'--metric',
'MeanSquares[{},{},{}]'.format(args.use_labels[2], lab_path,
w_lab)
])
cmdline.extend(
['--convergence', '[{},1e-9,15]'.format('x'.join(its_syn))])
cmdline.extend(['--smoothing-sigmas', smooth_sig])
cmdline.extend(['--shrink-factors', shrink_fac])
#
# mask
if args.template_mask is not None:
cmdline.extend(['--masks', args.template_mask[0]])
#
# launch
print "Launching registration of file {}".format(img_file)
name_list.append(img_file.split(os.extsep, 1)[0])
launcher.add(name_list[-1], ' '.join(cmdline), args.out_dir[0])
launcher.run(name_list[-1])
print "Waiting for registration jobs to finish..."
launcher.wait()
print "Registration finished."
cmdline += [
imagemath_path, '3',
os.path.join(tmp_dir, 'dummy.txt'), 'NormalizedCorrelation'
]
cmdline += [
os.path.join(in1_dir, file1),
os.path.join(in2_dir, file2)
]
if args.mask_file is not None:
cmdline += [
os.path.join(tmp_dir,
os.path.basename(args.mask_file[0]))
]
name_list.append('%sX%s' % (name1, name2))
launcher.add(name_list[-1], ' '.join(cmdline), tmp_dir)
launcher.run(name_list[-1])
# Read scores when jobs are finished
if method_cmdline:
launcher.wait()
for i2, name in enumerate(name_list):
out_file = os.path.join(tmp_dir, name + '.out')
check_file_repeat(out_file)
try:
with open(out_file) as f:
for i_img in range(Nimg):
est_path = os.path.join(args.est_dir[0], est_files[i_img])
gtr_path = os.path.join(args.gtr_dir[0], gtr_files[i_img])
out_path = os.path.join(tmp_dir, est_names[i_img])
out_paths.append(out_path)
cmdline = "%s 3 %s DiceAndMinDistSum %s %s" % (imagemath_path, out_path,
est_path, gtr_path)
qsub_launcher = Launcher(cmdline)
print("Launching Dice evaluation job for labels %s" % est_names[i_img])
launcher.add(est_names[i_img], cmdline, tmp_dir)
launcher.run(est_names[i_img])
print "Waiting for Dice evaluation jobs to finish..."
launcher.wait()
print "Dice evaluation finished."
subj_dices = dict([])
label_dices = dict([])
for i, out_path in enumerate(out_paths):
# Read per-label Dice
check_file_repeat(out_path + '.csv')
args.target_deform_intfix[0] + '1Warp.nii.gz')
]
cmdline += [
'--transform',
os.path.join(
args.target_reg_dir[0], target_name +
args.target_linear_intfix[0] + '0GenericAffine.mat')
]
cmdline += [
'--output',
os.path.join(
args.out_dir[0],
atlas_file.split(os.extsep, 1)[0] + args.out_suffix[0])
]
#
# launch
job_name = atlas_file.split(os.extsep, 1)[0]
print "Launching warping of file {}".format(job_name)
launcher.add(job_name, ' '.join(cmdline), args.out_dir[0])
launcher.run(job_name)
# Wait for the jobs to finish (in cluster)
print "Waiting for warping jobs to finish..."
launcher.wait()
print "Warping finished."