def test_grow_labels():
"""Test generation of circular source labels."""
seeds = [0, 50000]
# these were chosen manually in mne_analyze
should_be_in = [[49, 227], [51207, 48794]]
hemis = [0, 1]
names = ['aneurism', 'tumor']
labels = grow_labels('sample', seeds, 3, hemis, subjects_dir, names=names)
tgt_names = ['aneurism-lh', 'tumor-rh']
tgt_hemis = ['lh', 'rh']
for label, seed, hemi, sh, name in zip(labels, seeds, tgt_hemis,
should_be_in, tgt_names):
assert (np.any(label.vertices == seed))
assert (np.all(np.in1d(sh, label.vertices)))
assert_equal(label.hemi, hemi)
assert_equal(label.name, name)
# grow labels with and without overlap
seeds = [57532, [58887, 6304]]
l01, l02 = grow_labels('fsaverage', seeds, 20, [0, 0], subjects_dir)
seeds = [57532, [58887, 6304]]
l11, l12 = grow_labels('fsaverage', seeds, 20, [0, 0], subjects_dir,
overlap=False)
# test label naming
assert_equal(l01.name, 'Label_0-lh')
assert_equal(l02.name, 'Label_1-lh')
assert_equal(l11.name, 'Label_0-lh')
assert_equal(l12.name, 'Label_1-lh')
# test color assignment
l11_c, l12_c = grow_labels('fsaverage', seeds, 20, [0, 0], subjects_dir,
overlap=False, colors=None)
assert_equal(l11_c.color, _n_colors(2)[0])
assert_equal(l12_c.color, _n_colors(2)[1])
lab_colors = np.array([[0, 0, 1, 1], [1, 0, 0, 1]])
l11_c, l12_c = grow_labels('fsaverage', seeds, 20, [0, 0], subjects_dir,
overlap=False, colors=lab_colors)
assert_array_equal(l11_c.color, lab_colors[0, :])
assert_array_equal(l12_c.color, lab_colors[1, :])
lab_colors = np.array([.1, .2, .3, .9])
l11_c, l12_c = grow_labels('fsaverage', seeds, 20, [0, 0], subjects_dir,
overlap=False, colors=lab_colors)
assert_array_equal(l11_c.color, lab_colors)
assert_array_equal(l12_c.color, lab_colors)
# make sure set 1 does not overlap
overlap = np.intersect1d(l11.vertices, l12.vertices, True)
assert_array_equal(overlap, [])
# make sure both sets cover the same vertices
l0 = l01 + l02
l1 = l11 + l12
assert_array_equal(l1.vertices, l0.vertices)
def labels_from_clusters(clusters, names=None):
"""Create Labels from source space clusters
Parameters
----------
clusters : NDVar
NDVar which is non-zero on the cluster. Can have a case dimension, but
does not have to.
names : None | list of str | str
Label names corresponding to clusters (default is "cluster%i").
Returns
-------
labels : list of mne.Label
One label for each cluster.
"""
from mne.label import _n_colors
if isinstance(names, basestring):
names = [names]
source = clusters.source
source_space = clusters.source.get_source_space()
subject = source.subject
collapse = tuple(dim for dim in clusters.dimnames if dim not in ('case', 'source'))
clusters_index = clusters.any(collapse)
if clusters_index.has_case:
n_clusters = len(clusters)
else:
n_clusters = 1
clusters_index = (clusters_index,)
if names is None:
names = ("cluster%i" % i for i in xrange(n_clusters))
elif len(names) != n_clusters:
err = "Number of names difference from number of clusters."
raise ValueError(err)
colors = _n_colors(n_clusters)
labels = []
for cluster, color, name in izip(clusters_index, colors, names):
lh_vertices = source.lh_vertno[cluster.x[:source.lh_n]]
rh_vertices = source.rh_vertno[cluster.x[source.lh_n:]]
if len(lh_vertices) and len(rh_vertices):
lh = Label(lh_vertices, hemi='lh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
rh = Label(rh_vertices, hemi='rh', name=name + '-rh',
subject=subject, color=color).fill(source_space)
label = BiHemiLabel(lh, rh, name, color)
elif len(lh_vertices):
label = Label(lh_vertices, hemi='lh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
elif len(rh_vertices):
label = Label(rh_vertices, hemi='rh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
else:
raise ValueError("Empty Cluster")
labels.append(label)
return labels
def labels_from_clusters(clusters, names=None):
"""Create Labels from source space clusters
Parameters
----------
clusters : NDVar
NDVar which is non-zero on the cluster. Can have a case dimension, but
does not have to.
names : None | list of str | str
Label names corresponding to clusters (default is "cluster%i").
