/*
Get copy contents of sub-brick iv into an double array.
if iv == -1, get the entire dset
*/
double *THD_extract_to_double( int iv , THD_3dim_dataset *dset )
{
MRI_IMAGE *im ;
double *var=NULL, *vv=NULL;
register int ii , nvox ;
ENTRY("THD_extract_to_double") ;
if (!dset) RETURN(var);
if (iv >= 0) {
if (!(im = THD_extract_double_brick(iv, dset))) RETURN(var);
var = MRI_DOUBLE_PTR(im);mri_fix_data_pointer(NULL, im);
mri_free(im);im=NULL;
} else if (iv == -1) {
if (!(var = (double *)calloc(DSET_NVOX(dset)*DSET_NVALS(dset),
sizeof(double)))){
ERROR_message("Failed to allocate");
RETURN(NULL);
}
for (ii=0; ii<DSET_NVALS(dset); ++ii) {
if (!(im = THD_extract_double_brick(ii, dset))) {
ERROR_message("Failed toextract sb %d from dset", ii);
if (var) free(var);
RETURN(NULL);
}
vv = MRI_DOUBLE_PTR(im);
memcpy(var+ii*DSET_NVOX(dset),vv, sizeof(double)*DSET_NVOX(dset));
mri_free(im);im=NULL;
}
} else {
ERROR_message("Bad value of %d\n", iv);
}
RETURN(var);
}
/*
* for each input dataset name
* open (check dims, etc.)
* dilate (zeropad, make binary, dilate, unpad, apply)
* fill list of bytemask datasets
*
* also, count total volumes
*/
int process_input_dsets(param_t * params)
{
THD_3dim_dataset * dset, * dfirst=NULL;
int iset, nxyz;
ENTRY("process_input_dsets");
if( !params ) ERROR_exit("NULL inputs to PID");
if( params->ndsets <= 0 ) {
ERROR_message("process_input_dsets: no input datasets");
RETURN(1);
}
/* allocate space for dsets array */
params->dsets = (THD_3dim_dataset **)malloc(params->ndsets*
sizeof(THD_3dim_dataset*));
if( !params->dsets ) ERROR_exit("failed to allocate dset pointers");
if( params->verb ) INFO_message("processing %d input datasets...",
params->ndsets);
/* warn user of dilations */
if(params->verb && params->ndsets) {
int pad = needed_padding(¶ms->IND);
INFO_message("padding all datasets by %d (for dilations)", pad);
}
/* process the datasets */
nxyz = 0;
for( iset=0; iset < params->ndsets; iset++ ) {
/* open and verify dataset */
dset = THD_open_dataset(params->inputs[iset]);
if( !dset ) ERROR_exit("failed to open mask dataset '%s'",
params->inputs[iset]);
DSET_load(dset); CHECK_LOAD_ERROR(dset);
if( params->verb>1 ) INFO_message("loaded dset %s, with %d volumes",
DSET_PREFIX(dset), DSET_NVALS(dset));
if( nxyz == 0 ) { /* make an empty copy of the first dataset */
nxyz = DSET_NVOX(dset);
dfirst = EDIT_empty_copy(dset);
}
/* check for consistency in voxels and grid */
if( DSET_NVOX(dset) != nxyz ) ERROR_exit("nvoxel mis-match");
if( ! EQUIV_GRIDS(dset, dfirst) )
WARNING_message("grid from dset %s does not match that of dset %s",
DSET_PREFIX(dset), DSET_PREFIX(dfirst));
/* apply dilations to all volumes, returning bytemask datasets */
params->dsets[iset] = apply_dilations(dset, ¶ms->IND,1,params->verb);
if( ! params->dsets[iset] ) RETURN(1);
}
DSET_delete(dfirst); /* and nuke */
RETURN(0);
}
int SUMA_ShortizeDset(THD_3dim_dataset **dsetp, float thisfac) {
static char FuncName[]={"SUMA_ShortizeDset"};
char sprefix[THD_MAX_PREFIX+10];
int i, j;
byte *bb=NULL;
short *sb=NULL;
float bbf=0.0;
THD_3dim_dataset *cpset=NULL, *dset=*dsetp;
SUMA_ENTRY;
if (!dset) {
SUMA_S_Err("NULL *dsetp at input!");
SUMA_RETURN(0);
}
sprintf(sprefix, "%s.s", dset->dblk->diskptr->prefix);
NEW_SHORTY(dset, DSET_NVALS(dset), "ss.cp", cpset);
for (i=0; i<DSET_NVALS(dset); ++i) {
if (DSET_BRICK_TYPE(dset,i) == MRI_byte) {
bb = (byte *)DSET_ARRAY(dset,i);
sb = (short *)DSET_ARRAY(cpset,i);
if (thisfac <= 0.0) {
for (j=0; j<DSET_NVOX(dset); ++j) {
sb[j] = (short)bb[j];
}
thisfac = DSET_BRICK_FACTOR(dset,i);
} else {
bbf = DSET_BRICK_FACTOR(dset,i); if (bbf == 0.0f) bbf = 1.0;
bbf = bbf/thisfac;
for (j=0; j<DSET_NVOX(dset); ++j) {
sb[j] = SHORTIZE((((float)bb[j])*bbf));
}
}
EDIT_BRICK_FACTOR( cpset,i,thisfac ) ;
} else {
EDIT_substscale_brick(cpset, i, DSET_BRICK_TYPE(dset,i),
DSET_ARRAY(dset,i), MRI_short, thisfac);
if (DSET_BRICK_TYPE(dset,i) != MRI_short) {
DSET_FREE_ARRAY(dset, i);
} else {
DSET_NULL_ARRAY(dset, i);
}
}
}
/* preserve tables, if any */
THD_copy_labeltable_atr( cpset->dblk, dset->dblk);
DSET_delete(dset); dset = NULL;
*dsetp=cpset;
SUMA_RETURN(1);
}
int fill_mask(options_t * opts)
{
THD_3dim_dataset * mset;
int nvox;
ENTRY("fill_mask");
if( opts->automask ) {
if( opts->verb ) INFO_message("creating automask...");
opts->mask = THD_automask(opts->inset);
if( ! opts->mask ) {
ERROR_message("failed to apply -automask");
RETURN(1);
}
RETURN(0);
}
if( opts->mask_name ) {
if( opts->verb )
INFO_message("reading mask dset from %s...", opts->mask_name);
mset = THD_open_dataset( opts->mask_name );
if( ! mset ) ERROR_exit("cannot open mask dset '%s'", opts->mask_name);
nvox = DSET_NVOX(opts->inset);
if( DSET_NVOX(mset) != nvox ) {
ERROR_message("mask does not have the same voxel count as input");
RETURN(1);
}
/* fill mask array and mask_nxyz, remove mask dset */
DSET_load(mset); CHECK_LOAD_ERROR(mset);
opts->mask = THD_makemask(mset, 0, 1, 0);
DSET_delete(mset);
if( ! opts->mask ) {
ERROR_message("cannot make mask from '%s'", opts->mask_name);
RETURN(1);
}
if( opts->verb > 1 )
INFO_message("have mask with %d voxels", nvox);
}
RETURN(0);
}
/*---------------------------------------------------------------------
23 Feb 2012: Return the absolute value of the difference between
two volumes, divided by the number of voxels
and the number of sub-bricks. Voxels that are zero
in both sets are not counted.
Comparisons are done after conversion of data to double
return = -1.0 ERROR
= 0.0 Exactly the same
-----------------------------------------------------------------------*/
double THD_diff_vol_vals(THD_3dim_dataset *d1, THD_3dim_dataset *d2, int scl) {
double dd=0.0, denom=0.0;
int i=0, k=0;
double *a1=NULL, *a2=NULL;
MRI_IMAGE *b1 = NULL , *b2 = NULL;
ENTRY("THD_diff_vol_vals");
if (!d1 && !d2) RETURN(dd);
if (!d1 || !d2) RETURN(-1.0);
if (!EQUIV_GRIDS(d1,d2)) RETURN(-1.0);
if (DSET_NVALS(d1) != DSET_NVALS(d2)) RETURN(-1.0);
DSET_mallocize(d1) ; DSET_load(d1) ;
DSET_mallocize(d2) ; DSET_load(d2) ;
dd = 0.0; denom = 0;
for (i=0; i<DSET_NVALS(d1); ++i) {
b1 = THD_extract_double_brick(i, d1);
b2 = THD_extract_double_brick(i, d2);
a1 = MRI_DOUBLE_PTR(b1);
a2 = MRI_DOUBLE_PTR(b2);
for (k=0; k<DSET_NVOX(d1); ++k) {
dd += ABS(a1[k]-a2[k]);
if (a1[k]!=0.0 || a2[k]!=0.0) ++denom;
}
mri_clear_data_pointer(b1); mri_free(b1) ;
mri_clear_data_pointer(b2); mri_free(b2) ;
}
if (scl && denom>0.0) dd /= denom;
RETURN(dd);
}
/*
* A hole is defined as a connected set of zero voxels that does
* not reach an edge.
*
* The core functionality was added to libmri.a in THD_mask_fill_holes.
*/
int fill_holes(THD_3dim_dataset * dset, int verb)
{
short * sptr; /* to for filling holes */
byte * bmask; /* computed result */
int nfilled;
int nx, ny, nz, nvox, index, fill=0;
ENTRY("fill_holes");
bmask = THD_makemask(dset, 0, 1, 0); /* copy input as byte mask */
nx = DSET_NX(dset); ny = DSET_NY(dset); nz = DSET_NZ(dset);
nvox = DSET_NVOX(dset);
/* created filled mask */
nfilled = THD_mask_fill_holes(nx,ny,nz, bmask, verb);
if( nfilled < 0 ) { ERROR_message("failed to fill holes"); RETURN(1); }
/* apply to short volume */
sptr = DBLK_ARRAY(dset->dblk, 0);
for( index = 0; index < nvox; index++ )
if( !sptr[index] && bmask[index] ) { fill++; sptr[index] = 1; }
if(verb>2) INFO_message("final check: fill=%d, nfilled=%d", fill, nfilled);
RETURN(0);
}
MRI_IMAGE * THD_median_brick( THD_3dim_dataset *dset )
{
int nvox , nvals , ii ;
MRI_IMAGE *tsim , *medim ;
float *medar ;
float *tsar ; /* 05 Nov 2001 */
ENTRY("THD_median_brick") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
DSET_load(dset) ;
if( !DSET_LOADED(dset) ) RETURN(NULL) ;
nvals = DSET_NVALS(dset) ;
tsim = DSET_BRICK(dset,0) ;
if( nvals == 1 ){
medim = mri_scale_to_float( DSET_BRICK_FACTOR(dset,0), tsim ) ;
RETURN(medim) ;
}
medim = mri_new_conforming( tsim , MRI_float ) ;
medar = MRI_FLOAT_PTR(medim) ;
nvox = DSET_NVOX(dset) ;
tsar = (float *) calloc( sizeof(float),nvals+1 ) ; /* 05 Nov 2001 */
for( ii=0 ; ii < nvox ; ii++ ){
THD_extract_array( ii , dset , 0 , tsar ) ; /* 05 Nov 2001 */
medar[ii] = qmed_float( nvals , tsar ) ;
}
free(tsar) ; RETURN(medim) ;
}
/* just make sure we have sufficient data for computations */
int check_dims(options_t * opts)
{
int nt, nvox, nmask;
ENTRY("check_dims");
nt = DSET_NVALS(opts->inset);
nvox = DSET_NVOX(opts->inset);
if( opts->mask ) nmask = THD_countmask( nvox, opts->mask );
else nmask = nvox;
/* make sure we have something to compute */
if( nvox < 1 ) {
ERROR_message("input dataset must have at least 1 voxel");
RETURN(1);
} else if( nmask < 1 ) {
ERROR_message("input mask must have at least 1 voxel");
RETURN(1);
} else if( nt < 2 ) {
ERROR_message("input dataset must have at least 2 time points");
RETURN(1);
}
RETURN(0);
}
MRI_IMARR * THD_medmad_bricks( THD_3dim_dataset *dset )
{
int nvox , nvals , ii ;
MRI_IMAGE *tsim , *madim, *medim ;
float *madar, *medar ;
MRI_IMARR *imar ;
float *tsar ;
ENTRY("THD_medmad_bricks") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
nvals = DSET_NVALS(dset) ; if( nvals == 1 ) RETURN(NULL) ;
DSET_load(dset) ; if( !DSET_LOADED(dset) ) RETURN(NULL) ;
tsim = DSET_BRICK(dset,0) ;
madim = mri_new_conforming( tsim , MRI_float ) ;
madar = MRI_FLOAT_PTR(madim) ;
medim = mri_new_conforming( tsim , MRI_float ) ;
medar = MRI_FLOAT_PTR(medim) ;
nvox = DSET_NVOX(dset) ;
tsar = (float *) calloc( sizeof(float),nvals+1 ) ;
for( ii=0 ; ii < nvox ; ii++ ){
THD_extract_array( ii , dset , 0 , tsar ) ;
qmedmad_float( nvals , tsar , medar+ii , madar+ii ) ;
}
free(tsar) ;
INIT_IMARR(imar) ; ADDTO_IMARR(imar,medim) ; ADDTO_IMARR(imar,madim) ;
RETURN(imar) ;
}
MRI_IMAGE * THD_rms_brick( THD_3dim_dataset *dset )
{
int nvox , nvals , ii , jj ;
MRI_IMAGE *tsim , *medim ;
float *medar , sum,fac ;
float *tsar ;
ENTRY("THD_rms_brick") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
DSET_load(dset) ;
if( !DSET_LOADED(dset) ) RETURN(NULL) ;
nvals = DSET_NVALS(dset) ; fac = 1.0 / nvals ;
tsim = DSET_BRICK(dset,0) ;
if( nvals == 1 ){
medim = mri_scale_to_float( DSET_BRICK_FACTOR(dset,0), tsim ) ;
RETURN(medim) ;
}
medim = mri_new_conforming( tsim , MRI_float ) ;
medar = MRI_FLOAT_PTR(medim) ;
nvox = DSET_NVOX(dset) ;
tsar = (float *) calloc( sizeof(float),nvals+1 ) ;
for( ii=0 ; ii < nvox ; ii++ ){
THD_extract_array( ii , dset , 0 , tsar ) ;
for( sum=0.0,jj=0 ; jj < nvals ; jj++ ) sum += tsar[jj]*tsar[jj] ;
medar[ii] = sqrtf(fac * sum) ;
}
free(tsar) ; RETURN(medim) ;
}
int64_t THD_vectim_size( THD_3dim_dataset *dset , byte *mask )
{
int nvals , nvox , nmask ;
int64_t sz ;
ENTRY("THD_vectim_size") ;
