edits [%.3f%%]",
nproc,nspike,pspike,nbig,pbig ) ;
} else {
INFO_message("FINAL: no good voxels found to process!!??") ;
}
}
/* write results */
DSET_write(oset) ;
if( verb ) WROTE_DSET(oset) ;
DSET_delete(oset) ;
if( tset != NULL ){
DSET_write(tset) ;
if( verb ) WROTE_DSET(tset) ;
DSET_delete(tset) ;
}
exit( THD_get_write_error_count() ) ;
}