Returns
-------
labels : list of mne.Label
One label for each cluster.
"""
from mne.label import _n_colors
if isinstance(names, str):
names = [names]
source = clusters.source
source_space = clusters.source.get_source_space()
subject = source.subject
collapse = tuple(dim for dim in clusters.dimnames if dim not in ('case', 'source'))
clusters_index = clusters.any(collapse)
if clusters_index.has_case:
n_clusters = len(clusters)
else:
n_clusters = 1
clusters_index = (clusters_index,)
if names is None:
names = ("cluster%i" % i for i in range(n_clusters))
elif len(names) != n_clusters:
err = "Number of names difference from number of clusters."
raise ValueError(err)
colors = _n_colors(n_clusters)
labels = []
for cluster, color, name in zip(clusters_index, colors, names):
lh_vertices = source.lh_vertno[cluster.x[:source.lh_n]]
rh_vertices = source.rh_vertno[cluster.x[source.lh_n:]]
if len(lh_vertices) and len(rh_vertices):
lh = Label(lh_vertices, hemi='lh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
rh = Label(rh_vertices, hemi='rh', name=name + '-rh',
subject=subject, color=color).fill(source_space)
label = BiHemiLabel(lh, rh, name, color)
elif len(lh_vertices):
label = Label(lh_vertices, hemi='lh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
elif len(rh_vertices):
label = Label(rh_vertices, hemi='rh', name=name + '-lh',
subject=subject, color=color).fill(source_space)
else:
raise ValueError("Empty Cluster")
labels.append(label)
return labels
def labels_from_clusters(clusters, names=None):
"""Create Labels from source space clusters
Parameters
----------
clusters : NDVar
NDVar which is non-zero on the cluster. Can have a case dimension.
names : None | list of str | str
Label names corresponding to clusters (default is "clusterX").
Returns
-------
labels : list of mne.Label
One label for each cluster.
"""
from mne.label import _n_colors
source = clusters.source
source_space = clusters.source.get_source_space()
subject = source.subject
if clusters.has_case:
n_clusters = len(clusters)
x = clusters.x
else:
n_clusters = 1
x = clusters.x[None, :]
if isinstance(names, basestring) and n_clusters == 1:
names = [names]
elif names is None:
names = ("cluster%i" % i for i in xrange(n_clusters))
elif len(names) != n_clusters:
err = "Number of names difference from number of clusters."
raise ValueError(err)
colors = _n_colors(n_clusters)
labels = []
for i, color, name in izip(xrange(n_clusters), colors, names):
idx = (x[i] != 0)
where = np.nonzero(idx)[0]
src_in_lh = (where < source.lh_n)
if np.all(src_in_lh):
hemi = 'lh'
hemi_vertices = source.lh_vertno
elif np.any(src_in_lh):
raise ValueError("Can't have clusters spanning both hemispheres")
else:
hemi = 'rh'
hemi_vertices = source.rh_vertno
where -= source.lh_n
vertices = hemi_vertices[where]
label = Label(vertices, hemi=hemi, name=name, subject=subject,
color=color).fill(source_space)
labels.append(label)
return labels
def labels_from_clusters(clusters, names=None):
"""Create Labels from source space clusters
Parameters
----------
clusters : NDVar
NDVar which is non-zero on the cluster. Can have a case dimension.
names : None | list of str | str
Label names corresponding to clusters (default is "clusterX").
Returns
-------
labels : list of mne.Label
One label for each cluster.
