def main():
args = parse_command_line()
print args
smoothing = args.smoothing
use_inplane = args.use_inplane
basedir = os.path.abspath(args.basedir)
nonlinear = args.nonlinear
modelnum = args.modelnum
if not args.confound:
print 'omitting confound modeling'
dataset = args.taskid
if not args.test:
outfile = open('mk_all_level1_%s.sh' % dataset, 'w')
tasknum_spec = 'task*'
if not args.tasknum == None:
tasknum_spec = 'task%03d*' % args.tasknum
dsdir = os.path.join(basedir, dataset)
bolddirs = glob.glob(os.path.join(dsdir, 'sub*/BOLD/%s' % tasknum_spec))
print bolddirs
for root in bolddirs:
#print 'ROOT:',root
for m in glob.glob(os.path.join(root, 'bold_mcf_brain.nii.gz')):
#print 'BOLDFILE:',m
f_split = root.split('/')
#print f_split
scankey = '/' + '/'.join(f_split[1:7]) + '/scan_key.txt'
taskid = f_split[6]
subnum = int(f_split[7].lstrip('sub'))
taskinfo = f_split[9].split('_')
tasknum = int(taskinfo[0].lstrip('task'))
runnum = int(taskinfo[1].lstrip('run'))
#tr=float(load_scankey(scankey)['TR'])
# check for inplane
inplane = '/' + '/'.join(
f_split[1:8]) + '/anatomy/inplane001_brain.nii.gz'
## if args.nobbr:
## print 'using nobbr option'
## print 'mk_level1_fsf("%s",%d,%d,%d,%d,%d,"%s",%d)'%(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,modelnum)
## else:
## print 'mk_level1_fsf_bbr("%s",%d,%d,%d,%d,%d,"%s",%d)'%(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,modelnum)
if not args.test:
if args.nobbr:
fname = mk_level1_fsf(taskid, subnum, tasknum, runnum,
smoothing, use_inplane, basedir,
nonlinear, modelnum)
else:
fname = mk_level1_fsf_bbr(taskid, subnum, tasknum, runnum,
smoothing, use_inplane, basedir,
nonlinear, modelnum,
args.anatimg, args.confound,
args.hpf, args.whiten)
#print 'CMD: mk_level1_fsf_bbr(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,nonlinear,modelnum,args.anatimg,args.confound)'
outfile.write('feat %s\n' % fname)
if not args.test:
outfile.close()
if not args.test:
print 'now launching all feats:'
print "find %s/sub*/model/*.fsf |sed 's/^/feat /' > run_all_feats.sh; sh run_all_feats.sh" % args.taskid
f = open('mk_all_level1_%s.sh' % dataset)
l = f.readlines()
f.close()
njobs = len(l)
if args.parenv == '':
args.parenv = '6way'
way = float(args.parenv.replace('way', ''))
if args.ncores == 0:
ncores = (njobs / way) * 12.0
else:
ncores = args.ncores
if args.launch:
launch_qsub.launch_qsub(script_name='mk_all_level1_%s.sh' %
dataset,
runtime='04:00:00',
jobname='%sl1' % dataset,
email=False,
parenv=args.parenv,
ncores=ncores)
def main():
config = commandline()
basedir = config.basedir
dataset = config.dataset
model_num = config.model_num
nonlinear = config.nonlinear
use_inplane = config.use_inplane
smoothing = config.smoothing
full_path = os.path.dirname(os.path.realpath(__file__))
#outfile=open('mk_all_level1_%s.sh'%dataset,'w')
if config.qsub:
qsub_name = 'feat_level1_%s_qsub.sh' % dataset
qsub_file = open(qsub_name, 'w')
fsl_container = '/home/acp16sz/fsl.img'
else:
script_name = 'feat_level1_%s.sh' % dataset
script_file = open(script_name, 'w')
for subject in os.listdir(basedir + dataset):
if subject[0:3] == 'sub':
for bold in os.listdir('%s/%s/BOLD/' %
(basedir + dataset, subject)):
for image in os.listdir('%s/%s/BOLD/%s/' %
(basedir + dataset, subject, bold)):
# TBD: add checking to handle case with no viable data
if image == 'bold_mcf_brain.nii.gz':
path = '%s/%s/BOLD/%s/' % (basedir + dataset, subject,
bold)
path_split = path.split('/')
scankey = basedir + dataset + '/scan_key.txt'
ds_id = dataset
for i in path_split:
if i[0:3] == 'sub':
sub_num = int(i.lstrip('sub'))
if i[0:4] == 'task':
task_run = i.split('_')
task_num = int(task_run[0].lstrip('task'))
if config.task_num != 0 and task_num != config.task_num:
continue
run_num = int(task_run[1].lstrip('run'))
