# grab all realigned files
allrealigned = crg_out.outputs.coregistered_files + \
rlgnout.outputs.realigned_files
# make new mean files(s) based on fully realigned files
# 1. first 20 mins for coreg (frames 1-23)
# 2. 40-60 mins for possible SUVR (frames 28-31)
mean_20min = pp.make_mean_20min(allrealigned)
mean_40_60min = pp.make_mean_40_60(allrealigned)
# clean up
# remove copied unrealigned frames
bg.remove_files(newnifti)
# QA
# make 4d for QA
qadir, exists = qa.make_qa_dir(realigndir, name='data_QA')
data4d = qa.make_4d_nibabel(allrealigned, outdir=qadir)
#snrimg = qa.gen_sig2noise_img(data4d,qadir)
#artout = qa.run_artdetect(data4d,tmpparameterfile)
#qa.screen_data_dirnme(data4d, qadir)
qa.plot_movement(tmpparameterfile, subid)
qa.calc_robust_median_diff(data4d)
qa.screen_pet(data4d)
# Coregister cerebellum, brainmask and aparc_aseg to pet space
#
logging.info('Coreg %s' % (subid))
coregdir, exists = bg.make_dir(pth, 'coreg')
if exists:
logging.warning('%s exists, remove to rerun' % (coregdir))
continue
timingf = glob(globstr)
if len(timingf) < 1:
globstr = os.path.join(sub, 'RawData', tracer, 'frametimes-*.csv')
timingf = glob(globstr)
if len(timingf) < 1:
logging.error('%s missing, skipping' % (globstr))
raise IOError('%s missing, skipping' % (globstr))
timingf = timingf[0]
ft = ft.read_frametimes(timingf)
ft_sec = ft.copy() / 60.
start = singlechoice(['%d' % x for x in ft_sec[:, 1]], text='Start Time')
end = singlechoice(['%d' % x for x in ft_sec[:, -1]], text='End Time')
k2ref = 0.15
range = (int(start), int(end))
logging.info('Running Logan')
dvrdir, exists = qa.make_qa_dir(pth, name='dvr')
if exists:
logging.warning('%s exists, remove to re-run' % (pth + '/dvr'))
raise IOError('%s exists, remove to re-run' % (pth + '/dvr'))
midtimes, durs = pyl.midframes_from_file(timingf)
data4d = pyl.get_data_nibabel(nifti)
ref = pyl.get_ref(rcere, data4d)
ref_fig = pyl.save_inputplot(ref, (midtimes + durs / 2.), dvrdir)
masked_data, mask_roi = pyl.mask_data(rbrainmask, data4d)
x, y = pyl.calc_xy(ref, masked_data, midtimes)
allki, residuals = pyl.calc_ki(x, y, timingf, range=range)
dvr = pyl.results_to_array(allki, mask_roi)
resid = pyl.results_to_array(residuals, mask_roi)
outf = pyl.save_data2nii(dvr,
rbrainmask,
filename='DVR-%s' % subid,
# get timing file
sub, _ = os.path.split(pth)
timingf = bg.FileDialog(prompt="Select Timing File", indir=pth)
if len(timingf) < 1:
logging.error("%s missing, skipping" % (globstr))
raise IOError("%s missing, skipping" % (globstr))
timingf = timingf
ft = ft.read_frametimes(timingf)
ft_sec = ft.copy() / 60.0
start = singlechoice(["%d" % x for x in ft_sec[:, 1]], text="Start Time")
end = singlechoice(["%d" % x for x in ft_sec[:, -1]], text="End Time")
k2ref = 0.15
range = (int(start), int(end))
logging.info("Running Logan")
dvrdir, exists = qa.make_qa_dir(pth, name="dvr")
if exists:
logging.warning("%s exists, remove to re-run" % (pth + "/dvr"))
raise IOError("%s exists, remove to re-run" % (pth + "/dvr"))
