def init(subject, atlas, n_jobs):
from src.utils import geometry_utils as gu
if not utils.both_hemi_files_exist(
op.join(SUBJECTS_DIR, subject, 'label', '{}.{}.annot'.format(
'{hemi}', atlas))):
anat.create_annotation(subject, atlas)
if not utils.both_hemi_files_exist(
op.join(SUBJECTS_DIR, subject, 'label', '{}.{}.annot'.format(
'{hemi}', atlas))):
raise Exception(
'Can\'t find the cortical atlas {} for subject {}'.format(
atlas, subject))
labels_vertices = find_rois.read_labels_vertices(SUBJECTS_DIR, subject,
atlas, n_jobs)
labels = lu.read_labels(subject, SUBJECTS_DIR, atlas)
labels_names = [l.name for l in labels]
aseg_atlas_fname = op.join(SUBJECTS_DIR, subject, 'mri', 'aseg.mgz')
aseg_data = nib.load(aseg_atlas_fname).get_data()
lut = fu.import_freesurfer_lut()
pia_verts = {}
for hemi in ['rh', 'lh']:
pia_verts[hemi], _ = gu.read_surface(
op.join(SUBJECTS_DIR, subject, 'surf', '{}.pial'.format(hemi)))
# pia_verts[hemi], _ = nib.freesurfer.read_geometry(
# op.join(SUBJECTS_DIR, subject, 'surf', '{}.pial'.format(hemi)))
subs_center_of_mass, subs_names = calc_subcorticals_pos(
subject, aseg_data, lut)
labels_center_of_mass = lu.calc_center_of_mass(labels, ret_mat=True) * 1000
regions_center_of_mass = np.concatenate(
(labels_center_of_mass, subs_center_of_mass))
regions_names = labels_names + subs_names
# save_com_as_elecs(subject, regions_center_of_mass, regions_names, atlas)
# save_com_as_elecs(subject, subs_center_of_mass, subs_names, atlas)
return labels_vertices, regions_center_of_mass, regions_names, aseg_data, lut, pia_verts,
def read_surface(subject, subjects_dir, surf_type='pial'):
from src.utils import geometry_utils as gu
verts, faces = {}, {}
for hemi in utils.HEMIS:
surf_fname = op.join(subjects_dir, subject, 'surf', '{}.{}'.format(hemi, surf_type))
if not op.isfile(surf_fname):
print('{} does not exist!'.format(surf_fname))
return None, None
# verts[hemi], faces[hemi] = nib.freesurfer.read_geometry(surf_fname)
verts[hemi], faces[hemi] = gu.read_surface(surf_fname)
return verts, faces
def aseg_to_srf(subject,
subjects_dir,
output_fol,
region_id,
lookup,
mask_fname,
norm_fname,
overwrite_subcortical_objs=False,
**kargs):
from src.utils import geometry_utils as gu
ret = True
tmp_fol = op.join(subjects_dir, subject, 'tmp', utils.rand_letters(6))
utils.make_dir(tmp_fol)
rs = utils.partial_run_script(locals())
# output_fname = op.join(output_fol, '{}.srf'.format(region_id))
# tmp_output_fname = op.join(tmp_fol, '{}.asc'.format(region_id))
# if overwrite_subcortical_objs:
# utils.remove_file(output_fname)
try:
rs(mri_pretess)
rs(mri_tessellate)
rs(mris_smooth)
fs_file = op.join(tmp_fol, '{}_smooth'.format(region_id))
verts, faces = gu.read_surface(fs_file)
# verts, faces = nib_fs.read_geometry(fs_file)
num = int(op.basename(fs_file).split('_')[0])
if num not in lookup:
print('Error in the subcorticals lookup table!')