tr = float(load_scankey(scankey)['TR'])
inplane = basedir + dataset + '/anatomy/inplane001_brain.nii.gz'
if os.path.exists(inplane):
use_inplane = 1
else:
use_inplane = 0
feat_name = mk_level1_fsf(ds_id, sub_num, task_num,
run_num, smoothing,
use_inplane, basedir,
nonlinear, model_num)
if config.qsub:
sub_job_name = 'feat_level1_%s_sub00%s_task00%s_run00%s.sh' % (
ds_id, sub_num, task_num, run_num)
sub_job_file = open(sub_job_name, 'w')
sub_job_file.write('#!/bin/bash\n')
sub_job_file.write('#$ -l rmem=8G\n')
sub_job_file.write(
'singularity exec %s feat %s\n' %
(fsl_container, feat_name))
sub_job_file.close()
qsub_file.write('qsub %s\n' % sub_job_name)
else:
script_file.write('feat %s\n' % feat_name)
if config.qsub:
qsub_file.close()
print 'run "bash %s/%s" to submit job to HPC' % (full_path, qsub_name)
else:
script_file.close()
print 'now run: "bash %s/%s"' % (full_path, script_name)
def main():
args=parse_command_line()
print args
smoothing=args.smoothing
use_inplane=args.use_inplane
basedir=os.path.abspath(args.basedir)
nonlinear=args.nonlinear
modelnum=args.modelnum
if not args.confound:
print 'omitting confound modeling'
dataset=args.taskid
if not args.test:
outfile=open('mk_all_level1_%s.sh'%dataset,'w')
tasknum_spec='task*'
if not args.tasknum==None:
tasknum_spec='task%03d*'%args.tasknum
dsdir=os.path.join(basedir,dataset)
bolddirs=glob.glob(os.path.join(dsdir,'sub*/BOLD/%s'%tasknum_spec))
print bolddirs
for root in bolddirs:
#print 'ROOT:',root
for m in glob.glob(os.path.join(root,'bold_mcf_brain.nii.gz')):
#print 'BOLDFILE:',m
f_split=root.split('/')
#print f_split
scankey='/'+'/'.join(f_split[1:7])+'/scan_key.txt'
taskid=f_split[6]
subnum=int(f_split[7].lstrip('sub'))
taskinfo=f_split[9].split('_')
tasknum=int(taskinfo[0].lstrip('task'))
runnum=int(taskinfo[1].lstrip('run'))
tr=float(load_scankey(scankey)['TR'])
# check for inplane
inplane='/'+'/'.join(f_split[1:8])+'/anatomy/inplane001_brain.nii.gz'
## if args.nobbr:
## print 'using nobbr option'
## print 'mk_level1_fsf("%s",%d,%d,%d,%d,%d,"%s",%d)'%(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,modelnum)
## else:
## print 'mk_level1_fsf_bbr("%s",%d,%d,%d,%d,%d,"%s",%d)'%(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,modelnum)
if not args.test:
if args.nobbr:
fname=mk_level1_fsf(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,nonlinear,modelnum)
else:
fname=mk_level1_fsf_bbr(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,nonlinear,modelnum,args.anatimg,args.confound,args.hpf,args.whiten)
#print 'CMD: mk_level1_fsf_bbr(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,nonlinear,modelnum,args.anatimg,args.confound)'
outfile.write('feat %s\n'%fname)
if not args.test:
outfile.close()
if not args.test:
print 'now launching all feats:'
print "find %s/sub*/model/*.fsf |sed 's/^/feat /' > run_all_feats.sh; sh run_all_feats.sh"%args.taskid
f=open('mk_all_level1_%s.sh'%dataset)
l=f.readlines()
f.close()
njobs=len(l)
if args.parenv=='':
args.parenv='6way'
way=float(args.parenv.replace('way',''))
if args.ncores==0:
ncores=(njobs/way)*12.0
else:
ncores=args.ncores
if args.launch:
launch_qsub.launch_qsub(script_name='mk_all_level1_%s.sh'%dataset,runtime='04:00:00',jobname='%sl1'%dataset,email=False,parenv=args.parenv,ncores=ncores)
def main():
if len(sys.argv)>2:
dataset=sys.argv[1]
modelnum=int(sys.argv[2])
else:
usage()
if len(sys.argv)>3:
basedir=sys.argv[3]
if not os.path.exists(basedir):
print 'basedir %s does not exist!'%basedir
sys.exit(1)
else:
basedir=os.path.abspath(os.curdir)
if not basedir[-1]=='/':
basedir=basedir+'/'
nonlinear=1
if len(sys.argv)>4:
nonlinear=int(sys.argv[4])
if nonlinear==0:
print 'using linear registration'
outfile=open('mk_all_level1_%s.sh'%dataset,'w')
smoothing=0