if( !ISVALID_DSET(dset) ) RETURN(0) ;
nvals = DSET_NVALS(dset) ;
nvox = DSET_NVOX(dset) ;
if( mask != NULL ) nmask = THD_countmask( nvox , mask ) ;
else nmask = DSET_NVOX(dset) ;
sz = ((int64_t)nmask) * ( ((int64_t)nvals) * sizeof(float) + sizeof(int) ) ;
RETURN(sz) ;
}
bytevec * THD_create_mask_from_string( char *str ) /* Jul 2010 */
{
bytevec *bvec=NULL ; int nstr ; char *buf=NULL ;
ENTRY("THD_create_mask") ;
if( str == NULL || *str == '\0' ) RETURN(NULL) ;
nstr = strlen(str) ;
bvec = (bytevec *)malloc(sizeof(bytevec)) ;
/* try to read it as a dataset */
if( nstr < THD_MAX_NAME ){
THD_3dim_dataset *dset = THD_open_one_dataset(str) ;
if( dset != NULL ){
bvec->nar = DSET_NVOX(dset) ;
bvec->ar = THD_makemask( dset , 0 , 1.0f,0.0f ) ;
DSET_delete(dset) ;
if( bvec->ar == NULL ){
ERROR_message("Can't make mask from dataset '%s'",str) ;
free(bvec) ; bvec = NULL ;
}
RETURN(bvec) ;
}
}
/* if str is a filename, read that file;
otherwise, use the string itself to find the mask */
if( THD_is_file(str) ){
buf = AFNI_suck_file(str) ;
if( buf != NULL ) nstr = strlen(buf) ;
} else {
buf = str ;
}
/* try to read buf as a Base64 mask string */
if( strrchr(buf,'=') != NULL ){
int nvox ;
bvec->ar = mask_from_b64string( buf , &nvox ) ;
if( bvec->ar != NULL ){
bvec->nar = nvox ;
} else {
ERROR_message("Can't make mask from string '%.16s' %s",buf,(nstr<=16)?" ":"...") ;
free(bvec) ; bvec = NULL ;
}
} else {
ERROR_message("Don't understand mask string '%.16s'",buf,(nstr<=16)?" ":"...") ;
free(bvec) ; bvec = NULL ;
}
if( buf != str && buf != NULL ) free(buf) ;
RETURN(bvec) ;
}
/*
* check count against limit
* - clear small values
* - if not count, set large values to 1
*/
int limit_to_frac(THD_3dim_dataset * cset, int limit, int count, int verb)
{
short * dptr;
int index, nsub, nsuper;
ENTRY("limit_to_frac");
if( ! ISVALID_3DIM_DATASET(cset) ) {
ERROR_message("invalid count dataset");
RETURN(1);
} else if( DSET_BRICK_TYPE(cset, 0) != MRI_short ) {
ERROR_message("count dataset not of type short");
RETURN(1);
}
if(verb > 1) INFO_message("limiting to %d (count = %d)\n",limit,count);
/* note how many voxels are affected, just for kicks */
dptr = DBLK_ARRAY(cset->dblk, 0);
nsub = nsuper = 0;
for(index = 0; index < DSET_NVOX(cset); index++, dptr++) {
if( ! *dptr ) continue; /* 0, so skip */
else if( *dptr < limit ) { /* small, so clear */
*dptr = 0;
nsub++;
}
else { /* big enough */
if ( ! count ) *dptr = 1;
nsuper++;
}
}
/* entertain the user */
if( verb )
INFO_message("voxel limits: %d clipped, %d survived, %d were zero\n",
nsub, nsuper, DSET_NVOX(cset)-nsub-nsuper);
RETURN(0);
}
int THD_voxel_is_constant( int ind , THD_3dim_dataset *dset )
{
float *far ; int ii,nvox,nvals ;
if( !ISVALID_DSET(dset) ) return 1 ;
if( ind < 0 || ind >= DSET_NVOX(dset) ) return 1 ;
nvals = DSET_NVALS(dset) ; if( nvals == 1 ) return 1 ;
far = (float *)malloc(sizeof(float)*nvals) ; NULL_CHECK(far) ;
ii = THD_extract_array( ind , dset , 0 , far ) ;
if( ii < 0 ){ free(far); return 1; }
for( ii=1 ; ii < nvals && far[ii]==far[0]; ii++ ) ; /*nada*/
free(far) ; return (ii==nvals) ;
}
float THD_get_float_value( int ind , int ival , THD_3dim_dataset *dset )
{
MRI_TYPE typ ; float val=0.0f ;
if( ind < 0 || ival < 0 || !ISVALID_DSET(dset) ||
ival >= DSET_NVALS(dset) || ind >= DSET_NVOX(dset) ) return val ;
typ = DSET_BRICK_TYPE(dset,ival) ; /* raw data type */
switch( typ ){
default: /* don't know what to do --> return nada */
return(-1);
break ;
case MRI_byte:{
byte *bar ;
bar = (byte *) DSET_ARRAY(dset,ival) ;
if( bar != NULL ) val = (float)bar[ind] ;
}
break ;
case MRI_short:{
short *bar ;
bar = (short *) DSET_ARRAY(dset,ival) ;
if( bar != NULL ) val = (float)bar[ind] ;
}
break ;
case MRI_float:{
float *bar ;
bar = (float *) DSET_ARRAY(dset,ival) ;
if( bar != NULL ) val = bar[ind] ;
}
break ;
case MRI_complex:{
complex *bar ;
bar = (complex *) DSET_ARRAY(dset,ival) ;
if( bar != NULL ) val = CABS(bar[ind]) ;
}
break ;
}
if( DSET_BRICK_FACTOR(dset,ival) > 0.0f )
val *= DSET_BRICK_FACTOR(dset,ival) ;
return val ;
}
/* convert by hand, since no scaling will be done
* (byte seems inappropriate and float does not need it) */
int write_result(param_t * params, THD_3dim_dataset * oset,
int argc, char * argv[])
{
short * sptr;
int nvox = DSET_NVOX(oset), ind;
ENTRY("write_results");
EDIT_dset_items(oset, ADN_prefix, params->prefix, ADN_none);
if( params->verb )
INFO_message("writing result %s...\n", DSET_PREFIX(oset));
switch( params->datum ) {
default: ERROR_exit("invalid datum for result: %d", params->datum);
case MRI_short: break; /* nothing to do */
case MRI_float: {
float * data = (float *)malloc(nvox*sizeof(float));
sptr = DBLK_ARRAY(oset->dblk, 0);
if( ! data ) ERROR_exit("failed to alloc %d output floats\n", nvox);
for( ind = 0; ind < nvox; ind++ ) data[ind] = (float)sptr[ind];
EDIT_substitute_brick(oset, 0, params->datum, data);
}
break;
case MRI_byte: {
byte * data = (byte *)malloc(nvox*sizeof(byte));
int errs = 0;
sptr = DBLK_ARRAY(oset->dblk, 0);
if( ! data ) ERROR_exit("failed to alloc %d output bytes\n", nvox);
for( ind = 0; ind < nvox; ind++ ) {
if( sptr[ind] > 255 ) { /* watch for overflow */
data[ind] = (byte)255;
errs++;
} else data[ind] = (byte)sptr[ind];
}
EDIT_substitute_brick(oset, 0, params->datum, data);
if(errs) WARNING_message("convert to byte: %d truncated voxels",errs);
}
break;
}
tross_Make_History( "3dmask_tool", argc, argv, oset );
DSET_write(oset);
WROTE_DSET(oset);
RETURN(0);
}
int is_integral_sub_brick ( THD_3dim_dataset *dset, int isb, int check_values)
{
float mfac = 0.0;
void *vv=NULL;
if( !ISVALID_DSET(dset) ||
isb < 0 ||
isb >= DSET_NVALS(dset) ) {
fprintf(stderr,"** Bad dset or sub-brick index.\n");
return (0) ;
}
if( !DSET_LOADED(dset) ) DSET_load(dset);
switch( DSET_BRICK_TYPE(dset,isb) ){
case MRI_short:
case MRI_byte:
if (check_values) {
mfac = DSET_BRICK_FACTOR(dset,isb) ;
if (mfac != 0.0f && mfac != 1.0f) return(0);
}
break;
case MRI_double:
case MRI_complex:
case MRI_float:
vv = (void *)DSET_ARRAY(dset,isb);
mfac = DSET_BRICK_FACTOR(dset,isb) ;
if (mfac != 0.0f && mfac != 1.0f) return(0);
if (!vv) {
fprintf(stderr,"** NULL array!\n");
return(0);
}
return(is_integral_data(DSET_NVOX(dset),
DSET_BRICK_TYPE(dset,isb),
DSET_ARRAY(dset,isb) ) );
break;
default:
return(0);
}
return(1);
}
MRI_vectim * THD_dset_to_vectim_byslice( THD_3dim_dataset *dset, byte *mask ,
int ignore , int kzbot , int kztop )
{
byte *mmm ;
MRI_vectim *mrv=NULL ;
int kk,iv , nvals , nvox , nmask , nxy , nz ;
ENTRY("THD_dset_to_vectim_byslice") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
DSET_load(dset) ; if( !DSET_LOADED(dset) ) RETURN(NULL) ;
nvals = DSET_NVALS(dset) ; if( nvals <= 0 ) RETURN(NULL) ;
nvox = DSET_NVOX(dset) ;
nxy = DSET_NX(dset) * DSET_NY(dset) ; nz = DSET_NZ(dset) ;
if( kzbot < 0 ) kzbot = 0 ;
if( kztop >= nz ) kztop = nz-1 ;
if( kztop < kzbot ) RETURN(NULL) ;
if( kzbot == 0 && kztop == nz-1 ){
mrv = THD_dset_to_vectim( dset , mask, ignore ) ; RETURN(mrv) ;
}
/* make a mask that includes cutting out un-desirable slices */
{ int ibot , itop , ii ;
#pragma omp critical (MALLOC)
mmm = (byte *)malloc(sizeof(byte)*nvox) ;
if( mask == NULL ) AAmemset( mmm , 1 , sizeof(byte)*nvox ) ;
else AAmemcpy( mmm , mask , sizeof(byte)*nvox ) ;
if( kzbot > 0 )
AAmemset( mmm , 0 , sizeof(byte)*kzbot *nxy ) ;
if( kztop < nz-1 )
AAmemset( mmm+(kztop+1)*nxy , 0 , sizeof(byte)*(nz-1-kztop)*nxy ) ;
}
/* and make the vectim using the standard function */
mrv = THD_dset_to_vectim( dset , mmm , ignore ) ;
free(mmm) ;
RETURN(mrv) ;
}
MRI_IMAGE * THD_dset_to_1Dmri( THD_3dim_dataset *dset )
{
MRI_IMAGE *im ; float *far ;
int nx , ny , ii ;
ENTRY("THD_dset_to_1D") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
DSET_load(dset) ;
if( !DSET_LOADED(dset) ) RETURN(NULL) ;
nx = DSET_NVALS(dset) ;
ny = DSET_NVOX(dset) ;
im = mri_new( nx , ny , MRI_float ) ; far = MRI_FLOAT_PTR(im) ;
for( ii=0 ; ii < ny ; ii++ )
THD_extract_array( ii , dset , 0 , far + ii*nx ) ;
RETURN(im) ;
}
int main( int argc , char * argv[] )
{
int kk , nvox , ii ;
THD_3dim_dataset * oset ;
float * far ;
/*-- read command line arguments --*/
if( argc < 2 || strncmp(argv[1],"-help",5) == 0 ) UC_syntax(NULL) ;
(void) my_getenv("junk") ;
UC_read_opts( argc , argv ) ;
set_unusuality_tail( UC_ptail ) ;
oset = EDIT_empty_copy( UC_dset ) ;
EDIT_dset_items( oset ,
ADN_prefix , UC_prefix ,
ADN_ntt , 0 ,
ADN_nvals , 1 ,
ADN_datum_all , MRI_float ,
ADN_malloc_type , DATABLOCK_MEM_MALLOC ,
ADN_none ) ;
nvox = DSET_NVOX(oset) ;
far = (float *) malloc( sizeof(float) * nvox ) ;
for( kk=0 ; kk < nvox ; kk++ ) far[kk] = 0.0 ;
EDIT_substitute_brick( oset , 0 , MRI_float , far ) ;
if( !UC_be_quiet ){ printf("--- computing u") ; fflush(stdout) ; }
for( kk=0 ; kk < UC_nvec ; kk++ ){
ii = (UC_iv == NULL) ? kk : UC_iv[kk] ;
far[ii] = UC_unusuality( UC_vdim, UC_vec[kk] , UC_nvec, UC_vec ) ;
if( !UC_be_quiet && kk%1000==999 ){ printf(".");fflush(stdout); }
}
if( !UC_be_quiet ) printf("\n--- writing output\n") ;
DSET_write(oset) ;
exit(0) ;
}
void THD_extract_detrended_array( THD_3dim_dataset *dset ,
int nref, float **ref, MRI_IMARR *imar,
int ii, int scl, float *far )
{
int tt , nval , qq ;
float val , **fitar , *var ;
MRI_IMAGE *qim ;
ENTRY("THD_extract_detrended_array") ;
if( !ISVALID_DSET(dset) ||
nref < 1 || ref == NULL ||
imar == NULL || IMARR_COUNT(imar) < nref+1 ||
ii < 0 || ii >= DSET_NVOX(dset) || far == NULL ) EXRETURN ;
qq = THD_extract_array( ii , dset , 0 , far ) ; /* get data */
if( qq < 0 ) EXRETURN ;
nval = DSET_NVALS(dset) ;
fitar = (float **)malloc(sizeof(float *)*nref) ;
for( qq=0 ; qq < nref ; qq++ ){
qim = IMARR_SUBIM(imar,qq) ; fitar[qq] = MRI_FLOAT_PTR(qim) ;
}
qim = IMARR_SUBIM(imar,nref) ; var = MRI_FLOAT_PTR(qim) ;
for( tt=0 ; tt < nval ; tt++ ){ /* get residuals */
val = far[tt] ;
for( qq=0 ; qq < nref ; qq++ ) val -= ref[qq][tt] * fitar[qq][ii] ;
far[tt] = val ;
}
if( scl && var[ii] > 0.0f ){
val = 1.0f / var[ii] ;
for( tt=0 ; tt < nval ; tt++ ) far[tt] *= val ;
}
/* ZSS: Need to free fitar */
free(fitar); fitar=NULL;
EXRETURN ;
}
THD_3dim_dataset * THD_detrend_dataset( THD_3dim_dataset *dset ,
int nref , float **ref ,
int meth , int scl ,
byte *mask , MRI_IMARR **imar )
{
MRI_IMARR *qmar ;
int ii,jj,kk , nvals,nvox , iv ;
float *var ;
THD_3dim_dataset *newset ;
ENTRY("THD_detrend_dataset") ;
if( !ISVALID_DSET(dset) ) RETURN(NULL) ;
nvals = DSET_NVALS(dset) ; nvox = DSET_NVOX(dset) ;
qmar = THD_time_fit_dataset( dset , nref,ref , meth , mask ) ;
if( qmar == NULL ) RETURN(NULL) ;
newset = EDIT_empty_copy(dset) ;