return False
new_name = lookup.get(num, '')
utils.write_ply_file(verts, faces,
op.join(output_fol, '{}.ply'.format(new_name)),
True)
# mris_convert = 'mris_convert {tmp_fol}/{region_id}_smooth {tmp_fol}/{region_id}.asc'
# rs(mris_convert)
# if op.isfile(tmp_output_fname):
# shutil.move(tmp_output_fname, output_fname)
if op.isdir(tmp_fol):
shutil.rmtree(tmp_fol)
else:
ret = False
except:
print('Error in aseg_to_srf! subject: {}'.format(subject))
print(traceback.format_exc())
ret = False
return ret
def read_surface(subject, subjects_dir, surf_type='pial'):
from src.utils import geometry_utils as gu
verts, faces = {}, {}
surf_found = True
for hemi in utils.HEMIS:
surf_fname = op.join(subjects_dir, subject, 'surf', '{}.{}'.format(hemi, surf_type))
if op.isfile(surf_fname):
verts[hemi], faces[hemi] = gu.read_surface(surf_fname)
elif not op.isfile(surf_fname):
surf_fname = op.join(
MMVT_DIR, subject, 'subcortical', '{}-{}.npz'.format('Left' if hemi=='lh' else 'Right', surf_type))
if op.isfile(surf_fname):
d = np.load(surf_fname)
verts[hemi], faces[hemi] = d['verts'], d['faces']
if not op.isfile(surf_fname):
print('{} does not exist!'.format(surf_fname))
return None, None
return verts, faces
def parcelate(subject, atlas, hemi, surface_type, vertices_labels_ids_lookup=None,
overwrite_vertices_labels_lookup=False):
output_fol = op.join(MMVT_DIR, subject, 'labels', '{}.{}.{}'.format(atlas, surface_type, hemi))
utils.make_dir(output_fol)
# vtx, fac = utils.read_ply_file(op.join(MMVT_DIR, subject, 'surf', '{}.{}.ply'.format(hemi, surface_type)))
vtx, fac = gu.read_surface(op.join(SUBJECTS_DIR, subject, 'surf', '{}.{}'.format(hemi, surface_type)))
if vertices_labels_ids_lookup is None or overwrite_vertices_labels_lookup:
vertices_labels_ids_lookup = lu.create_vertices_labels_lookup(
subject, atlas, True, overwrite_vertices_labels_lookup)[hemi]
labels = lu.read_labels(subject, SUBJECTS_DIR, atlas, hemi=hemi)
if 'unknown-{}'.format(hemi) not in [l.name for l in labels]:
labels.append(lu.Label([], name='unknown-{}'.format(hemi), hemi=hemi))
nV = vtx.shape[0]
nF = fac.shape[0]
nL = len(labels)
# print('The number of unique labels is {}'.format(nL))
vtxL = [[] for _ in range(nL)]
facL = [[] for _ in range(nL)]
now = time.time()
for f in range(nF):
utils.time_to_go(now, f, nF, runs_num_to_print=50000)
# Current face & labels
Cfac = fac[f]
Cidx = [vertices_labels_ids_lookup[vert_ind] for vert_ind in Cfac]
# Depending on how many vertices of the current face
# are in different labels, behave differently
# nuCidx = len(np.unique(Cidx))
# if nuCidx == 1: # If all vertices share same label
# same_label = utils.all_items_equall(Cidx)
# if same_label:
if Cidx[0] == Cidx[1] == Cidx[2]:
# Add the current face to the list of faces of the
# respective label, and don't create new faces
facL[Cidx[0]] += [Cfac.tolist()]
else: # If 2 or 3 vertices are in different labels
# Create 3 new vertices at the midpoints of the 3 edges
vtxCfac = vtx[Cfac]
vtxnew = (vtxCfac + vtxCfac[[1, 2, 0]]) / 2
vtx = np.concatenate((vtx, vtxnew))
# Define 4 new faces, with care preserve normals (all CCW)
facnew = [
[Cfac[0], nV, nV + 2],
[nV, Cfac[1], nV + 1],
[nV + 2, nV + 1, Cfac[2]],
[nV, nV + 1, nV + 2]]
# Update nV for the next loop
nV = vtx.shape[0]
# Add the new faces to their respective labels
facL[Cidx[0]] += [facnew[0]]
facL[Cidx[1]] += [facnew[1]]
facL[Cidx[2]] += [facnew[2]]
freq_Cidx = mode(Cidx)
facL[freq_Cidx] += [facnew[3]] # central face
# Having defined new faces and assigned all faces to labels, now
# select the vertices and redefine faces to use the new vertex indices
# Also, create the file for the indices
# fidx = fopen(sprintf('%s.index.csv', srfprefix), 'w');
# params = []
# for lab in range(nL):
# facL_lab = facL[lab]
# facL_lab_flat = utils.list_flatten(facL_lab)
# vidx = list(set(facL_lab_flat))
# vtxL_lab = vtx[vidx]
# params.append((facL_lab, vtxL_lab, vidx, nV, labels[lab].name, hemi, output_fol))
# utils.run_parallel(writing_ply_files_parallel, params, njobs=n_jobs)
#
ret = True
for lab in range(nL):
ret = ret and writing_ply_files(subject, surface_type, lab, facL[lab], vtx, vtxL, labels, hemi, output_fol)
return ret