def _applytfms(args):
"""
Applies ANTs' antsApplyTransforms to the input image.
All inputs are zipped in one tuple to make it digestible by
multiprocessing's map
"""
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
in_file, in_xform, ifargs, index, newpath = args
out_file = fname_presuffix(in_file,
suffix='_xform-%05d' % index,
newpath=newpath,
use_ext=True)
copy_dtype = ifargs.pop('copy_dtype', False)
xfm = ApplyTransforms(input_image=in_file,
transforms=in_xform,
output_image=out_file,
**ifargs)
xfm.terminal_output = 'allatonce'
xfm.resource_monitor = False
runtime = xfm.run().runtime
if copy_dtype:
nii = nb.load(out_file, mmap=False)
in_dtype = nb.load(in_file).get_data_dtype()
# Overwrite only iff dtypes don't match
if in_dtype != nii.get_data_dtype():
nii.set_data_dtype(in_dtype)
nii.to_filename(out_file)
return (out_file, runtime.cmdline)
def _applytfms(args):
"""
Applies ANTs' antsApplyTransforms to the input image.
All inputs are zipped in one tuple to make it digestible by
multiprocessing's map
"""
import nibabel as nb
from nipype.utils.filemanip import fname_presuffix
from niworkflows.interfaces.fixes import FixHeaderApplyTransforms as ApplyTransforms
in_file, in_xform, ifargs, index, newpath = args
out_file = fname_presuffix(in_file, suffix='_xform-%05d' % index,
newpath=newpath, use_ext=True)
copy_dtype = ifargs.pop('copy_dtype', False)
xfm = ApplyTransforms(
input_image=in_file, transforms=in_xform, output_image=out_file, **ifargs)
xfm.terminal_output = 'allatonce'
xfm.resource_monitor = False
runtime = xfm.run().runtime
if copy_dtype:
nii = nb.load(out_file)
in_dtype = nb.load(in_file).get_data_dtype()
# Overwrite only iff dtypes don't match
if in_dtype != nii.get_data_dtype():
nii.set_data_dtype(in_dtype)
nii.to_filename(out_file)
return (out_file, runtime.cmdline)