for( iv=0 ; iv < nvals ; iv++ ){
EDIT_substitute_brick( newset , iv , MRI_float , NULL ) ;
EDIT_BRICK_FACTOR( newset , iv , 0.0f ) ; /* 04 Jun 2007 */
}
var = (float *)malloc(sizeof(float)*nvals) ;
for( ii=0 ; ii < nvox ; ii++ ){
if( mask == NULL || mask[ii] )
THD_extract_detrended_array( dset , nref,ref , qmar , ii,scl , var ) ;
else
memset(var,0,sizeof(float)*nvals) ;
THD_insert_series( ii , newset , nvals , MRI_float , var , 0 ) ;
}
free(var) ;
if( imar != NULL ) *imar = qmar ;
else DESTROY_IMARR(qmar) ;
RETURN(newset) ;
}
int THD_retrend_dataset( THD_3dim_dataset *dset ,
int nref , float **ref ,
int scl , byte *mask , MRI_IMARR *imar )
{
int ii,qq,tt , nvals,nvox ;
MRI_IMAGE *qim ; float **fitar , *far , fac , *var , val ;
ENTRY("THD_retrend_dataset") ;
if( !ISVALID_DSET(dset) ||
nref < 1 || ref == NULL ||
imar == NULL || IMARR_COUNT(imar) <= nref ) RETURN(0) ;
nvals = DSET_NVALS(dset) ; nvox = DSET_NVOX(dset) ;
fitar = (float **)malloc(sizeof(float *)*nref) ;
for( qq=0 ; qq < nref ; qq++ ){
qim = IMARR_SUBIM(imar,qq) ; fitar[qq] = MRI_FLOAT_PTR(qim) ;
}
qim = IMARR_SUBIM(imar,nref) ; var = MRI_FLOAT_PTR(qim) ;
far = (float *)malloc(sizeof(float)*nvals) ;
for( ii=0 ; ii < nvox ; ii++ ){
if( mask != NULL && !mask[ii] ) continue ;
qq = THD_extract_array( ii , dset , 0 , far ) ; /* get data */
if( qq < 0 ) continue ;
fac = (scl) ? var[ii] : 1.0f ;
for( tt=0 ; tt < nvals ; tt++ ){ /* add fit back in */
val = far[tt] * fac ;
for( qq=0 ; qq < nref ; qq++ ) val += ref[qq][tt] * fitar[qq][ii] ;
far[tt] = val ;
}
THD_insert_series( ii , dset , nvals , MRI_float , far , 0 ) ;
}
free(far) ; free(fitar) ; RETURN(1) ;
}
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=NULL;
char *prefix="RSFC" ;
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 ;
// @@ non-BP variables
float fbotALL=0.0f, ftopALL=999999.9f; // do full range version
int NumDen = 0; // switch for doing numerator or denom
THD_3dim_dataset *outsetALL=NULL ;
int m, mm;
float delf; // harmonics
int ind_low,ind_high,N_ny, ctr;
float sqnt,nt_fac;
gsl_fft_real_wavetable *real1, *real2; // GSL stuff
gsl_fft_real_workspace *work;
double *series1, *series2;
double *xx1,*xx2;
float numer,denom,val;
float *alff=NULL,*malff=NULL,*falff=NULL,
*rsfa=NULL,*mrsfa=NULL,*frsfa=NULL; // values
float meanALFF=0.0f,meanRSFA=0.0f; // will be for mean in brain region
THD_3dim_dataset *outsetALFF=NULL;
THD_3dim_dataset *outsetmALFF=NULL;
THD_3dim_dataset *outsetfALFF=NULL;
THD_3dim_dataset *outsetRSFA=NULL;
THD_3dim_dataset *outsetmRSFA=NULL;
THD_3dim_dataset *outsetfRSFA=NULL;
char out_lff[300];
char out_alff[300];
char out_malff[300];
char out_falff[300];
char out_rsfa[300];
char out_mrsfa[300];
char out_frsfa[300];
char out_unBP[300];
int SERIES_OUT = 1;
int UNBP_OUT = 0;
int DO_RSFA = 1;
int BP_LAST = 0; // option for only doing filter to LFFs at very end of proc
float de_rsfa=0.0f,nu_rsfa=0.0f;
double pow1=0.0,pow2=0.0;
/*-- help? --*/
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
printf(
"\n Program to calculate common resting state functional connectivity (RSFC)\n"
" parameters (ALFF, mALFF, fALFF, RSFA, etc.) for resting state time\n"
" series. This program is **heavily** based on the existing\n"
" 3dBandPass by RW Cox, with the amendments to calculate RSFC\n"
" parameters written by PA Taylor (July, 2012).\n"
" This program is part of FATCAT (Taylor & Saad, 2013) in AFNI. Importantly,\n"
" its functionality can be included in the `afni_proc.py' processing-script \n"
" generator; see that program's help file for an example including RSFC\n"
" and spectral parameter calculation via the `-regress_RSFC' option.\n"
"\n"
"* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *\n"
"\n"
" All options of 3dBandPass may be used here (with a couple other\n"
" parameter options, as well): essentially, the motivation of this\n"
" program is to produce ALFF, etc. values of the actual RSFC time\n"
" series that you calculate. Therefore, all the 3dBandPass processing\n"
" you normally do en route to making your final `resting state time\n"
" series' is done here to generate your LFFs, from which the\n"
" amplitudes in the LFF band are calculated at the end. In order to\n"
" calculate fALFF, the same initial time series are put through the\n"
" same processing steps which you have chosen but *without* the\n"
" bandpass part; the spectrum of this second time series is used to\n"
" calculate the fALFF denominator.\n"
" \n"
" For more information about each RSFC parameter, see, e.g.: \n"
" ALFF/mALFF -- Zang et al. (2007),\n"
" fALFF -- Zou et al. (2008),\n"
" RSFA -- Kannurpatti & Biswal (2008).\n"
"\n"
"* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *\n"
"\n"
" + USAGE: 3dRSFC [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 3dRSFC 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"
"* 3dRSFC 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 3dRSFC will\n"
" depend on the order in which you run these programs. That's why\n"
" 3dRSFC 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), and\n"
" for the LFFs, the bandpass is done between the specified fbot and ftop,\n"
" while for the `whole spectrum' (i.e., fALFF denominator) the bandpass is:\n"
" done only to exclude the time series mean and the Nyquist frequency:\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"
" (9) Calculate spectrum and amplitudes, for RSFC parameters.\n"
"\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. Name of filtered time\n"
" series would be, e.g., ppp_LFF+orig.*, and the parameter\n"
" outputs are named with obvious suffices.\n"
" -quiet = Turn off the fun and informative messages. (Why?)\n"
" -no_rs_out = Don't output processed time series-- just output\n"
" parameters (not recommended, since the point of\n"
" calculating RSFC params here is to have them be quite\n"
" related to the time series themselves which are used for\n"
" further analysis)."
" -un_bp_out = Output the un-bandpassed series as well (default is not \n"
" to). Name would be, e.g., ppp_unBP+orig.* .\n"
" with suffix `_unBP'.\n"
" -no_rsfa = If you don't want RSFA output (default is to do so).\n"
" -bp_at_end = A (probably unnecessary) switch to have bandpassing be \n"
" the very last processing step that is done in the\n"
" sequence of steps listed above; at Step 3 above, only \n"
" the time series mean and nyquist are BP'ed out, and then\n"
" the LFF series is created only after Step 9. NB: this \n"
" probably makes only very small changes for most\n"
" processing sequences (but maybe not, depending usage).\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-\n"
" voxel correlations via InstaCorr.\n"
" ++ No other tests are made [yet] for non-stationary \n"
" behavior in the time series data.\n"
"\n"
"* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *\n"
"\n"
" If you use this program, please reference the introductory/description\n"
" paper for the FATCAT toolbox:\n"
" Taylor PA, Saad ZS (2013). FATCAT: (An Efficient) Functional\n"
" And Tractographic Connectivity Analysis Toolbox. Brain \n"
" Connectivity 3(5):523-535.\n"
"____________________________________________________________________________\n"
);
PRINT_AFNI_OMP_USAGE(
" 3dRSFC" ,
" * At present, the only part of 3dRSFC that is parallelized is the\n"
" '-blur' option, which processes each sub-brick independently.\n"
) ;
PRINT_COMPILE_DATE ; exit(0) ;
}
/*-- startup --*/
mainENTRY("3dRSFC"); machdep();
AFNI_logger("3dRSFC",argc,argv);
PRINT_VERSION("3dRSFC (from 3dBandpass by RW Cox): version THETA");
AUTHOR("PA Taylor");
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],"-no_rs_out") == 0 ){ // @@
SERIES_OUT = 0 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-un_bp_out") == 0 ){ // @@
UNBP_OUT = 1 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-no_rsfa") == 0 ){ // @@
DO_RSFA = 0 ; nopt++ ; continue ;
}
if( strcmp(argv[nopt],"-bp_at_end") == 0 ){ // @@
BP_LAST = 1 ; 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 ;
}
}
ftopALL = 1./dt ;// Aug,2016: should solve problem of a too-large
// value for THD_bandpass_vectors(), while still
// being >f_{Nyquist}
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 ) // @@ alert if aaaalllllll vox are going to be analyzed!
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 */
// @@ convert BP'ing ftop/bot into indices for the DFT (below)
delf = 1.0/(ntime*dt);
ind_low = (int) rint(fbot/delf);
ind_high = (int) rint(ftop/delf);
if( ntime % 2 ) // nyquist number
N_ny = (ntime-1)/2;
else
N_ny = ntime/2;
sqnt = sqrt(ntime);
nt_fac = sqrt(ntime*(ntime-1));
// @@ if BP_LAST==0:
// now we go through twice, doing LFF bandpass for NumDen==0 and
// `full spectrum' processing for NumDen==1.
// if BP_LAST==1:
// now we go through once, doing only `full spectrum' processing
for( NumDen=0 ; NumDen<2 ; NumDen++) {
//if( NumDen==1 ){ // full spectrum
// fbot = fbotALL;
// ftop = ftopALL;
//}
// essentially, just doesn't BP here, and the perfect filtering at end
// is used for both still; this makes the final output spectrum
// contain only frequencies in range of 0.01-0.08
if( BP_LAST==1 )
INFO_message("Only doing filtering to LFFs at end!");
mrv = THD_dset_to_vectim( inset , mask , 0 ) ;
if( mrv == NULL ) ERROR_exit("Can't load time series data!?") ;
if( NumDen==1 )
DSET_unload(inset) ; // @@ only unload on 2nd pass
/* 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 ;
}
}
/* 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") ;
if( (BP_LAST==0) && (NumDen==0) )
(void)THD_bandpass_vectim( mrv , dt,fbot,ftop , qdet , nort,ort ) ;
else
(void)THD_bandpass_vectim( mrv , dt,fbotALL,ftopALL, 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 ) ; //@@
if( (BP_LAST==0) && (NumDen==0) )
(void)THD_bandpass_vectim(orv,dt,fbot,ftop,qdet,nort,ort);
else
(void)THD_bandpass_vectim(orv,dt,fbotALL,ftopALL,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( (NumDen==0) ) { // @@ BP'ed version; will do filt if BP_LAST
if(BP_LAST) // do bandpass here for BP_LAST
(void)THD_bandpass_vectim(mrv,dt,fbot,ftop,qdet,0,NULL);
if( verb ) INFO_message("Creating output dataset in memory, then writing it") ;
outset = EDIT_empty_copy(inset) ;
if(SERIES_OUT){
sprintf(out_lff,"%s_LFF",prefix);
EDIT_dset_items( outset , ADN_prefix,out_lff , 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) ;
if(SERIES_OUT){ // @@
DSET_write(outset) ; if( verb ) WROTE_DSET(outset) ;
}
}
else{ // @@ non-BP'ed version
if( verb ) INFO_message("Creating output dataset 2 in memory") ;
// do this here because LFF version was also BP'ed at end.