"""
from mne.label import _n_colors
source = clusters.source
source_space = clusters.source.get_source_space()
subject = source.subject
if clusters.has_case:
n_clusters = len(clusters)
x = clusters.x
else:
n_clusters = 1
x = clusters.x[None, :]
if isinstance(names, basestring) and n_clusters == 1:
names = [names]
elif names is None:
names = ("cluster%i" % i for i in xrange(n_clusters))
elif len(names) != n_clusters:
err = "Number of names difference from number of clusters."
raise ValueError(err)
colors = _n_colors(n_clusters)
labels = []
for i, color, name in izip(xrange(n_clusters), colors, names):
idx = (x[i] != 0)
where = np.nonzero(idx)[0]
src_in_lh = (where < source.lh_n)
if np.all(src_in_lh):
hemi = 'lh'
hemi_vertices = source.lh_vertno
elif np.any(src_in_lh):
raise ValueError("Can't have clusters spanning both hemispheres")
else:
hemi = 'rh'
hemi_vertices = source.rh_vertno
where -= source.lh_n
vertices = hemi_vertices[where]
label = Label(vertices, hemi=hemi, name=name, subject=subject,
color=color, src=source_space)
labels.append(label)
return labels
def _stc_to_label(stc, src, smooth, subjects_dir=None):
"""Compute a label from the non-zero sources in an stc object.
Parameters
----------
stc : SourceEstimate
The source estimates.
src : SourceSpaces | str | None
The source space over which the source estimates are defined.
If it's a string it should the subject name (e.g. fsaverage).
Can be None if stc.subject is not None.
smooth : int
Number of smoothing iterations.
subjects_dir : str | None
Path to SUBJECTS_DIR if it is not set in the environment.
Returns
-------
labels : list of Labels | list of list of Labels
The generated labels. If connected is False, it returns
a list of Labels (one per hemisphere). If no Label is available
in a hemisphere, None is returned. If connected is True,
it returns for each hemisphere a list of connected labels
ordered in decreasing order depending of the maximum value in the stc.
If no Label is available in an hemisphere, an empty list is returned.
"""
src = stc.subject if src is None else src
if isinstance(src, string_types):
subject = src
else:
subject = stc.subject
if isinstance(src, string_types):
subjects_dir = get_subjects_dir(subjects_dir)
surf_path_from = op.join(subjects_dir, src, 'surf')
rr_lh, tris_lh = read_surface(op.join(surf_path_from, 'lh.white'))
rr_rh, tris_rh = read_surface(op.join(surf_path_from, 'rh.white'))
rr = [rr_lh, rr_rh]
tris = [tris_lh, tris_rh]
else:
if not isinstance(src, SourceSpaces):
raise TypeError('src must be a string or a set of source spaces')
if len(src) != 2:
raise ValueError('source space should contain the 2 hemispheres')
rr = [1e3 * src[0]['rr'], 1e3 * src[1]['rr']]
tris = [src[0]['tris'], src[1]['tris']]
labels = []
cnt = 0
for hemi_idx, (hemi, this_vertno, this_tris, this_rr) in enumerate(
zip(['lh', 'rh'], stc.vertices, tris, rr)):
this_data = stc.data[cnt:cnt + len(this_vertno)]
e = mesh_edges(this_tris)
e.data[e.data == 2] = 1
n_vertices = e.shape[0]
e = e + sparse.eye(n_vertices, n_vertices)
clusters = [this_vertno[np.any(this_data, axis=1)]]
cnt += len(this_vertno)
clusters = [c for c in clusters if len(c) > 0]
if len(clusters) == 0:
this_labels = None
else:
this_labels = []
colors = _n_colors(len(clusters))
for c, color in zip(clusters, colors):
idx_use = c
for k in range(smooth):
e_use = e[:, idx_use]
data1 = e_use * np.ones(len(idx_use))
idx_use = np.where(data1)[0]
label = Label(idx_use,
this_rr[idx_use],
None,
hemi,
'Label from stc',
subject=subject,
color=color)
this_labels.append(label)
this_labels = this_labels[0]
labels.append(this_labels)
return labels
def write_labels_to_annot(labels,
subject=None,
parc=None,
overwrite=False,
subjects_dir=None,
annot_fname=None,
colormap='hsv',
hemi='both'):
"""Create a FreeSurfer annotation from a list of labels
FIX: always write both hemispheres
Parameters
----------
labels : list with instances of mne.Label
The labels to create a parcellation from.
subject : str | None
The subject for which to write the parcellation for.
parc : str | None
The parcellation name to use.
overwrite : bool
Overwrite files if they already exist.
subjects_dir : string, or None
Path to SUBJECTS_DIR if it is not set in the environment.
annot_fname : str | None
Filename of the .annot file. If not None, only this file is written
and 'parc' and 'subject' are ignored.
colormap : str
Colormap to use to generate label colors for labels that do not
have a color specified.
hemi : 'both' | 'lh' | 'rh'
The hemisphere(s) for which to write *.annot files (only applies if
annot_fname is not specified; default is 'both').