midtimes, durs = pyl.midframes_from_file(timingf)
data4d = pyl.get_data_nibabel(nifti)
ref = pyl.get_ref(rcere, data4d)
ref_fig = pyl.save_inputplot(ref, (midtimes + durs / 2.0), dvrdir)
masked_data, mask_roi = pyl.mask_data(rbrainmask, data4d)
x, y = pyl.calc_xy(ref, masked_data, midtimes)
allki, residuals = pyl.calc_ki(x, y, timingf, range=range)
dvr = pyl.results_to_array(allki, mask_roi)
resid = pyl.results_to_array(residuals, mask_roi)
outf = pyl.save_data2nii(dvr, rbrainmask, filename="DVR-%s" % subid, outdir=dvrdir)
_ = pyl.save_data2nii(resid, rbrainmask, filename="RESID-%s" % subid, outdir=dvrdir)
logging.info("%s Finished Logan: %s" % (subid, outf))
allrealigned = crg_out.outputs.coregistered_files + \
rlgnout.outputs.realigned_files
# make new mean files(s) based on fully realigned files
# 1. first 20 mins for coreg (frames 1-23)
# 2. 40-60 mins for possible SUVR (frames 28-31)
mean_20min = pp.make_mean_20min(allrealigned)
mean_40_60min = pp.make_mean_40_60(allrealigned)
# clean up
# remove copied unrealigned frames
bg.remove_files(newnifti)
# QA
# make 4d for QA
qadir, exists = qa.make_qa_dir(realigndir, name='data_QA')
data4d = qa.make_4d_nibabel(allrealigned, outdir=qadir)
#snrimg = qa.gen_sig2noise_img(data4d,qadir)
#artout = qa.run_artdetect(data4d,tmpparameterfile)
#qa.screen_data_dirnme(data4d, qadir)
qa.plot_movement(tmpparameterfile, subid)
qa.calc_robust_median_diff(data4d)
qa.screen_pet(data4d)
# Coregister cerebellum, brainmask and aparc_aseg to pet space
#
logging.info('Coreg %s'%(subid))
coregdir, exists = bg.make_dir(pth, 'coreg')
if exists:
logging.warning('%s exists, remove to rerun'%(coregdir))
continue
timingf = glob(globstr)
if len(timingf) < 1:
globstr = os.path.join(sub, 'RawData', tracer, 'frametimes-*.csv')
timingf = glob(globstr)
if len(timingf) < 1:
logging.error('%s missing, skipping'%(globstr))
raise IOError('%s missing, skipping'%(globstr))
timingf = timingf[0]
ft = ft.read_frametimes(timingf)
ft_sec = ft.copy() / 60.
start = singlechoice(['%d'%x for x in ft_sec[:,1]], text='Start Time')
end = singlechoice(['%d'%x for x in ft_sec[:,-1]], text='End Time')
k2ref = 0.15
range = (int(start),int(end))
logging.info('Running Logan')
dvrdir, exists = qa.make_qa_dir(pth, name='dvr')
if exists:
logging.warning('%s exists, remove to re-run'%(pth + '/dvr'))
raise IOError('%s exists, remove to re-run'%(pth + '/dvr'))
midtimes, durs = pyl.midframes_from_file(timingf)
data4d = pyl.get_data_nibabel(nifti)
ref = pyl.get_ref(rcere, data4d)
ref_fig = pyl.save_inputplot(ref, (midtimes + durs/2.), dvrdir)
masked_data, mask_roi = pyl.mask_data(rbrainmask, data4d)
x,y = pyl.calc_xy(ref, masked_data, midtimes)
allki, residuals = pyl.calc_ki(x, y, timingf, range=range)
dvr = pyl.results_to_array(allki, mask_roi)
resid = pyl.results_to_array(residuals, mask_roi)
outf = pyl.save_data2nii(dvr, rbrainmask,
filename='DVR-%s'%subid, outdir=dvrdir)
_ = pyl.save_data2nii(resid, rbrainmask,
