def get_fsaverage_label_operator(parc='aparc.a2009s', remove_bads=True,
combine_medial=False, return_labels=False,
subjects_dir=None, verbose=None):
"""Get a label operator matrix for fsaverage."""
subjects_dir = get_subjects_dir(subjects_dir, raise_error=True)
src = read_source_spaces(op.join(
subjects_dir, 'fsaverage', 'bem', 'fsaverage-5-src.fif'),
verbose=False)
fs_vertices = [np.arange(10242), np.arange(10242)]
assert all(np.array_equal(a['vertno'], b)
for a, b in zip(src, fs_vertices))
labels = read_labels_from_annot('fsaverage', parc)
# Remove bad labels
if remove_bads:
bads = get_fsaverage_medial_vertices(False)
bads = dict(lh=bads[0], rh=bads[1])
assert all(b.size > 1 for b in bads.values())
labels = [label for label in labels
if np.in1d(label.vertices, bads[label.hemi]).mean() < 0.8]
del bads
if combine_medial:
labels = combine_medial_labels(labels)
offsets = dict(lh=0, rh=10242)
rev_op = np.zeros((20484, len(labels)))
for li, label in enumerate(labels):
if isinstance(label, BiHemiLabel):
use_labels = [label.lh, label.rh]
else:
use_labels = [label]
for ll in use_labels:
rev_op[ll.get_vertices_used() + offsets[ll.hemi], li:li + 1] = 1.
# every src vertex is in exactly one label, except medial wall verts
# assert (rev_op.sum(-1) == 1).sum()
label_op = SourceEstimate(np.eye(20484), fs_vertices, 0, 1)
label_op = label_op.extract_label_time_course(labels, src)
out = (label_op, rev_op)
if return_labels:
out += (labels,)
return out