if(BP_LAST) // do bandpass here for BP_LAST
(void)THD_bandpass_vectim(mrv,dt,fbotALL,ftopALL,qdet,0,NULL);
outsetALL = EDIT_empty_copy(inset) ;
if(UNBP_OUT){
sprintf(out_unBP,"%s_unBP",prefix);
EDIT_dset_items( outsetALL, ADN_prefix, out_unBP, ADN_none );
tross_Copy_History( inset , outsetALL ) ;
tross_Make_History( "3dRSFC" , argc,argv , outsetALL ) ;
}
for( vv=0 ; vv < ntime ; vv++ )
EDIT_substitute_brick( outsetALL , vv , MRI_float , NULL ) ;
#if 1
THD_vectim_to_dset( mrv , outsetALL ) ;
#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(outsetALL,vv) ; var = mrv->fvec + vv ;
for( kk=0 ; kk < nmask ; kk++ ) far[ivec[kk]] = var[kk*ntime] ;
}
}
AFNI_OMP_END ;
#endif
VECTIM_destroy(mrv) ;
if(UNBP_OUT){
DSET_write(outsetALL) ; if( verb ) WROTE_DSET(outsetALL) ;
}
}
}// end of NumDen loop
// @@
INFO_message("Starting the (f)ALaFFel calcs") ;
// allocations
series1 = (double *)calloc(ntime,sizeof(double));
series2 = (double *)calloc(ntime,sizeof(double));
xx1 = (double *)calloc(2*ntime,sizeof(double));
xx2 = (double *)calloc(2*ntime,sizeof(double));
alff = (float *)calloc(nvox,sizeof(float));
malff = (float *)calloc(nvox,sizeof(float));
falff = (float *)calloc(nvox,sizeof(float));
if( (series1 == NULL) || (series2 == NULL)
|| (xx1 == NULL) || (xx2 == NULL)
|| (alff == NULL) || (malff == NULL) || (falff == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(122);
}
if(DO_RSFA) {
rsfa = (float *)calloc(nvox,sizeof(float));
mrsfa = (float *)calloc(nvox,sizeof(float));
frsfa = (float *)calloc(nvox,sizeof(float));
if( (rsfa == NULL) || (mrsfa == NULL) || (frsfa == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(123);
}
}
work = gsl_fft_real_workspace_alloc (ntime);
real1 = gsl_fft_real_wavetable_alloc (ntime);
real2 = gsl_fft_real_wavetable_alloc (ntime);
gsl_complex_packed_array compl_freqs1 = xx1;
gsl_complex_packed_array compl_freqs2 = xx2;
// *********************************************************************
// *********************************************************************
// ************** Falafelling = ALFF/fALFF calcs *****************
// *********************************************************************
// *********************************************************************
// Be now have the BP'ed data set (outset) and the non-BP'ed one
// (outsetALL). now we'll FFT both, get amplitudes in appropriate
// ranges, and calculate: ALFF, mALFF, fALFF,
ctr = 0;
for( kk=0; kk<nvox ; kk++) {
if(mask[kk]) {
// BP one, and unBP one, either for BP_LAST or !BP_LAST
for( m=0 ; m<ntime ; m++ ) {
series1[m] = THD_get_voxel(outset,kk,m);
series2[m] = THD_get_voxel(outsetALL,kk,m);
}
mm = gsl_fft_real_transform(series1, 1, ntime, real1, work);
mm = gsl_fft_halfcomplex_unpack(series1, compl_freqs1, 1, ntime);
mm = gsl_fft_real_transform(series2, 1, ntime, real2, work);
mm = gsl_fft_halfcomplex_unpack(series2, compl_freqs2, 1, ntime);
numer = 0.0f;
denom = 0.0f;
de_rsfa = 0.0f;
nu_rsfa = 0.0f;
for( m=1 ; m<N_ny ; m++ ) {
mm = 2*m;
pow2 = compl_freqs2[mm]*compl_freqs2[mm] +
compl_freqs2[mm+1]*compl_freqs2[mm+1]; // power
//pow2*=2;// factor of 2 since ampls are even funcs
denom+= (float) sqrt(pow2); // amplitude
de_rsfa+= (float) pow2;
if( ( m>=ind_low ) && ( m<=ind_high ) ){
pow1 = compl_freqs1[mm]*compl_freqs1[mm]+
compl_freqs1[mm+1]*compl_freqs1[mm+1];
//pow1*=2;
numer+= (float) sqrt(pow1);
nu_rsfa+= (float) pow1;
}
}
if( denom>0.000001 )
falff[kk] = numer/denom;
else
falff[kk] = 0.;
alff[kk] = 2*numer/sqnt;// factor of 2 since ampl is even funct
meanALFF+= alff[kk];
if(DO_RSFA){
nu_rsfa = sqrt(2*nu_rsfa); // factor of 2 since ampls
de_rsfa = sqrt(2*de_rsfa); // are even funcs
if( de_rsfa>0.000001 )
frsfa[kk] = nu_rsfa/de_rsfa;
else
frsfa[kk]=0.;
rsfa[kk] = nu_rsfa/nt_fac;
meanRSFA+= rsfa[kk];
}
ctr+=1;
}
}
meanALFF/= ctr;
meanRSFA/= ctr;
gsl_fft_real_wavetable_free(real1);
gsl_fft_real_wavetable_free(real2);
gsl_fft_real_workspace_free(work);
// ALFFs divided by mean of brain value
for( kk=0 ; kk<nvox ; kk++ )
if(mask[kk]){
malff[kk] = alff[kk]/meanALFF;
if(DO_RSFA)
mrsfa[kk] = rsfa[kk]/meanRSFA;
}
// **************************************************************
// **************************************************************
// Store and output
// **************************************************************
// **************************************************************
outsetALFF = EDIT_empty_copy( inset ) ;
sprintf(out_alff,"%s_ALFF",prefix);
EDIT_dset_items( outsetALFF,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_alff,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetALFF)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetALFF));
EDIT_substitute_brick(outsetALFF, 0, MRI_float, alff);
alff=NULL;
THD_load_statistics(outsetALFF);
tross_Make_History("3dRSFC", argc, argv, outsetALFF);
THD_write_3dim_dataset(NULL, NULL, outsetALFF, True);
outsetfALFF = EDIT_empty_copy( inset ) ;
sprintf(out_falff,"%s_fALFF",prefix);
EDIT_dset_items( outsetfALFF,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_falff,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetfALFF)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetfALFF));
EDIT_substitute_brick(outsetfALFF, 0, MRI_float, falff);
falff=NULL;
THD_load_statistics(outsetfALFF);
tross_Make_History("3dRSFC", argc, argv, outsetfALFF);
THD_write_3dim_dataset(NULL, NULL, outsetfALFF, True);
outsetmALFF = EDIT_empty_copy( inset ) ;
sprintf(out_malff,"%s_mALFF",prefix);
EDIT_dset_items( outsetmALFF,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_malff,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetmALFF)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetmALFF));
EDIT_substitute_brick(outsetmALFF, 0, MRI_float, malff);
malff=NULL;
THD_load_statistics(outsetmALFF);
tross_Make_History("3dRSFC", argc, argv, outsetmALFF);
THD_write_3dim_dataset(NULL, NULL, outsetmALFF, True);
if(DO_RSFA){
outsetRSFA = EDIT_empty_copy( inset ) ;
sprintf(out_rsfa,"%s_RSFA",prefix);
EDIT_dset_items( outsetRSFA,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_rsfa,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetRSFA)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetRSFA));
EDIT_substitute_brick(outsetRSFA, 0, MRI_float, rsfa);
rsfa=NULL;
THD_load_statistics(outsetRSFA);
tross_Make_History("3dRSFC", argc, argv, outsetRSFA);
THD_write_3dim_dataset(NULL, NULL, outsetRSFA, True);
outsetfRSFA = EDIT_empty_copy( inset ) ;
sprintf(out_frsfa,"%s_fRSFA",prefix);
EDIT_dset_items( outsetfRSFA,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_frsfa,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetfRSFA)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetfRSFA));
EDIT_substitute_brick(outsetfRSFA, 0, MRI_float, frsfa);
frsfa=NULL;
THD_load_statistics(outsetfRSFA);
tross_Make_History("3dRSFC", argc, argv, outsetfRSFA);
THD_write_3dim_dataset(NULL, NULL, outsetfRSFA, True);
outsetmRSFA = EDIT_empty_copy( inset ) ;
sprintf(out_mrsfa,"%s_mRSFA",prefix);
EDIT_dset_items( outsetmRSFA,
ADN_nvals, 1,
ADN_datum_all , MRI_float ,
ADN_prefix , out_mrsfa,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetmRSFA)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetmRSFA));
EDIT_substitute_brick(outsetmRSFA, 0, MRI_float, mrsfa);
mrsfa=NULL;
THD_load_statistics(outsetmRSFA);
tross_Make_History("3dRSFC", argc, argv, outsetmRSFA);
THD_write_3dim_dataset(NULL, NULL, outsetmRSFA, True);
}
// ************************************************************
// ************************************************************
// Freeing
// ************************************************************
// ************************************************************
DSET_delete(inset);
DSET_delete(outsetALL);
DSET_delete(outset);
DSET_delete(outsetALFF);
DSET_delete(outsetmALFF);
DSET_delete(outsetfALFF);
DSET_delete(outsetRSFA);
DSET_delete(outsetmRSFA);
DSET_delete(outsetfRSFA);
free(inset);
free(outsetALL);
free(outset);
free(outsetALFF);
free(outsetmALFF);
free(outsetfALFF);
free(outsetRSFA);
free(outsetmRSFA);
free(outsetfRSFA);
free(rsfa);
free(mrsfa);
free(frsfa);
free(alff);
free(malff);
free(falff);
free(mask);
free(series1);
free(series2);
free(xx1);
free(xx2);
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) ;
}
/*
* create empty count dataset
* for each input dataset and each sub-volume
* for each voxel, if set: increment
* close datasets as they are processed
*/
int count_masks(THD_3dim_dataset * dsets[], int ndsets, int verb, /* inputs */
THD_3dim_dataset ** cset, int * nvol) /* outputs */
{
THD_3dim_dataset * dset;
short * counts = NULL; /* will become data for returned cset */
byte * bptr; /* always points to mask volumes */
int nxyz, iset, ivol, ixyz;
ENTRY("count_masks");
if( !dsets || !cset || !nvol )
ERROR_exit("NULL inputs to count_masks");
if( ndsets <= 0 ) {
ERROR_message("count_masks: no input datasets");
RETURN(1);
}
*nvol = 0;
nxyz = DSET_NVOX(dsets[0]);
/* allocate memory for the counts */
counts = (short *)calloc(nxyz, sizeof(short));
if( !counts ) ERROR_exit("failed to malloc %d shorts", nxyz);
/* for each volume of each dataset, count set voxels */
for( iset=0; iset < ndsets; iset++ ) {
dset = dsets[iset];
*nvol += DSET_NVALS(dset); /* accumulate num volumes */
/* for each volume in this dataset, count set voxels */
for( ivol=0; ivol < DSET_NVALS(dset); ivol++ ) {
if( DSET_BRICK_TYPE(dset, ivol) != MRI_byte )
ERROR_exit("in count_masks with non-byte data (set %d, vol %d)",
iset, ivol);
bptr = DBLK_ARRAY(dset->dblk, ivol);
for( ixyz = 0; ixyz < nxyz; ixyz++ )
if( bptr[ixyz] ) counts[ixyz]++;
}
if( iset > 0 ) DSET_delete(dset); /* close the first one at end */
} /* dataset */
if( verb > 1 ) {
int maxval;
for( maxval=counts[0], ixyz=1; ixyz < nxyz; ixyz++ )
if( counts[ixyz] > maxval ) maxval = counts[ixyz];
INFO_message("counted %d mask volumes in %d datasets (%d voxels)\n",
*nvol, ndsets, nxyz);
INFO_message(" (maximum overlap = %d)\n", maxval);
}
if( *nvol >= (1<<15) )
WARNING_message("too many volumes to count as shorts: %d", *nvol);
/* create output dataset */
*cset = EDIT_empty_copy(dsets[0]);
EDIT_dset_items(*cset, ADN_nvals, 1, ADN_ntt, 0, ADN_none);
EDIT_substitute_brick(*cset, 0, MRI_short, counts);
DSET_delete(dsets[0]); /* now finished with first dataset */
RETURN(0);
}
int main(int argc, char *argv[]) {
int i,j,k,m,n,aa,ii,jj,kk,mm,rr;
int iarg;
int nmask1=0;
int nmask2=0;
THD_3dim_dataset *insetFA = NULL, *insetV1 = NULL,
*insetMD = NULL, *insetL1 = NULL;
THD_3dim_dataset *insetEXTRA=NULL;
THD_3dim_dataset *mset2=NULL;
THD_3dim_dataset *mset1=NULL;
THD_3dim_dataset *outsetMAP=NULL, *outsetMASK=NULL;
char *prefix="tracky";
int LOG_TYPE=0;
char in_FA[300];
char in_V1[300];
char in_MD[300];
char in_L1[300];
int EXTRAFILE=0; // switch for whether other file is input as WM map
char OUT_bin[300];
char OUT_tracstat[300];
char prefix_mask[300];
char prefix_map[300];
// FACT algopts
FILE *fout0;
float MinFA=0.2,MaxAngDeg=45,MinL=20.0;
float MaxAng;
int SeedPerV[3]={2,2,2};
int ArrMax=0;
float tempvmagn;
int Nvox=-1; // tot number vox
int Dim[3]={0,0,0}; // dim in each dir
int Nseed=0,M=30,bval=1000;
int DimSeed[3]; // number of seeds there will be
float Ledge[3]; // voxel edge lengths
int *ROI1, *ROI2;
short int *temp_arr;
char *temp_byte;
int **Tforw, **Tback;
int **Ttot;
float **flTforw, **flTback;
float ****coorded;
int ****INDEX;
int len_forw, len_back; // int count of num of squares through
float phys_forw[1], phys_back[1];
int idx;
float ave_tract_len, ave_tract_len_phys;
int inroi1, inroi2, KEEPIT; // switches for detecting
int in[3]; // to pass to trackit
float physin[3]; // also for trackit, physical loc,
int totlen;
float totlen_phys;
int Numtract;
int READS_in;
float READS_fl;
int end[2][3];
int test_ind[2][3];
int roi3_ct=0, id=0;
float roi3_mu_MD = 0.,roi3_mu_RD = 0.,roi3_mu_L1 = 0.,roi3_mu_FA = 0.;
float roi3_sd_MD = 0.,roi3_sd_RD = 0.,roi3_sd_L1 = 0.,roi3_sd_FA = 0.;
float tempMD,tempFA,tempRD,tempL1;
char dset_or[4] = "RAI";
THD_3dim_dataset *dsetn;
int TV_switch[3] = {0,0,0};
TAYLOR_BUNDLE *tb=NULL;
TAYLOR_TRACT *tt=NULL;
char *mode = "NI_fast_binary";
NI_element *nel=NULL;
int dump_opts=0;
tv_io_header header1 = {.id_string = "TRACK\0",
.origin = {0,0,0},
.n_scalars = 3,
.scal_n[0] = "FA",
.scal_n[1] = "MD",
.scal_n[2] = "L1",
.n_properties = 0,
.vox_to_ras = {{0.,0.,0.,0.},{0.,0.,0.,0.},
{0.,0.,0.,0.},{0.,0.,0.,0.}},
// reset this later based on actual data set
.voxel_order = "RAI\0",
.invert_x = 0,
.invert_y = 0,
.invert_z = 0,
.swap_xy = 0,
.swap_yz = 0,
.swap_zx = 0,
.n_count = 0,
.version = 2,
.hdr_size = 1000};
// for testing names...