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
Notes
-----
Vertices that are not covered by any of the labels are assigned to a label
named "unknown".
"""
subjects_dir = get_subjects_dir(subjects_dir)
# get the .annot filenames and hemispheres
annot_fname, hemis = _get_annot_fname(annot_fname, subject, hemi, parc,
subjects_dir)
if not overwrite:
for fname in annot_fname:
if op.exists(fname):
raise ValueError('File %s exists. Use "overwrite=True" to '
'overwrite it' % fname)
# prepare container for data to save:
to_save = []
# keep track of issues found in the labels
duplicate_colors = []
invalid_colors = []
overlap = []
no_color = (-1, -1, -1, -1)
no_color_rgb = (-1, -1, -1)
for hemi, fname in zip(hemis, annot_fname):
hemi_labels = [label for label in labels if label.hemi == hemi]
n_hemi_labels = len(hemi_labels)
if n_hemi_labels == 0:
ctab = np.empty((0, 4), dtype=np.int32)
ctab_rgb = ctab[:, :3]
else:
hemi_labels.sort(key=lambda label: label.name)
# convert colors to 0-255 RGBA tuples
hemi_colors = [
no_color if label.color is None else tuple(
int(round(255 * i)) for i in label.color)
for label in hemi_labels
]
ctab = np.array(hemi_colors, dtype=np.int32)
ctab_rgb = ctab[:, :3]
# make color dict (for annot ID, only R, G and B count)
labels_by_color = defaultdict(list)
for label, color in zip(hemi_labels, ctab_rgb):
labels_by_color[tuple(color)].append(label.name)
# check label colors
for color, names in labels_by_color.items():
if color == no_color_rgb:
continue
if color == (0, 0, 0):
# we cannot have an all-zero color, otherw. e.g. tksurfer
# refuses to read the parcellation
msg = ('At least one label contains a color with, "r=0, '
'g=0, b=0" value. Some FreeSurfer tools may fail '
'to read the parcellation')
logger.warning(msg)
if any(i > 255 for i in color):
msg = ("%s: %s (%s)" % (color, ', '.join(names), hemi))
invalid_colors.append(msg)
if len(names) > 1:
msg = "%s: %s (%s)" % (color, ', '.join(names), hemi)
duplicate_colors.append(msg)
# replace None values (labels with unspecified color)
if labels_by_color[no_color_rgb]:
default_colors = _n_colors(n_hemi_labels,
bytes_=True,
cmap=colormap)
safe_color_i = 0 # keep track of colors known to be in hemi_colors
for i in xrange(n_hemi_labels):
if ctab[i, 0] == -1:
color = default_colors[i]
# make sure to add no duplicate color
while np.any(np.all(color[:3] == ctab_rgb, 1)):
color = default_colors[safe_color_i]
safe_color_i += 1
# assign the color
ctab[i] = color
# find number of vertices in surface
if subject is not None and subjects_dir is not None:
fpath = op.join(subjects_dir, subject, 'surf', '%s.white' % hemi)
points, _ = read_surface(fpath)
n_vertices = len(points)
else:
if len(hemi_labels) > 0:
max_vert = max(np.max(label.vertices) for label in hemi_labels)
n_vertices = max_vert + 1
else:
n_vertices = 1
msg = (' Number of vertices in the surface could not be '
'verified because the surface file could not be found; '
'specify subject and subjects_dir parameters.')
logger.warning(msg)
# Create annot and color table array to write
annot = np.empty(n_vertices, dtype=np.intp)
annot[:] = -1
# create the annotation ids from the colors
annot_id_coding = np.array((1, 2**8, 2**16))
annot_ids = list(np.sum(ctab_rgb * annot_id_coding, axis=1))
for label, annot_id in zip(hemi_labels, annot_ids):
# make sure the label is not overwriting another label
if np.any(annot[label.vertices] != -1):
other_ids = set(annot[label.vertices])
other_ids.discard(-1)
other_indices = (annot_ids.index(i) for i in other_ids)
other_names = (hemi_labels[i].name for i in other_indices)
other_repr = ', '.join(other_names)
msg = "%s: %s overlaps %s" % (hemi, label.name, other_repr)
overlap.append(msg)
annot[label.vertices] = annot_id
hemi_names = [label.name for label in hemi_labels]
# Assign unlabeled vertices to an "unknown" label
unlabeled = (annot == -1)
if np.any(unlabeled):
msg = ("Assigning %i unlabeled vertices to "
"'unknown-%s'" % (unlabeled.sum(), hemi))
logger.info(msg)
# find an unused color (try shades of gray first)
for i in range(1, 257):
if not np.any(np.all((i, i, i) == ctab_rgb, 1)):
break
if i < 256:
color = (i, i, i, 0)
else:
err = ("Need one free shade of gray for 'unknown' label. "
"Please modify your label colors, or assign the "
"unlabeled vertices to another label.")