if len(sys.argv)>5:
smoothing=int(sys.argv[5])
tasknum_spec=0
if len(sys.argv)>6:
tasknum_spec=int(sys.argv[6])
use_inplane=1
for d in os.listdir(basedir+dataset):
if d[0:3]=='sub':
for bd in os.listdir('%s/%s/BOLD/'%(basedir+dataset,d)):
for m in os.listdir('%s/%s/BOLD/%s/'%(basedir+dataset,d,bd)):
# TBD: add checking to handle case with no viable data
if m=='bold_mcf_brain.nii.gz':
root='%s/%s/BOLD/%s/'%(basedir+dataset,d,bd)
f_split=root.split('/')
scankey='/'+'/'.join(f_split[1:7])+'/scan_key.txt'
taskid=f_split[6]
subnum=int(f_split[7].lstrip('sub'))
taskinfo=f_split[9].split('_')
tasknum=int(taskinfo[0].lstrip('task'))
if (tasknum_spec>0) and not (tasknum==tasknum_spec):
continue
runnum=int(taskinfo[1].lstrip('run'))
tr=float(load_scankey(scankey)['TR'])
# check for inplane
inplane='/'+'/'.join(f_split[1:8])+'/anatomy/inplane001_brain.nii.gz'
if os.path.exists(inplane):
use_inplane=1
else:
use_inplane=0
print 'mk_level1_fsf("%s",%d,%d,%d,%d,%d,"%s",%d)'%(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,modelnum)
fname=mk_level1_fsf(taskid,subnum,tasknum,runnum,smoothing,use_inplane,basedir,nonlinear,modelnum)
outfile.write('feat %s\n'%fname)
outfile.close()
print 'now launching all feats:'
print "find %s/sub*/model/*.fsf |sed 's/^/feat /' > run_all_feats.sh; sh run_all_feats.sh"%taskid
f=open('mk_all_level1_%s.sh'%dataset)
l=f.readlines()
f.close()
njobs=len(l)
ncores=(njobs/2)*12
launch_qsub.launch_qsub(script_name='mk_all_level1_%s.sh'%dataset,runtime='04:00:00',jobname='%sl1'%dataset,email=False,parenv='2way',ncores=ncores)
def main():
if len(sys.argv) > 2:
dataset = sys.argv[1]
modelnum = int(sys.argv[2])
else:
usage()
if len(sys.argv) > 3:
basedir = sys.argv[3]
if not os.path.exists(basedir):
print 'basedir %s does not exist!' % basedir
sys.exit(1)
else:
basedir = os.path.abspath(os.curdir)
if not basedir[-1] == '/':
basedir = basedir + '/'
nonlinear = 1
if len(sys.argv) > 4:
nonlinear = int(sys.argv[4])
if nonlinear == 0:
print 'using linear registration'
outfile = open('mk_all_level1_%s.sh' % dataset, 'w')
smoothing = 0
if len(sys.argv) > 5:
smoothing = int(sys.argv[5])
tasknum_spec = 0
if len(sys.argv) > 6:
tasknum_spec = int(sys.argv[6])
use_inplane = 1
for d in os.listdir(basedir + dataset):
if d[0:3] == 'sub':
for bd in os.listdir('%s/%s/BOLD/' % (basedir + dataset, d)):
for m in os.listdir('%s/%s/BOLD/%s/' %
(basedir + dataset, d, bd)):
# TBD: add checking to handle case with no viable data
if m == 'bold_mcf_brain.nii.gz':
root = '%s/%s/BOLD/%s/' % (basedir + dataset, d, bd)
f_split = root.split('/')
scankey = '/' + '/'.join(
f_split[1:7]) + '/scan_key.txt'
taskid = f_split[6]
subnum = int(f_split[7].lstrip('sub'))
taskinfo = f_split[9].split('_')
tasknum = int(taskinfo[0].lstrip('task'))
if (tasknum_spec > 0) and not (tasknum
== tasknum_spec):
continue
runnum = int(taskinfo[1].lstrip('run'))
tr = float(load_scankey(scankey)['TR'])
# check for inplane
inplane = '/' + '/'.join(
f_split[1:8]) + '/anatomy/inplane001_brain.nii.gz'
if os.path.exists(inplane):
use_inplane = 1
else:
use_inplane = 0
print 'mk_level1_fsf("%s",%d,%d,%d,%d,%d,"%s",%d)' % (
taskid, subnum, tasknum, runnum, smoothing,
use_inplane, basedir, modelnum)
fname = mk_level1_fsf(taskid, subnum, tasknum, runnum,
smoothing, use_inplane, basedir,
nonlinear, modelnum)
outfile.write('feat %s\n' % fname)
outfile.close()
print 'now launching all feats:'
print "find %s/sub*/model/*.fsf |sed 's/^/feat /' > run_all_feats.sh; sh run_all_feats.sh" % taskid
f = open('mk_all_level1_%s.sh' % dataset)
l = f.readlines()
f.close()
njobs = len(l)
ncores = (njobs / 2) * 12
launch_qsub.launch_qsub(script_name='mk_all_level1_%s.sh' % dataset,
runtime='04:00:00',
jobname='%sl1' % dataset,
email=False,
parenv='2way',
ncores=ncores)