char *postfix[4]={"+orig.HEAD\0",".nii.gz\0",".nii\0","+tlrc.HEAD\0"};
int FOUND =-1;
int RECORD_ORIG = 0;
float Orig[3] = {0.0,0.0,0.0};
mainENTRY("3dTrackID"); machdep();
// ****************************************************************
// ****************************************************************
// load AFNI stuff
// ****************************************************************
// ****************************************************************
INFO_message("version: MU");
/** scan args **/
if (argc == 1) { usage_TrackID(1); exit(0); }
iarg = 1;
while( iarg < argc && argv[iarg][0] == '-' ){
if( strcmp(argv[iarg],"-help") == 0 ||
strcmp(argv[iarg],"-h") == 0 ) {
usage_TrackID(strlen(argv[iarg])>3 ? 2:1);
exit(0);
}
if( strcmp(argv[iarg],"-verb") == 0) {
if( ++iarg >= argc )
ERROR_exit("Need argument after '-verb'") ;
set_tract_verb(atoi(argv[iarg]));
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-write_opts") == 0) {
dump_opts=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-rec_orig") == 0) {
RECORD_ORIG=1;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-tract_out_mode") == 0) {
if( ++iarg >= argc )
ERROR_exit("Need argument after '-tract_out_mode'") ;
if (strcmp(argv[iarg], "NI_fast_binary") &&
strcmp(argv[iarg], "NI_fast_text") &&
strcmp(argv[iarg], "NI_slow_binary") &&
strcmp(argv[iarg], "NI_slow_text") ) {
ERROR_message("Bad value (%s) for -tract_out_mode",argv[iarg]);
exit(1);
}
mode = argv[iarg];
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-mask1") == 0 ){
if( ++iarg >= argc )
ERROR_exit("Need argument after '-mask1'") ;
mset1 = THD_open_dataset( argv[iarg] ) ;
if( mset1 == NULL )
ERROR_exit("Can't open mask1 dataset '%s'", argv[iarg]) ;
DSET_load(mset1) ; CHECK_LOAD_ERROR(mset1) ;
nmask1 = DSET_NVOX(mset1) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-mask2") == 0 ){
if( ++iarg >= argc )
ERROR_exit("Need argument after '-mask2'") ;
mset2 = THD_open_dataset( argv[iarg] ) ;
if( mset2 == NULL )
ERROR_exit("Can't open mask2 dataset '%s'",
argv[iarg]) ;
DSET_load(mset2) ; CHECK_LOAD_ERROR(mset2) ;
nmask2 = DSET_NVOX(mset2) ;
iarg++ ; continue ;
}
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],"-input") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-input'");
for( i=0 ; i<4 ; i++) {
sprintf(in_FA,"%s_FA%s", argv[iarg],postfix[i]);
if(THD_is_ondisk(in_FA)) {
FOUND = i;
break;
}
}
insetFA = THD_open_dataset(in_FA) ;
if( (insetFA == NULL ) || (FOUND==-1))
ERROR_exit("Can't open dataset '%s': for FA.",in_FA);
DSET_load(insetFA) ; CHECK_LOAD_ERROR(insetFA) ;
Nvox = DSET_NVOX(insetFA) ;
Dim[0] = DSET_NX(insetFA); Dim[1] = DSET_NY(insetFA);
Dim[2] = DSET_NZ(insetFA);
Ledge[0] = fabs(DSET_DX(insetFA)); Ledge[1] = fabs(DSET_DY(insetFA));
Ledge[2] = fabs(DSET_DZ(insetFA));
Orig[0] = DSET_XORG(insetFA); Orig[1] = DSET_YORG(insetFA);
Orig[2] = DSET_ZORG(insetFA);
// check tot num vox match (as proxy for dims...)
if( (Nvox != nmask1) || (Nvox != nmask2) )
ERROR_exit("Input dataset does not match both mask volumes!");
// this stores the original data file orientation for later use,
// as well since we convert everything to RAI temporarily, as
// described below
header1.voxel_order[0]=ORIENT_typestr[insetFA->daxes->xxorient][0];
header1.voxel_order[1]=ORIENT_typestr[insetFA->daxes->yyorient][0];
header1.voxel_order[2]=ORIENT_typestr[insetFA->daxes->zzorient][0];
for( i=0 ; i<3 ; i++) {
header1.dim[i] = Dim[i];
header1.voxel_size[i] = Ledge[i];
// will want this when outputting file later for TrackVis.
TV_switch[i] = !(dset_or[i]==header1.voxel_order[i]);
}
dset_or[3]='\0';
FOUND = -1;
for( i=0 ; i<4 ; i++) {
sprintf(in_V1,"%s_V1%s", argv[iarg],postfix[i]);
if(THD_is_ondisk(in_V1)) {
FOUND = i;
break;
}
}
insetV1 = THD_open_dataset(in_V1);
if( insetV1 == NULL )
ERROR_exit("Can't open dataset '%s':V1",in_V1);
DSET_load(insetV1) ; CHECK_LOAD_ERROR(insetV1) ;
FOUND = -1;
for( i=0 ; i<4 ; i++) {
sprintf(in_L1,"%s_L1%s", argv[iarg],postfix[i]);
if(THD_is_ondisk(in_L1)) {
FOUND = i;
break;
}
}
insetL1 = THD_open_dataset(in_L1);
if( insetL1 == NULL )
ERROR_exit("Can't open dataset '%s':L1",in_L1);
DSET_load(insetL1) ; CHECK_LOAD_ERROR(insetL1) ;
FOUND = -1;
for( i=0 ; i<4 ; i++) {
sprintf(in_MD,"%s_MD%s", argv[iarg],postfix[i]);
if(THD_is_ondisk(in_MD)) {
FOUND = i;
break;
}
}
insetMD = THD_open_dataset(in_MD);
if( insetMD == NULL )
ERROR_exit("Can't open dataset '%s':MD",in_MD);
DSET_load(insetMD) ; CHECK_LOAD_ERROR(insetMD) ;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-algopt") == 0 ){
iarg++ ;
if( iarg >= argc )
ERROR_exit("Need argument after '-algopt'");
if (!(nel = ReadTractAlgOpts(argv[iarg]))) {
ERROR_message("Failed to read options in %s\n", argv[iarg]);
exit(19);
}
if (NI_getTractAlgOpts(nel, &MinFA, &MaxAngDeg, &MinL,
SeedPerV, &M, &bval)) {
ERROR_message("Failed to get options");
exit(1);
}
NI_free_element(nel); nel=NULL;
iarg++ ; continue ;
}
if( strcmp(argv[iarg],"-logic") == 0 ){
iarg++ ; if( iarg >= argc )
ERROR_exit("Need argument after '-logic'");
INFO_message("ROI logic type is: %s",argv[iarg]);
if( strcmp(argv[iarg],"AND") == 0 )
LOG_TYPE = 1;
else if( strcmp(argv[iarg],"OR") == 0 )
LOG_TYPE = 0;
else if( strcmp(argv[iarg],"ALL") == 0 )
LOG_TYPE = -1;
else
ERROR_exit("Illegal after '-logic': need 'OR' or 'AND'");
iarg++ ; continue ;
}
//@@
if( strcmp(argv[iarg],"-extra_set") == 0) {
if( ++iarg >= argc )
ERROR_exit("Need argument after '-extra_set'");
EXTRAFILE = 1; // switch on
insetEXTRA = THD_open_dataset(argv[iarg]);
if( (insetEXTRA == NULL ) )
ERROR_exit("Can't open dataset '%s': for extra set.",argv[iarg]);
DSET_load(insetEXTRA) ; CHECK_LOAD_ERROR(insetEXTRA) ;
if( !((Dim[0] == DSET_NX(insetEXTRA)) && (Dim[1] == DSET_NY(insetEXTRA)) && (Dim[2] == DSET_NZ(insetEXTRA))))
ERROR_exit("Dimensions of extra set '%s' don't match those of the DTI prop ones ('%s', etc.).",argv[iarg], in_FA);
iarg++ ; continue ;
}
ERROR_message("Bad option '%s'\n",argv[iarg]) ;
suggest_best_prog_option(argv[0], argv[iarg]);
exit(1);
}
if (iarg < 4) {
ERROR_message("Too few options. Try -help for details.\n");
exit(1);
}
if (dump_opts) {
nel = NI_setTractAlgOpts(NULL, &MinFA, &MaxAngDeg, &MinL,
SeedPerV, &M, &bval);
WriteTractAlgOpts(prefix, nel);
NI_free_element(nel); nel=NULL;
}
// Process the options a little
for( i=0 ; i<3 ; i++)
DimSeed[i] = Dim[i]*SeedPerV[i];
Nseed = Nvox*SeedPerV[0]*SeedPerV[1]*SeedPerV[2];
// convert to cos of rad value for comparisons, instead of using acos()
MaxAng = cos(CONV*MaxAngDeg);
// switch to add header-- option for now, added Sept. 2012
// for use with map_TrackID to map tracks to different space
if(RECORD_ORIG) {
for( i=0 ; i<3 ; i++)
header1.origin[i] = Orig[i];
}
// at some point, we will have to convert indices into
// pseudo-locations; being forced into this choice means that
// different data set orientations would be represented differently
// and incorrectly in some instances... so, for now, we'll resample
// everything to RAI, and then resample back later. guess this will
// just slow things down slightly.
// have all be RAI for processing here
if(TV_switch[0] || TV_switch[1] || TV_switch[2]) {
dsetn = r_new_resam_dset(insetFA, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(insetFA);
insetFA=dsetn;
dsetn=NULL;
dsetn = r_new_resam_dset(insetMD, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(insetMD);
insetMD=dsetn;
dsetn=NULL;
dsetn = r_new_resam_dset(insetV1, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(insetV1);
insetV1=dsetn;
dsetn=NULL;
dsetn = r_new_resam_dset(insetL1, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(insetL1);
insetL1=dsetn;
dsetn=NULL;
dsetn = r_new_resam_dset(mset1, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(mset1);
mset1=dsetn;
dsetn=NULL;
dsetn = r_new_resam_dset(mset2, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(mset2);
mset2=dsetn;
dsetn=NULL;
if(EXTRAFILE) {
dsetn = r_new_resam_dset(insetEXTRA, NULL, 0.0, 0.0, 0.0,
dset_or, RESAM_NN_TYPE, NULL, 1, 0);
DSET_delete(insetEXTRA);
insetEXTRA=dsetn;
dsetn=NULL;
}
}
// ****************************************************************
// ****************************************************************
// make arrays for tracking
// ****************************************************************
// ****************************************************************
// for temp storage array, just a multiple of longest dimension!
if(Dim[0] > Dim[1])
ArrMax = Dim[0] * 4;
else
ArrMax = Dim[1] * 4;
if(4*Dim[2] > ArrMax)
ArrMax = Dim[2] * 4;
ROI1 = (int *)calloc(Nvox, sizeof(int));
ROI2 = (int *)calloc(Nvox, sizeof(int));
temp_arr = (short int *)calloc(Nvox, sizeof(short int));
temp_byte = (char *)calloc(Nvox, sizeof(char));
// temp storage whilst tracking
Tforw = calloc(ArrMax, sizeof(Tforw));
for(i=0 ; i<ArrMax ; i++)
Tforw[i] = calloc(3, sizeof(int));
Ttot = calloc(2*ArrMax , sizeof(Ttot));
for(i=0 ; i<2*ArrMax ; i++)
Ttot[i] = calloc(3, sizeof(int));
Tback = calloc(ArrMax, sizeof(Tback));
for(i=0 ; i<ArrMax ; i++)
Tback[i] = calloc(3, sizeof(int));
// temp storage whilst tracking, physical loc
flTforw = calloc(ArrMax, sizeof(flTforw));
for(i=0 ; i<ArrMax ; i++)
flTforw[i] = calloc(3, sizeof(int));
flTback = calloc(ArrMax,sizeof(flTback));
for(i=0 ; i<ArrMax ; i++)
flTback[i] = calloc(3, sizeof(int));
if( (ROI1 == NULL) || (ROI2 == NULL) || (temp_arr == NULL)
|| (Tforw == NULL) || (Tback == NULL) || (flTforw == NULL)
|| (flTback == NULL) || (Ttot == NULL)) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(12);
}
coorded = (float ****) calloc( Dim[0], sizeof(float ***) );
for ( i = 0 ; i < Dim[0] ; i++ )
coorded[i] = (float ***) calloc( Dim[1], sizeof(float **) );
for ( i = 0 ; i < Dim[0] ; i++ )
for ( j = 0 ; j < Dim[1] ; j++ )
coorded[i][j] = (float **) calloc( Dim[2], sizeof(float *) );
for ( i=0 ; i<Dim[0] ; i++ )
for ( j=0 ; j<Dim[1] ; j++ )
for ( k= 0 ; k<Dim[2] ; k++ ) //3 comp of V1 and FA
coorded[i][j][k] = (float *) calloc( 4, sizeof(float) );
INDEX = (int ****) calloc( Dim[0], sizeof(int ***) );
for ( i = 0 ; i < Dim[0] ; i++ )
INDEX[i] = (int ***) calloc( Dim[1], sizeof(int **) );
for ( i = 0 ; i < Dim[0] ; i++ )
for ( j = 0 ; j < Dim[1] ; j++ )
INDEX[i][j] = (int **) calloc( Dim[2], sizeof(int *) );
for ( i=0 ; i<Dim[0] ; i++ )
for ( j=0 ; j<Dim[1] ; j++ )
for ( k= 0 ; k<Dim[2] ; k++ )
INDEX[i][j][k] = (int *) calloc( 4, sizeof(int) );
// this statement will never be executed if allocation fails above
if( (INDEX == NULL) || (coorded == NULL) ) {
fprintf(stderr, "\n\n MemAlloc failure.\n\n");
exit(122);
}
for(i=0 ; i<Nvox ; i++) {
if(THD_get_voxel( mset1, i, 0) >0.5){
ROI1[i] = 1;
}
if(THD_get_voxel( mset2, i, 0) >0.5)
ROI2[i] = 1;
}
// set up eigvecs in 3D coord sys,
// mark off where ROIs are and keep index handy
idx=0;
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
for( m=0 ; m<3 ; m++ )
coorded[i][j][k][m] = THD_get_voxel(insetV1, idx, m);
if(EXTRAFILE)
coorded[i][j][k][3] = THD_get_voxel(insetEXTRA, idx, 0);
else
coorded[i][j][k][3] = THD_get_voxel(insetFA, idx, 0);
// make sure that |V1| == 1 for all eigenvects, otherwise it's
/// a problem in the tractography; currently, some from
// 3dDWItoDT do not have this property...
