def mri_surf2surf(data, source_subj, target_subj, hemi, subjects_dir=None):
"""Uses freesurfer mri_surf2surf to transfer vertex data between
two freesurfer subjects
Parameters
==========
data: ndarray, shape=(n_imgs, n_verts)
data arrays representing vertex data
source_subj: str
freesurfer subject name of source subject
target_subj: str
freesurfer subject name of target subject
hemi: str in ("lh", "rh")
string indicating hemisphere.
Notes
=====
Requires path to mri_surf2surf or freesurfer environment to be active.
"""
data_arrays = [gifti.GiftiDataArray(d) for d in data]
gifti_image = gifti.GiftiImage(darrays=data_arrays)
tf_in = NamedTemporaryFile(suffix=".gii")
nibabel.save(gifti_image, tf_in.name)
tf_out = NamedTemporaryFile(suffix='.gii')
cmd = _mri_surf2surf_command(source_subj, target_subj, tf_in.name,
tf_out.name, hemi)
if subjects_dir is not None:
env = os.environ.copy()
env['SUBJECTS_DIR'] = subjects_dir
else:
env = None
print('Calling:')
print(' '.join(cmd))
p = sp.Popen(cmd, env=env)
exit_code = p.wait()
if exit_code != 0:
if exit_code == 255:
raise Exception(
("Missing file (see above). "
"If lh.sphere.reg is missing,\n"
"you likely need to run the 3rd "
"stage of freesurfer autorecon\n"
"(sphere registration) for this subject:\n"
">>> cortex.freesurfer.autorecon('{fs_subject}', type='3')"
).format(fs_subject=source_subj))
#from subprocess import CalledProcessError # handle with this, maybe?
raise Exception(("Exit code {exit_code} means that "
"mri_surf2surf failed").format(exit_code=exit_code))
tf_in.close()
output_img = nibabel.load(tf_out.name)
output_data = np.array([da.data for da in output_img.darrays])
tf_out.close()
return output_data
def write(self, gifti_filename, scalar_arr=None, **kwargs):
"""
Writes a surface to a surface gifti file.
:param gifti_filename: output filename
:param scalar_arr: optionally include a scalar array with same length as number of vertices (as expected by FSL's probtrackX)
:param kwargs: any keywords are added to the meta information in the GIFTI file
"""
from . import cortical_mesh
use_kwargs = {
'Date': str(datetime.datetime.now()),
'encoding': 'XML',
'GeometricType': 'Anatomical'
}
use_kwargs.update(cortical_mesh.BrainStructure('Other').gifti)
use_kwargs.update(kwargs)
meta = gifti.GiftiMetaData.from_dict(use_kwargs)
img = gifti.GiftiImage(meta=meta)
for arr, intent, dtype in zip([self.vertices, self.faces],
['pointset', 'triangle'], ['f4', 'i4']):
img.add_gifti_data_array(
gifti.GiftiDataArray(arr.T.astype(dtype),
intent,
meta=meta.metadata))
if scalar_arr is not None:
img.add_gifti_data_array(
gifti.GiftiDataArray(scalar_arr.astype('f4'),
intent='shape',
meta=meta.metadata))
for da in img.darrays:
da.encoding = 2 # Base64Binary
nib.save(img, gifti_filename)
def test_load_surf_mesh_file_gii(tmp_path):
# Test the loader `load_surf_mesh`
# If nibabel is of older version we skip tests as nibabel does not
# support intent argument and intent codes are not handled properly with
# older versions
if not LooseVersion(nb.__version__) >= LooseVersion('2.1.0'):
raise pytest.skip('Nibabel version too old to handle intent codes')
mesh = generate_surf()
# test if correct gii is loaded into correct list
fd_mesh, filename_gii_mesh = tempfile.mkstemp(suffix='.gii',
dir=str(tmp_path))
os.close(fd_mesh)
coord_array = gifti.GiftiDataArray(data=mesh[0],
intent=nb.nifti1.intent_codes[
'NIFTI_INTENT_POINTSET'])
face_array = gifti.GiftiDataArray(data=mesh[1],
intent=nb.nifti1.intent_codes[
'NIFTI_INTENT_TRIANGLE'])
gii = gifti.GiftiImage(darrays=[coord_array, face_array])
gifti.write(gii, filename_gii_mesh)
assert_array_equal(load_surf_mesh(filename_gii_mesh)[0], mesh[0])
assert_array_equal(load_surf_mesh(filename_gii_mesh)[1], mesh[1])
os.remove(filename_gii_mesh)
# test if incorrect gii raises error
fd_no, filename_gii_mesh_no_point = tempfile.mkstemp(suffix='.gii',
dir=str(tmp_path))
os.close(fd_no)
gifti.write(gifti.GiftiImage(darrays=[face_array, face_array]),
filename_gii_mesh_no_point)
with pytest.raises(ValueError, match='NIFTI_INTENT_POINTSET'):
load_surf_mesh(filename_gii_mesh_no_point)
os.remove(filename_gii_mesh_no_point)
fd_face, filename_gii_mesh_no_face = tempfile.mkstemp(suffix='.gii',
dir=str(tmp_path))
os.close(fd_face)
gifti.write(gifti.GiftiImage(darrays=[coord_array, coord_array]),
filename_gii_mesh_no_face)
with pytest.raises(ValueError, match='NIFTI_INTENT_TRIANGLE'):
load_surf_mesh(filename_gii_mesh_no_face)
os.remove(filename_gii_mesh_no_face)
def save_texture(filename, data):
from nibabel import gifti
import codecs
darray = gifti.GiftiDataArray(data)
gii = gifti.GiftiImage(darrays=[darray])
f = codecs.open(filename, 'wb')
f.write(gii.to_xml(enc='utf-8'))
f.close()
def writegifti(filename, polydata, refniifn):
refnii = radiological.load(refniifn)
points, polys = polydata_to_points_polys(polydata, True)
scaledpoints4 = np.hstack([
points / refnii.header.get_zooms()[0:3],
np.ones(points.shape[0])[:, None]
])
transformedpoints = refnii.affine.dot(
scaledpoints4.transpose())[0:3, :].transpose()
# Not setting xfm as nifti mat has already been applied - is this the right way to do it?
giftipoints = gii.GiftiDataArray(data=transformedpoints,
intent='NIFTI_INTENT_POINTSET',
datatype='NIFTI_TYPE_FLOAT32',
encoding='GIFTI_ENCODING_ASCII')
giftipolys = gii.GiftiDataArray(data=polys,
intent='NIFTI_INTENT_TRIANGLE',
datatype='NIFTI_TYPE_INT32',
encoding='GIFTI_ENCODING_ASCII')
giftimesh = gii.GiftiImage(darrays=[giftipoints, giftipolys])
giftimesh.to_filename(filename)