def create_lut_file_for_atlas(subject, atlas):
# Read the subcortical segmentation from the freesurfer lut
lut = utils.read_freesurfer_lookup_table(FREE_SURFER_HOME, get_colors=True)
lut_new = [list(l) for l in lut if l[0] < 1000]
for hemi, offset in zip(['lh', 'rh'], [1000, 2000]):
if hemi == 'lh':
lut_new.append([1000, 'ctx-lh-unknown', 25, 5, 25, 0])
else:
lut_new.append([2000, 'ctx-rh-unknown', 25, 5, 25, 0])
_, ctab, names = _read_annot(op.join(SUBJECTS_DIR, subject, 'label', '{}.{}.annot'.format(hemi, atlas)))
names = [name.astype(str) for name in names]
for index, (label, cval) in enumerate(zip(names, ctab)):
r,g,b,a, _ = cval
lut_new.append([index + offset + 1, label, r, g, b, a])
lut_new.sort(key=lambda x:x[0])
# Add the values above 3000
for l in [l for l in lut if l[0] >= 3000]:
lut_new.append(l)
new_lut_fname = op.join(SUBJECTS_DIR, subject, 'label', '{}ColorLUT.txt'.format(atlas))
with open(new_lut_fname, 'w') as fp:
csv_writer = csv.writer(fp, delimiter='\t')
csv_writer.writerows(lut_new)
# np.savetxt(new_lut_fname, lut_new, delimiter='\t', fmt="%s")
utils.make_dir(op.join(MMVT_DIR, subject, 'freeview'))
shutil.copyfile(new_lut_fname, op.join(MMVT_DIR, subject, 'freeview', '{}ColorLUT.txt'.format(atlas)))
def test_read_labels_from_annot(tmp_path):
"""Test reading labels from FreeSurfer parcellation."""
# test some invalid inputs
pytest.raises(ValueError,
read_labels_from_annot,
'sample',
hemi='bla',
subjects_dir=subjects_dir)
pytest.raises(ValueError,
read_labels_from_annot,
'sample',
annot_fname='bla.annot',
subjects_dir=subjects_dir)
with pytest.raises(IOError, match='does not exist'):
_read_annot_cands('foo')
with pytest.raises(IOError, match='no candidate'):
_read_annot(str(tmp_path))
# read labels using hemi specification
labels_lh = read_labels_from_annot('sample',
hemi='lh',
subjects_dir=subjects_dir)
for label in labels_lh:
assert label.name.endswith('-lh')
assert label.hemi == 'lh'
assert label.color is not None
# read labels using annot_fname
annot_fname = op.join(subjects_dir, 'sample', 'label', 'rh.aparc.annot')
labels_rh = read_labels_from_annot('sample',
annot_fname=annot_fname,
subjects_dir=subjects_dir)
for label in labels_rh:
assert label.name.endswith('-rh')
assert label.hemi == 'rh'
assert label.color is not None
# combine the lh, rh, labels and sort them
labels_lhrh = list()
labels_lhrh.extend(labels_lh)
labels_lhrh.extend(labels_rh)
names = [label.name for label in labels_lhrh]
labels_lhrh = [label for (name, label) in sorted(zip(names, labels_lhrh))]
# read all labels at once
labels_both = read_labels_from_annot('sample', subjects_dir=subjects_dir)
# we have the same result
_assert_labels_equal(labels_lhrh, labels_both)
# aparc has 68 cortical labels
assert (len(labels_both) == 68)
# test regexp
label = read_labels_from_annot('sample',
parc='aparc.a2009s',
regexp='Angu',
subjects_dir=subjects_dir)[0]
assert (label.name == 'G_pariet_inf-Angular-lh')
# silly, but real regexp:
label = read_labels_from_annot('sample',
'aparc.a2009s',
regexp='.*-.{4,}_.{3,3}-L',
subjects_dir=subjects_dir)[0]
assert (label.name == 'G_oc-temp_med-Lingual-lh')
with pytest.raises(RuntimeError, match='did not match any of'):
read_labels_from_annot('sample',
parc='aparc',
annot_fname=annot_fname,
regexp='foo',
subjects_dir=subjects_dir)
def get_labels_num(subject, subjects_dir, atlas, hemi='both'):
from mne.label import _read_annot
annot_fnames = get_annot_fnames(subject, subjects_dir, atlas, hemi)
return np.concatenate(
[_read_annot(annot_fname)[2] for annot_fname in annot_fnames]).shape[0]