tempvmagn = sqrt(coorded[i][j][k][0]*coorded[i][j][k][0]+
coorded[i][j][k][1]*coorded[i][j][k][1]+
coorded[i][j][k][2]*coorded[i][j][k][2]);
if( tempvmagn<0.99 )
for( m=0 ; m<3 ; m++ )
coorded[i][j][k][m]/= tempvmagn;
INDEX[i][j][k][0] =idx; // first value is the index itself
if( ROI1[idx]==1 )
INDEX[i][j][k][1]=1; // second value identifies ROI1 mask
else
INDEX[i][j][k][1]=0;
if( ROI2[idx]==1 )
INDEX[i][j][k][2]=1; // third value identifies ROI2 mask
else
INDEX[i][j][k][2]=0;
// fourth value will be counter for number of kept tracks
// passing through
INDEX[i][j][k][3] = 0;
idx+= 1;
}
// *************************************************************
// *************************************************************
// Beginning of main loop
// *************************************************************
// *************************************************************
Numtract = 0;
ave_tract_len = 0.;
ave_tract_len_phys = 0.;
sprintf(OUT_bin,"%s.trk",prefix);
if( (fout0 = fopen(OUT_bin, "w")) == NULL) {
fprintf(stderr, "Error opening file %s.",OUT_bin);
exit(16);
}
fwrite(&header1,sizeof(tv_io_header),1,fout0);
if (get_tract_verb()) {
INFO_message("Begin tracking...");
}
tb = AppCreateBundle(NULL, 0, NULL, insetFA); // start bundle
id = 0;
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ )
if(coorded[i][j][k][3] >= MinFA) {
for( ii=0 ; ii<SeedPerV[0] ; ii++ )
for( jj=0 ; jj<SeedPerV[1] ; jj++ )
for( kk=0 ; kk<SeedPerV[2] ; kk++ ) {
in[0] = i;
in[1] = j;
in[2] = k;
physin[0] = ((float) in[0] +
(0.5 + (float) ii)/SeedPerV[0])*Ledge[0];
physin[1] = ((float) in[1] +
(0.5 + (float) jj)/SeedPerV[1])*Ledge[1];
physin[2] = ((float) in[2] +
(0.5 + (float) kk)/SeedPerV[2])*Ledge[2];
len_forw = TrackIt(coorded, in, physin, Ledge, Dim,
MinFA, MaxAng, ArrMax, Tforw,
flTforw, 1, phys_forw);
// reset, because it's changed in TrackIt func
in[0] = i;
in[1] = j;
in[2] = k;
physin[0] = ((float) in[0] +
(0.5 + (float) ii)/SeedPerV[0])*Ledge[0];
physin[1] = ((float) in[1] +
(0.5 + (float) jj)/SeedPerV[1])*Ledge[1];
physin[2] = ((float) in[2] +
(0.5 + (float) kk)/SeedPerV[2])*Ledge[2];
len_back = TrackIt(coorded, in, physin, Ledge, Dim,
MinFA, MaxAng, ArrMax, Tback,
flTback, -1, phys_back);
KEEPIT = 0; // a simple switch
totlen = len_forw+len_back-1; // NB: overlap of starts
totlen_phys = phys_forw[0] + phys_back[0];
if( totlen_phys >= MinL ) {
// glue together for simpler notation later
for( n=0 ; n<len_back ; n++) { // all of this
rr = len_back-n-1; // read in backward
for(m=0;m<3;m++)
Ttot[rr][m] = Tback[n][m];
}
for( n=1 ; n<len_forw ; n++){// skip first->overlap
rr = n+len_back-1; // put after
for(m=0;m<3;m++)
Ttot[rr][m] = Tforw[n][m];
}
// <<So close and orthogonal condition>>:
// test projecting ends, to see if they abut ROI.
for(m=0;m<3;m++) {
//actual projected ends
end[1][m] = 2*Ttot[totlen-1][m]-Ttot[totlen-2][m];
end[0][m] = 2*Ttot[0][m]-Ttot[1][m];
// default choice, just retest known ends
// as default
test_ind[1][m] = test_ind[0][m] = Ttot[0][m];
}
tt = Create_Tract(len_back, flTback, len_forw,
flTforw, id, insetFA); ++id;
if (LOG_TYPE == -1) {
KEEPIT = 1;
} else {
inroi1 = 0;
// check forw
for( n=0 ; n<len_forw ; n++) {
if(INDEX[Tforw[n][0]][Tforw[n][1]][Tforw[n][2]][1]==1){
inroi1 = 1;
break;
} else
continue;
}
if( inroi1==0 ){// after 1st half, check 2nd half
for( m=0 ; m<len_back ; m++) {
if(INDEX[Tback[m][0]][Tback[m][1]][Tback[m][2]][1]==1){
inroi1 = 1;
break;
} else
continue;
}
}
// after 1st&2nd halves, check bound/neigh
if( inroi1==0 ) {
if(INDEX[test_ind[1][0]][test_ind[1][1]][test_ind[1][2]][1]==1)
inroi1 = 1;
if(INDEX[test_ind[0][0]][test_ind[0][1]][test_ind[0][2]][1]==1)
inroi1 = 1;
}
if( ((LOG_TYPE ==0) && (inroi1 ==0)) ||
((LOG_TYPE ==1) && (inroi1 ==1))) {
// have to check in ROI2
inroi2 = 0;
// check forw
for( n=0 ; n<len_forw ; n++) {
if(INDEX[Tforw[n][0]][Tforw[n][1]][Tforw[n][2]][2]==1){
inroi2 = 1;
break;
} else
continue;
}
//after 1st half, check 2nd half
if( inroi2==0 ) {
for( m=0 ; m<len_back ; m++) {
if(INDEX[Tback[m][0]][Tback[m][1]][Tback[m][2]][2]==1){
inroi2 = 1;
break;
} else
continue;
}
}
// after 1st&2nd halves, check bound/neigh
if( inroi2==0 ) {
if(INDEX[test_ind[1][0]][test_ind[1][1]][test_ind[1][2]][2]==1)
inroi2 = 1;
if(INDEX[test_ind[0][0]][test_ind[0][1]][test_ind[0][2]][2]==1)
inroi2 = 1;
}
// for both cases, need to see it here to keep
if( inroi2 ==1 )
KEEPIT = 1; // otherwise, it's gone
} else if((LOG_TYPE ==0) && (inroi1 ==1))
KEEPIT = 1;
}
}
// by now, we *know* if we're keeping this or not.
if( KEEPIT == 1 ) {
tb = AppCreateBundle(tb, 1, tt, NULL);
tt = Free_Tracts(tt, 1);
READS_in = totlen;
fwrite(&READS_in,sizeof(READS_in),1,fout0);
for( n=0 ; n<len_back ; n++) {
//put this one in backwords, to make it connect
m = len_back - 1 - n;
for(aa=0 ; aa<3 ; aa++) {
// recenter phys loc for trackvis, if nec...
// just works this way (where they define
// origin)
READS_fl = flTback[m][aa];
if(!TV_switch[aa])
READS_fl = Ledge[aa]*Dim[aa]-READS_fl;
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
}
mm = INDEX[Tback[m][0]][Tback[m][1]][Tback[m][2]][0];
READS_fl =THD_get_voxel(insetFA, mm, 0); // FA
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
READS_fl =THD_get_voxel(insetMD, mm, 0); // MD
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
READS_fl =THD_get_voxel(insetL1, mm, 0); // L1
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
// count this voxel for having a tract
INDEX[Tback[m][0]][Tback[m][1]][Tback[m][2]][3]+= 1;
}
for( m=1 ; m<len_forw ; m++) {
for(aa=0 ; aa<3 ; aa++) {
// recenter phys loc for trackvis, if nec...
READS_fl = flTforw[m][aa];
if(!TV_switch[aa])
READS_fl = Ledge[aa]*Dim[aa]-READS_fl;
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
}
mm = INDEX[Tforw[m][0]][Tforw[m][1]][Tforw[m][2]][0];
READS_fl =THD_get_voxel(insetFA, mm, 0); // FA
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
READS_fl =THD_get_voxel(insetMD, mm, 0); // MD
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
READS_fl =THD_get_voxel(insetL1, mm, 0); // L1
fwrite(&READS_fl,sizeof(READS_fl),1,fout0);
// count this voxel for having a tract
INDEX[Tforw[m][0]][Tforw[m][1]][Tforw[m][2]][3]+= 1;
}
ave_tract_len+= totlen;
ave_tract_len_phys+= totlen_phys;
Numtract+=1;
}
}
}
fclose(fout0);
if (get_tract_verb()) {
INFO_message("Done tracking, have %d tracks.", tb->N_tracts);
Show_Taylor_Bundle(tb, NULL, 3);
}
if (!Write_Bundle(tb,prefix,mode)) {
ERROR_message("Failed to write the bundle");
}
// **************************************************************
// **************************************************************
// Some simple stats on ROIs and outputs
// **************************************************************
// **************************************************************
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
if( INDEX[i][j][k][3]>=1 ) {
tempMD = THD_get_voxel(insetMD,INDEX[i][j][k][0],0);
tempFA = THD_get_voxel(insetFA,INDEX[i][j][k][0],0);
tempL1 = THD_get_voxel(insetL1,INDEX[i][j][k][0],0);
tempRD = 0.5*(3*tempMD-tempL1);
roi3_mu_MD+= tempMD;
roi3_mu_FA+= tempFA;
roi3_mu_L1+= tempL1;
roi3_mu_RD+= tempRD;
roi3_sd_MD+= tempMD*tempMD;
roi3_sd_FA+= tempFA*tempFA;
roi3_sd_L1+= tempL1*tempL1;
roi3_sd_RD+= tempRD*tempRD;
roi3_ct+= 1;
}
}
if(roi3_ct > 0 ) { // !!!! make into afni file
roi3_mu_MD/= (float) roi3_ct;
roi3_mu_FA/= (float) roi3_ct;
roi3_mu_L1/= (float) roi3_ct;
roi3_mu_RD/= (float) roi3_ct;
roi3_sd_MD-= roi3_ct*roi3_mu_MD*roi3_mu_MD;
roi3_sd_FA-= roi3_ct*roi3_mu_FA*roi3_mu_FA;
roi3_sd_L1-= roi3_ct*roi3_mu_L1*roi3_mu_L1;
roi3_sd_RD-= roi3_ct*roi3_mu_RD*roi3_mu_RD;
roi3_sd_MD/= (float) roi3_ct-1;
roi3_sd_FA/= (float) roi3_ct-1;
roi3_sd_L1/= (float) roi3_ct-1;
roi3_sd_RD/= (float) roi3_ct-1;
roi3_sd_MD = sqrt(roi3_sd_MD);
roi3_sd_FA = sqrt(roi3_sd_FA);
roi3_sd_L1 = sqrt(roi3_sd_L1);
roi3_sd_RD = sqrt(roi3_sd_RD);
sprintf(OUT_tracstat,"%s.stats",prefix);
if( (fout0 = fopen(OUT_tracstat, "w")) == NULL) {
fprintf(stderr, "Error opening file %s.",OUT_tracstat);
exit(19);
}
fprintf(fout0,"%d\t%d\n",Numtract,roi3_ct);
fprintf(fout0,"%.3f\t%.3f\n",ave_tract_len/Numtract,
ave_tract_len_phys/Numtract);
// as usual, these next values would have to be divided by the
// bval to get their actual value in standard phys units
fprintf(fout0,"%.4f\t%.4f\n",roi3_mu_FA,roi3_sd_FA);
fprintf(fout0,"%.4f\t%.4f\n",roi3_mu_MD,roi3_sd_MD);
fprintf(fout0,"%.4f\t%.4f\n",roi3_mu_RD,roi3_sd_RD);
fprintf(fout0,"%.4f\t%.4f\n",roi3_mu_L1,roi3_sd_L1);
fclose(fout0);
sprintf(prefix_map,"%s_MAP",prefix);
sprintf(prefix_mask,"%s_MASK",prefix);
outsetMAP = EDIT_empty_copy( mset1 ) ;
EDIT_dset_items( outsetMAP ,
ADN_datum_all , MRI_short ,
ADN_prefix , prefix_map ,
ADN_none ) ;
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetMAP)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetMAP));
outsetMASK = EDIT_empty_copy( mset1 ) ;
EDIT_dset_items( outsetMASK ,
ADN_datum_all , MRI_byte ,
ADN_prefix , prefix_mask ,
ADN_none ) ;
if(!THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetMASK)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetMASK));
m=0;
for( k=0 ; k<Dim[2] ; k++ )
for( j=0 ; j<Dim[1] ; j++ )
for( i=0 ; i<Dim[0] ; i++ ) {
temp_arr[m]=INDEX[i][j][k][3];
if(temp_arr[m]>0.5)
temp_byte[m]=1;
else
temp_byte[m]=0;
m++;
}
// re-orient the data as original inputs
// (this function copies the pointer)
EDIT_substitute_brick(outsetMAP, 0, MRI_short, temp_arr);
temp_arr=NULL;
if(TV_switch[0] || TV_switch[1] || TV_switch[2]) {
dsetn = r_new_resam_dset(outsetMAP, NULL, 0.0, 0.0, 0.0,
header1.voxel_order, RESAM_NN_TYPE,
NULL, 1, 0);
DSET_delete(outsetMAP);
outsetMAP=dsetn;
dsetn=NULL;
}
EDIT_dset_items( outsetMAP ,
ADN_prefix , prefix_map ,
ADN_none ) ;
THD_load_statistics(outsetMAP );
if( !THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetMAP)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetMAP));
tross_Make_History( "3dTrackID" , argc , argv , outsetMAP) ;
THD_write_3dim_dataset(NULL, NULL, outsetMAP, True);
// re-orient the data as original inputs
EDIT_substitute_brick(outsetMASK, 0, MRI_byte, temp_byte);
temp_byte=NULL;
if(TV_switch[0] || TV_switch[1] || TV_switch[2]) {
dsetn = r_new_resam_dset(outsetMASK, NULL, 0.0, 0.0, 0.0,
header1.voxel_order, RESAM_NN_TYPE,
NULL, 1, 0);
DSET_delete(outsetMASK);
outsetMASK=dsetn;
dsetn=NULL;
}
EDIT_dset_items( outsetMASK ,
ADN_prefix , prefix_mask ,
ADN_none ) ;
THD_load_statistics(outsetMASK);
if(!THD_ok_overwrite() && THD_is_ondisk(DSET_HEADNAME(outsetMASK)) )
ERROR_exit("Can't overwrite existing dataset '%s'",
DSET_HEADNAME(outsetMASK));
tross_Make_History( "3dTrackID" , argc , argv , outsetMASK) ;
THD_write_3dim_dataset(NULL, NULL, outsetMASK, True);
INFO_message("Number of tracts found = %d",Numtract) ;
}
else
INFO_message("\n No Tracts Found!!!\n");
// ************************************************************
// ************************************************************
// Freeing
// ************************************************************
// ************************************************************
// !!! need to free afni-sets?