raise ValueError(err)
# find the id
annot_id = np.sum(annot_id_coding * color[:3])
# update data to write
annot[unlabeled] = annot_id
ctab = np.vstack((ctab, color))
hemi_names.append("unknown")
# convert to FreeSurfer alpha values
ctab[:, 3] = 255 - ctab[:, 3]
# remove hemi ending in names
hemi_names = [
name[:-3] if name.endswith(hemi) else name for name in hemi_names
]
to_save.append((fname, annot, ctab, hemi_names))
issues = []
if duplicate_colors:
msg = ("Some labels have the same color values (all labels in one "
"hemisphere must have a unique color):")
duplicate_colors.insert(0, msg)
issues.append('\n'.join(duplicate_colors))
if invalid_colors:
msg = ("Some labels have invalid color values (all colors should be "
"RGBA tuples with values between 0 and 1)")
invalid_colors.insert(0, msg)
issues.append('\n'.join(invalid_colors))
if overlap:
msg = ("Some labels occupy vertices that are also occupied by one or "
"more other labels. Each vertex can only be occupied by a "
"single label in *.annot files.")
overlap.insert(0, msg)
issues.append('\n'.join(overlap))
if issues:
raise ValueError('\n\n'.join(issues))
# write it
for fname, annot, ctab, hemi_names in to_save:
logger.info(' writing %d labels to %s' % (len(hemi_names), fname))
_write_annot(fname, annot, ctab, hemi_names)
logger.info('[done]')
def _stc_to_label(stc, src, smooth, subjects_dir=None):
"""Compute a label from the non-zero sources in an stc object.
Parameters
----------
stc : SourceEstimate
The source estimates.
src : SourceSpaces | str | None
The source space over which the source estimates are defined.
If it's a string it should the subject name (e.g. fsaverage).
Can be None if stc.subject is not None.
smooth : int
Number of smoothing iterations.
subjects_dir : str | None
Path to SUBJECTS_DIR if it is not set in the environment.
Returns
-------
labels : list of Labels | list of list of Labels
The generated labels. If connected is False, it returns
a list of Labels (one per hemisphere). If no Label is available
in a hemisphere, None is returned. If connected is True,
it returns for each hemisphere a list of connected labels
ordered in decreasing order depending of the maximum value in the stc.
If no Label is available in an hemisphere, an empty list is returned.
"""
src = stc.subject if src is None else src
if isinstance(src, string_types):
subject = src
else:
subject = stc.subject
if isinstance(src, string_types):
subjects_dir = get_subjects_dir(subjects_dir)
surf_path_from = op.join(subjects_dir, src, 'surf')
rr_lh, tris_lh = read_surface(op.join(surf_path_from,
'lh.white'))
rr_rh, tris_rh = read_surface(op.join(surf_path_from,
'rh.white'))
rr = [rr_lh, rr_rh]
tris = [tris_lh, tris_rh]
else:
if not isinstance(src, SourceSpaces):
raise TypeError('src must be a string or a set of source spaces')
if len(src) != 2:
raise ValueError('source space should contain the 2 hemispheres')
rr = [1e3 * src[0]['rr'], 1e3 * src[1]['rr']]
tris = [src[0]['tris'], src[1]['tris']]
labels = []
cnt = 0
for hemi_idx, (hemi, this_vertno, this_tris, this_rr) in enumerate(
zip(['lh', 'rh'], stc.vertices, tris, rr)):
this_data = stc.data[cnt:cnt + len(this_vertno)]
e = mesh_edges(this_tris)
e.data[e.data == 2] = 1
n_vertices = e.shape[0]
e = e + sparse.eye(n_vertices, n_vertices)
clusters = [this_vertno[np.any(this_data, axis=1)]]
cnt += len(this_vertno)
clusters = [c for c in clusters if len(c) > 0]
if len(clusters) == 0:
this_labels = None
else:
this_labels = []
colors = _n_colors(len(clusters))
for c, color in zip(clusters, colors):
idx_use = c
for k in range(smooth):
e_use = e[:, idx_use]
data1 = e_use * np.ones(len(idx_use))
idx_use = np.where(data1)[0]
label = Label(idx_use, this_rr[idx_use], None, hemi,
'Label from stc', subject=subject,
color=color)
this_labels.append(label)
this_labels = this_labels[0]
labels.append(this_labels)
return labels
# Compute goodness of fit
gof = _sesame.goodness_of_fit()
print(' Goodness of fit with the recorded data: {0}%'.format(
round(gof, 4) * 100))