DSET_delete(insetFA);
DSET_delete(insetMD);
DSET_delete(insetL1);
DSET_delete(insetV1);
DSET_delete(insetEXTRA);
//DSET_delete(outsetMAP);
//DSET_delete(outsetMASK);
DSET_delete(mset2);
DSET_delete(mset1);
free(prefix);
free(insetV1);
free(insetFA);
free(mset1);
free(mset2);
free(insetEXTRA);
free(ROI1);
free(ROI2);
free(temp_byte);
for( i=0 ; i<ArrMax ; i++) {
free(Tforw[i]);
free(Tback[i]);
free(flTforw[i]);
free(flTback[i]);
}
free(Tforw);
free(Tback);
free(flTforw);
free(flTback);
for( i=0 ; i<Dim[0] ; i++)
for( j=0 ; j<Dim[1] ; j++)
for( k=0 ; k<Dim[2] ; k++)
free(coorded[i][j][k]);
for( i=0 ; i<Dim[0] ; i++)
for( j=0 ; j<Dim[1] ; j++)
free(coorded[i][j]);
for( i=0 ; i<Dim[0] ; i++)
free(coorded[i]);
free(coorded);
for( i=0 ; i<Dim[0] ; i++)
for( j=0 ; j<Dim[1] ; j++)
for( k=0 ; k<Dim[2] ; k++)
free(INDEX[i][j][k]);
for( i=0 ; i<Dim[0] ; i++)
for( j=0 ; j<Dim[1] ; j++)
free(INDEX[i][j]);
for( i=0 ; i<Dim[0] ; i++)
free(INDEX[i]);
free(INDEX);
free(temp_arr); // need to free
for( i=0 ; i<2*ArrMax ; i++)
free(Ttot[i]);
free(Ttot);
//free(mode);
return 0;
}
THD_3dim_dataset * THD_localhistog( int nsar , THD_3dim_dataset **insar ,
int numval , int *rlist , MCW_cluster *nbhd ,
int do_prob , int verb )
{
THD_3dim_dataset *outset=NULL , *inset ;
int nvox=DSET_NVOX(insar[0]) ;
int ids, iv, bb, nnpt=nbhd->num_pt ;
MRI_IMAGE *bbim ; int btyp ;
float **outar , **listar ;
ENTRY("THD_localhistog") ;
/*---- create output dataset ----*/
outset = EDIT_empty_copy(insar[0]) ;
EDIT_dset_items( outset ,
ADN_nvals , numval ,
ADN_datum_all , MRI_float ,
ADN_nsl , 0 ,
ADN_brick_fac , NULL ,
ADN_none ) ;
outar = (float **)malloc(sizeof(float *)*numval) ;
for( bb=0 ; bb < numval ; bb++ ){
EDIT_substitute_brick( outset , bb , MRI_float , NULL ) ;
outar[bb] = DSET_BRICK_ARRAY(outset,bb) ;
}
/*---- make mapping between values and arrays to get those values ----*/
listar = (float **)malloc(sizeof(float *)*TWO16) ;
for( bb=0 ; bb < TWO16 ; bb++ ) listar[bb] = outar[0] ;
for( bb=1 ; bb < numval ; bb++ ){
listar[ rlist[bb] + TWO15 ] = outar[bb] ;
}
/*----------- loop over datasets, add in counts for all voxels -----------*/
for( ids=0 ; ids < nsar ; ids++ ){ /* dataset loop */
inset = insar[ids] ; DSET_load(inset) ;
for( iv=0 ; iv < DSET_NVALS(inset) ; iv++ ){ /* sub-brick loop */
if( verb ) fprintf(stderr,".") ;
bbim = DSET_BRICK(inset,iv) ; btyp = bbim->kind ;
if( nnpt == 1 ){ /* only 1 voxel in nbhd */
int qq,ii,jj,kk,ib,nb ;
switch( bbim->kind ){
case MRI_short:{
short *sar = MRI_SHORT_PTR(bbim) ;
for( qq=0 ; qq < nvox ; qq++ ) listar[sar[qq]+TWO15][qq]++ ;
}
break ;
case MRI_byte:{
byte *bar = MRI_BYTE_PTR(bbim) ;
for( qq=0 ; qq < nvox ; qq++ ) listar[bar[qq]+TWO15][qq]++ ;
}
break ;
case MRI_float:{
float *far = MRI_FLOAT_PTR(bbim) ; short ss ;
for( qq=0 ; qq < nvox ; qq++ ){ ss = SHORTIZE(far[qq]); listar[ss+TWO15][qq]++; }
}
break ;
}
} else { /* multiple voxels in nbhd */
AFNI_OMP_START ;
#pragma omp parallel
{ int qq,ii,jj,kk,ib,nb ; void *nar ; short *sar,ss ; byte *bar ; float *far ;
nar = malloc(sizeof(float)*nnpt) ;
sar = (short *)nar ; bar = (byte *)nar ; far = (float *)nar ;
#pragma omp for
for( qq=0 ; qq < nvox ; qq++ ){ /* qq=voxel index */
ii = DSET_index_to_ix(inset,qq) ;
jj = DSET_index_to_jy(inset,qq) ;
kk = DSET_index_to_kz(inset,qq) ;
nb = mri_get_nbhd_array( bbim , NULL , ii,jj,kk , nbhd , nar ) ;
if( nb == 0 ) continue ;
switch( btyp ){
case MRI_short:
for( ib=0 ; ib < nb ; ib++ ) listar[sar[ib]+TWO15][qq]++ ;
break ;
case MRI_byte:
for( ib=0 ; ib < nb ; ib++ ) listar[bar[ib]+TWO15][qq]++ ;
break ;
case MRI_float:
for( ib=0 ; ib < nb ; ib++ ){ ss = SHORTIZE(far[ib]); listar[ss+TWO15][qq]++; }
break ;
}
} /* end of voxel loop */
free(nar) ;
} /* end of OpenMP */
AFNI_OMP_END ;
}
} /* end of sub-brick loop */
DSET_unload(inset) ;
} /* end of dataset loop */
if( verb ) fprintf(stderr,"\n") ;
free(listar) ;
/*---- post-process output ---*/
if( do_prob ){
byte **bbar ; int pp ;
if( verb ) INFO_message("Conversion to probabilities") ;
AFNI_OMP_START ;
#pragma omp parallel
{ int qq , ib ; float pfac , val ; byte **bbar ;
#pragma omp for
for( qq=0 ; qq < nvox ; qq++ ){
pfac = 0.0001f ;
for( ib=0 ; ib < numval ; ib++ ) pfac += outar[ib][qq] ;
pfac = 250.0f / pfac ;
for( ib=0 ; ib < numval ; ib++ ){
val = outar[ib][qq]*pfac ; outar[ib][qq] = BYTEIZE(val) ;
}
}
} /* end OpenMP */
AFNI_OMP_END ;
bbar = (byte **)malloc(sizeof(byte *)*numval) ;
for( bb=0 ; bb < numval ; bb++ ){
bbar[bb] = (byte *)malloc(sizeof(byte)*nvox) ;
for( pp=0 ; pp < nvox ; pp++ ) bbar[bb][pp] = (byte)outar[bb][pp] ;
EDIT_substitute_brick(outset,bb,MRI_byte,bbar[bb]) ;
EDIT_BRICK_FACTOR(outset,bb,0.004f) ;
}
free(bbar) ;
} /* end of do_prob */
free(outar) ;
RETURN(outset) ;
}
MRI_shindss * GRINCOR_read_input( char *fname )
{
NI_element *nel=NULL ;
char *dfname=NULL , *atr ;
NI_float_array *facar ; NI_int_array *nvar, *nnode=NULL, *ninmask=NULL;
MRI_shindss *shd ;
long long nbytes_needed , nbytes_dfname=0 ; int fdes ;
void *var ; int ids , nvmax , nvtot ;
int datum , datum_size ;
char *geometry_string=NULL ;
THD_3dim_dataset *tdset=NULL; int nvox;
int no_ivec=0 , *ivec=NULL , *nvals=NULL , nvec,ndset ; float *fac=NULL ;
NI_str_array *slabar=NULL ;
if( fname == NULL || *fname == '\0' ) GQUIT(NULL) ;
/* get data element */
if (!THD_is_ondisk(fname))
GQUIT("not on disk") ;
nelshd = nel = NI_read_element_fromfile(fname) ;
if( nel == NULL || nel->type != NI_ELEMENT_TYPE )
GQUIT("not properly formatted") ;
if( strcmp(nel->name,"3dGroupInCorr") != 0 )
GQUIT("data element name is not '3dGroupInCorr'") ;
/* no data vector ==> using all voxels */
no_ivec = ( nel->vec_num < 1 ||
nel->vec_len < 1 || nel->vec_typ[0] != NI_INT ) ;
/* number of vectors in each dataset */
atr = NI_get_attribute(nel,"nvec");
if( atr == NULL ) GQUIT("nvec attribute missing?") ;
nvec = (int)strtod(atr,NULL) ;
if( nvec < 2 || (!no_ivec && nel->vec_len != nvec) )
GQUIT("nvec attribute has illegal value") ;
/* number of datasets */
atr = NI_get_attribute(nel,"ndset");
if( atr == NULL ) GQUIT("ndset attribute missing") ;
ndset = (int)strtod(atr,NULL) ;
if( ndset < 1 ) GQUIT("ndset attribute has illegal value") ;
/* number of time points in each dataset (varies with dataset) */
atr = NI_get_attribute(nel,"nvals");
if( atr == NULL ) GQUIT("nvals attribute missing") ;
nvar = NI_decode_int_list(atr,",") ;
if( nvar == NULL || nvar->num < ndset )
GQUIT("nvals attribute doesn't match ndset") ;
nvals = nvar->ar ; nvar->ar = NULL ; NI_delete_int_array(nvar) ;
nvmax = nvtot = nvals[0] ;
for( ids=1 ; ids < ndset ; ids++ ){ /* Feb 2011 */
nvtot += nvals[ids] ;
if( nvals[ids] > nvmax ) nvmax = nvals[ids] ;
}
/* dataset labels [23 May 2010] */
atr = NI_get_attribute(nel,"dset_labels") ;
if( atr != NULL ){
slabar = NI_decode_string_list(atr,";,") ;
if( slabar == NULL || slabar->num < ndset )
GQUIT("dset_labels attribute invalid") ;
}
/* datum of datasets */
atr = NI_get_attribute(nel,"datum") ;
if( atr != NULL && strcasecmp(atr,"byte") == 0 ){
datum = 1 ; datum_size = sizeof(sbyte) ;
} else {
datum = 2 ; datum_size = sizeof(short) ;
}
/* number of bytes needed:
sizeof(datum) * number of vectors per dataset
* number of datasets
* sum of per dataset vector lengths */
nbytes_needed = 0 ;
for( ids=0 ; ids < ndset ; ids++ ) nbytes_needed += nvals[ids] ;
nbytes_needed *= ((long long)nvec) * datum_size ;
if( nbytes_needed >= twogig &&
( sizeof(void *) < 8 || sizeof(size_t) < 8 ) ) /* too much for 32-bit */
GQUIT("datafile size exceeds 2 GB -- you need a 64-bit computer!") ;
/* scale factor for each dataset */
atr = NI_get_attribute(nel,"fac") ;
if( atr == NULL ) GQUIT("fac attribute missing") ;
facar = NI_decode_float_list(atr,",") ;
if( facar == NULL || facar->num < ndset )
GQUIT("can't decode fac attribute") ;
fac = facar->ar ; facar->ar = NULL ; NI_delete_float_array(facar) ;
for( ids=0 ; ids < ndset ; ids++ ) if( fac[ids] <= 0.0f ) fac[ids] = 1.0f ;
/* grid definition */
atr = NI_get_attribute(nel,"geometry") ;
if( atr == NULL ) GQUIT("geometry attribute missing") ;
geometry_string = strdup(atr) ;
tdset = EDIT_geometry_constructor( geometry_string , "GrpInCorr" ) ;
if( tdset == NULL ) GQUIT("can't decode geometry attribute") ;
nvox = DSET_NVOX(tdset) ;
if( no_ivec && nvox != nvec )
GQUIT("geometry attribute doesn't match nvec attribute") ;
if( !no_ivec && nvox < nvec )
GQUIT("geometry attribute specifies too few voxels") ;
/* name of data file: check its size against what's needed */
#if 0
atr = NI_get_attribute(nel,"datafile") ;
if( atr != NULL ){
dfname = strdup(atr) ; nbytes_dfname = THD_filesize(dfname) ;
if( nbytes_dfname <= 0 && strstr(dfname,"/") != NULL ){
char *tnam = THD_trailname(atr,0) ;
nbytes_dfname = THD_filesize(tnam) ;
if( nbytes_dfname > 0 ){ free(dfname); dfname = strdup(tnam); }
}
}
#endif
if( nbytes_dfname <= 0 && strstr(fname,".niml") != NULL ){
if( dfname != NULL ) free(dfname) ;
dfname = strdup(fname) ; strcpy(dfname+strlen(dfname)-5,".data") ;
nbytes_dfname = THD_filesize(dfname) ;
}
if( nbytes_dfname <= 0 ){
char mess[THD_MAX_NAME+256] ;
sprintf(mess,"datafile is missing (%s)",dfname) ; GQUIT(mess) ;
} else if( nbytes_dfname < nbytes_needed ){
char mess[THD_MAX_NAME+1024] ;
sprintf(mess,"datafile %s has %s bytes but needs at least %s",
dfname ,
commaized_integer_string(nbytes_dfname) ,
commaized_integer_string(nbytes_needed) ) ;
GQUIT(mess) ;
} else {
INFO_message("EIC: data file %s found with %s bytes of data",
dfname , commaized_integer_string(nbytes_dfname) ) ;
}
fdes = open( dfname , O_RDWR ) ;
if( fdes < 0 ){
char mess[THD_MAX_NAME+256] ;
sprintf(mess,"can't open datafile (%s)",dfname) ; GQUIT(mess) ;
}
NI_set_attribute( nelshd , "datafile" , dfname ) ;
/* ivec[i] is the voxel spatial index of the i-th vector */
if( no_ivec ){
ivec = NULL ; /* means all voxels: ivec[i] == i */
} else {
ivec = (int *)nel->vec[0] ; /* copy pointer */
nel->vec[0] = NULL ; /* NULL out in element so won't be free-ed */
}
/* And stuff for LR surface pairs ZSS Jan 09*/
if ((atr=NI_get_attribute(nel,"LRpair_nnode"))) {
nnode = NI_decode_int_list(atr,",") ;
}
if ((atr=NI_get_attribute(nel,"LRpair_ninmask"))) {
ninmask = NI_decode_int_list(atr,",") ;
}
/* create output struct */
shd = (MRI_shindss *)malloc(sizeof(MRI_shindss)) ;
shd->nvals = nvals ; shd->nvals_max = nvmax ; shd->nvals_tot = nvtot ;
shd->nvec = nvec ;
shd->ndset = ndset ;
shd->geometry_string = geometry_string ;
shd->tdset = tdset ;
shd->dfname = dfname ;
shd->nvox = nvox ;
shd->nx = DSET_NX(tdset); shd->ny = DSET_NY(tdset); shd->nz = DSET_NZ(tdset);
shd->ivec = ivec ;
shd->fac = fac ;
/* and surface fields... ZSS Jan 09 */
if (nnode) {
if (nnode->num != 2) GQUIT("LRpair_nnode must have 2 values");
shd->nnode[0] = nnode->ar[0];
shd->nnode[1] = nnode->ar[1];
NI_delete_int_array(nnode); nnode=NULL;
} else {
shd->nnode[0] = shd->nnode[1] = -1 ;
}
if (ninmask) {
if (ninmask->num != 2) GQUIT("LRpair_ninmask must have 2 values");
shd->ninmask[0] = ninmask->ar[0];
shd->ninmask[1] = ninmask->ar[1];
NI_delete_int_array(ninmask); ninmask=NULL;
} else {
shd->ninmask[0] = shd->ninmask[1] = -1 ;
}
/*--- 07 Apr 2010: setup default use list (all of them) ---*/
shd->nuse = ndset ;
shd->use = (int *)malloc(sizeof(int)*ndset) ;
for( ids=0 ; ids < ndset ; ids++ ) shd->use[ids] = ids ;
shd->dslab = (slabar != NULL) ? slabar->str : NULL ; /* 23 May 2010 */
/*--- now have to map data from disk ---*/
var = mmap( 0 , (size_t)nbytes_needed ,
PROT_WRITE , THD_MMAP_FLAG , fdes , 0 ) ;
close(fdes) ; /* close file descriptor does not unmap data */
if( var == (void *)(-1) ){ /* this is bad */
ERROR_message(
"EIC: file %s: can't mmap() datafile -- memory space exhausted?" , dfname ) ;
free(shd) ; return NULL ;
}
/*-- create array of pointers to each dataset's data array --*/
shd->datum = datum ;
if( datum == 2 ){ /* shorts */
shd->sv = (short **)malloc(sizeof(short *)*ndset) ;
shd->bv = NULL ;
shd->sv[0] = (short *)var ;
for( ids=1 ; ids < ndset ; ids++ )
shd->sv[ids] = shd->sv[ids-1] + nvals[ids-1]*nvec ;
} else { /* sbytes */
shd->sv = NULL ;
shd->bv = (sbyte **)malloc(sizeof(sbyte *)*ndset) ;
shd->bv[0] = (sbyte *)var ;
for( ids=1 ; ids < ndset ; ids++ )
shd->bv[ids] = shd->bv[ids-1] + nvals[ids-1]*nvec ;
}
shd->nbytes = nbytes_needed ;
return shd ;
}
/*! Replace a voxel's value by the value's rank in the entire set of input datasets */
int main( int argc , char * argv[] )
{
THD_3dim_dataset ** dsets_in = NULL, *dset=NULL; /*input and output datasets*/
int nopt=0, nbriks=0, nsubbriks=0, ib=0, isb=0;
byte *cmask=NULL;
int *all_uniques=NULL, **uniques=NULL, *final_unq=NULL, *N_uniques=NULL;
int N_final_unq=0, iun=0, total_unq=0;
INT_HASH_DATUM *rmap=NULL, *hd=NULL;
int imax=0, iunq=0, ii=0, id = 0;
long int off=0;
char *prefix=NULL;
char stmp[THD_MAX_PREFIX+1]={""};
FILE *fout=NULL;
/*----- Read command line -----*/
if( argc < 2 || strcmp(argv[1],"-help") == 0 ){
Rank_help ();
exit(0) ;
}
mainENTRY("3dRank main"); machdep(); AFNI_logger("3dRank",argc,argv);
nopt = 1 ;
while( nopt < argc && argv[nopt][0] == '-' ){
if( strcmp(argv[nopt],"-ver") == 0 ){
PRINT_VERSION("3dRank"); AUTHOR("Ziad Saad");
nopt++; continue;
}
if( strcmp(argv[nopt],"-help") == 0 ){
Rank_help();
exit(0) ;
}
if( strcmp(argv[nopt],"-prefix") == 0 ){
++nopt;
if (nopt>=argc) {
fprintf(stderr,"**ERROR: Need string after -prefix\n");
exit(1);
}
prefix = argv[nopt] ;
++nopt; continue;
}
if( strcmp(argv[nopt],"-input") == 0 ){
dsets_in = (THD_3dim_dataset**)
calloc(argc-nopt+1, sizeof(THD_3dim_dataset*));
++nopt; nbriks=0;
while (nopt < argc ) {
dsets_in[nbriks] = THD_open_dataset( argv[nopt] );
if( !ISVALID_DSET(dsets_in[nbriks]) ){
fprintf(stderr,"**ERROR: can't open dataset %s\n",argv[nopt]) ;
exit(1);
}
++nopt; ++nbriks;
}
continue;
}
ERROR_exit( " Error - unknown option %s", argv[nopt]);
}
if (nopt < argc) {
ERROR_exit( " Error unexplained trailing option: %s\n", argv[nopt]);
}
if (!nbriks) {
ERROR_exit( " Error no volumes entered on command line?");
}
/* some checks and inits*/
nsubbriks = 0;
for (ib = 0; ib<nbriks; ++ib) {
if (!is_integral_dset(dsets_in[ib], 0)) {
ERROR_exit("Dset %s is not of an integral data type.",
DSET_PREFIX(dsets_in[ib]));
}
nsubbriks += DSET_NVALS(dsets_in[ib]);
}
/* Now get unique arrays */
uniques = (int **)calloc(nsubbriks, sizeof(int*));
N_uniques = (int *)calloc(nsubbriks, sizeof(int));
total_unq = 0;
iun = 0;
for (ib = 0; ib<nbriks; ++ib) {
DSET_mallocize(dsets_in[ib]); DSET_load(dsets_in[ib]);
for (isb=0; isb<DSET_NVALS(dsets_in[ib]); ++isb) {
uniques[iun] = THD_unique_vals(dsets_in[ib], isb,
&(N_uniques[iun]), cmask);
total_unq += N_uniques[iun];
++iun;
}
}
/* put all the arrays together and get the unique of the uniques */
all_uniques = (int *)calloc(total_unq, sizeof(int));
off=0;
for (iun=0; iun<nsubbriks; ++iun) {
memcpy(all_uniques+off, uniques[iun], N_uniques[iun]*sizeof(int));
off += N_uniques[iun];
}
/* free intermediate unique arrays */
for (iun=0; iun<nsubbriks; ++iun) {
free(uniques[iun]);
}
free(uniques); uniques=NULL;
free(N_uniques); N_uniques=NULL;
/* get unique of catenated array */
if (!(final_unq = UniqueInt (all_uniques, total_unq, &N_final_unq, 0 ))) {
ERROR_exit( " Failed to get unique list (%d, %d, %d) ",
total_unq, N_final_unq, nsubbriks);
}
free(all_uniques); all_uniques=NULL;
if (prefix) {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"%s.rankmap.1D", prefix);
} else {
if (nbriks == 1) {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"%s.rankmap.1D", DSET_PREFIX(dsets_in[0]));
} else {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"%s+.rankmap.1D", DSET_PREFIX(dsets_in[0]));
}
}
if (stmp[0]) {
if ((fout = fopen(stmp,"w"))) {
fprintf(fout, "#Rank Map (%d unique values)\n", N_final_unq);
fprintf(fout, "#Col. 0: Rank\n");
fprintf(fout, "#Col. 1: Input Dset Value\n");
}
}
/* get the maximum integer in the unique array */
imax = 0;
for (iunq=0; iunq<N_final_unq; ++iunq) {
if (final_unq[iunq] > imax) imax = final_unq[iunq];
if (fout) fprintf(fout, "%d %d\n", iunq, final_unq[iunq]);
hd = (INT_HASH_DATUM*)calloc(1,sizeof(INT_HASH_DATUM));
hd->id = final_unq[iunq];
hd->index = iunq;
HASH_ADD_INT(rmap, id, hd);
}
fclose(fout); fout=NULL;
/* now cycle over all dsets and replace their voxel values with rank */
for (ib = 0; ib<nbriks; ++ib) {
for (isb=0; isb<DSET_NVALS(dsets_in[ib]); ++isb) {
EDIT_BRICK_LABEL( dsets_in[ib],isb, "rank" ) ;
EDIT_BRICK_TO_NOSTAT( dsets_in[ib],isb ) ;
EDIT_BRICK_FACTOR( dsets_in[ib],isb, 0.0);/* no factors for rank*/
switch (DSET_BRICK_TYPE(dsets_in[ib],isb) ){
default:
fprintf(stderr,
"** Bad dset type for unique operation.\n"
"Only Byte, Short, and float dsets are allowed.\n");
break ; /* this should not happen here,
so don't bother returning*/
case MRI_short:{
short *mar = (short *) DSET_ARRAY(dsets_in[ib],isb) ;
if (imax > MRI_TYPE_maxval[MRI_short]) {
WARNING_message("Maximum rank value of %d is\n"
"than maximum value for dset datatype of %d\n",
imax, MRI_TYPE_maxval[MRI_short]);
}
for( ii=0 ; ii < DSET_NVOX(dsets_in[ib]) ; ii++ )
if (!cmask || cmask[ii]) {
id = (int)mar[ii];
HASH_FIND_INT(rmap,&id ,hd);
if (hd) mar[ii] = (short)(hd->index);
else
ERROR_exit("** Failed to find key %d in hash table\n",id);
} else mar[ii] = 0;
}
break ;
case MRI_byte:{
byte *mar ;
if (imax > MRI_TYPE_maxval[MRI_short]) {
WARNING_message("Maximum rank value of %d is\n"
"than maximum value for dset datatype of %d\n",
imax, MRI_TYPE_maxval[MRI_byte]);
}
mar = (byte *) DSET_ARRAY(dsets_in[ib],isb) ;
for( ii=0 ; ii < DSET_NVOX(dsets_in[ib]) ; ii++ )
if (!cmask || cmask[ii]) {
id = (int)mar[ii];
HASH_FIND_INT(rmap,&id ,hd);
if (hd) mar[ii] = (byte)(hd->index);
else
ERROR_exit("** Failed to find key %d in hash table\n",id);
} else mar[ii] = 0;
}
break ;
case MRI_float:{
float *mar = (float *) DSET_ARRAY(dsets_in[ib],isb) ;
for( ii=0 ; ii < DSET_NVOX(dsets_in[ib]) ; ii++ )
if (!cmask || cmask[ii]) {
id = (int)mar[ii]; /* Assuming float is integral valued */
HASH_FIND_INT(rmap,&id ,hd);
if (hd) mar[ii] = (float)(hd->index);
else
ERROR_exit("** Failed to find key %d in hash table\n",id);
} else mar[ii] = 0;
}
break ;
}
}
/* update range, etc. */
THD_load_statistics(dsets_in[ib]);
/* Now write the bricks */
if (prefix) {
if (nbriks == 1) {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"%s", prefix);
} else {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"r%02d.%s", ib, prefix);
}
} else {
snprintf(stmp, sizeof(char)*THD_MAX_PREFIX,
"rank.%s", DSET_PREFIX(dsets_in[ib]));
}
EDIT_dset_items( dsets_in[ib] ,
ADN_prefix , stmp ,
ADN_none ) ;
/* change storage mode, this way prefix will determine
format of output dset */
dsets_in[ib]->dblk->diskptr->storage_mode = STORAGE_BY_BRICK;
tross_Make_History( "3dRank" , argc, argv , dsets_in[ib] ) ;
if (DSET_IS_MASTERED(dsets_in[ib])) {
/* THD_write_3dim_dataset won't write a mastered dude */
dset = EDIT_full_copy(dsets_in[ib],stmp);
} else {
dset = dsets_in[ib];
}
/* New ID */
ZERO_IDCODE(dset->idcode);
dset->idcode = MCW_new_idcode() ;
if (!THD_write_3dim_dataset( NULL, stmp, dset,True )) {
ERROR_message("Failed to write %s", stmp);
exit(1);
} else {
WROTE_DSET(dsets_in[ib]);
if (dset != dsets_in[ib]) DSET_deletepp(dset);
DSET_deletepp(dsets_in[ib]);
}
}
/* destroy hash */
while (rmap) {
hd = rmap;
HASH_DEL(rmap,hd);
free(hd);
}
free(final_unq); final_unq=NULL;
exit(0);
}