###############################################################################
# Visualize amplitude of the estimated sources as function of time.
est_n_dips = _sesame.est_n_dips[-1]
est_locs = _sesame.est_locs[-1]
times = evoked.times[_sesame.s_min:_sesame.s_max + 1]
amplitude = np.array([
np.linalg.norm(_sesame.est_dip_moms[:, 3 * i_d:3 * (i_d + 1)], axis=1)
for i_d in range(est_n_dips)
])
colors = _n_colors(est_n_dips)
plt.figure()
for idx, amp in enumerate(amplitude):
plt.plot(times, 1e9 * amp, color=colors[idx], linewidth=2)
plt.xlabel('Time (s)')
plt.ylabel('Source amplitude (nAm)')
plt.show()
###############################################################################
# Visualize the posterior map of the dipoles' location
# :math:`p(r| \textbf{y}, 2)` as an overlay onto the MRI.
stc = _sesame.compute_stc(subject)
peak_vertex, peak_time = stc.get_peak(vert_as_index=True, time_as_index=True)
peak_pos = fwd['source_rr'][peak_vertex]
peak_mri_pos = head_to_mri(peak_pos,
def write_labels_to_annot(labels, subject=None, parc=None, overwrite=False,
subjects_dir=None, annot_fname=None,
colormap='hsv', hemi='both'):
"""Create a FreeSurfer annotation from a list of labels
FIX: always write both hemispheres
Parameters
----------
labels : list with instances of mne.Label
The labels to create a parcellation from.
subject : str | None
The subject for which to write the parcellation for.
parc : str | None
The parcellation name to use.
overwrite : bool
Overwrite files if they already exist.
subjects_dir : string, or None
Path to SUBJECTS_DIR if it is not set in the environment.
annot_fname : str | None
Filename of the .annot file. If not None, only this file is written
and 'parc' and 'subject' are ignored.
colormap : str
Colormap to use to generate label colors for labels that do not
have a color specified.
hemi : 'both' | 'lh' | 'rh'
The hemisphere(s) for which to write *.annot files (only applies if
annot_fname is not specified; default is 'both').
verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose).
Notes
-----
Vertices that are not covered by any of the labels are assigned to a label
named "unknown".
"""
subjects_dir = get_subjects_dir(subjects_dir)
# get the .annot filenames and hemispheres
annot_fname, hemis = _get_annot_fname(annot_fname, subject, hemi, parc,
subjects_dir)
if not overwrite:
for fname in annot_fname:
if op.exists(fname):
raise ValueError('File %s exists. Use "overwrite=True" to '
'overwrite it' % fname)
# prepare container for data to save:
to_save = []
# keep track of issues found in the labels
duplicate_colors = []
invalid_colors = []
overlap = []
no_color = (-1, -1, -1, -1)
no_color_rgb = (-1, -1, -1)
for hemi, fname in zip(hemis, annot_fname):
hemi_labels = [label for label in labels if label.hemi == hemi]
n_hemi_labels = len(hemi_labels)
if n_hemi_labels == 0:
ctab = np.empty((0, 4), dtype=np.int32)
ctab_rgb = ctab[:, :3]
else:
hemi_labels.sort(key=lambda label: label.name)
# convert colors to 0-255 RGBA tuples
hemi_colors = [no_color if label.color is None else
tuple(int(round(255 * i)) for i in label.color)
for label in hemi_labels]
ctab = np.array(hemi_colors, dtype=np.int32)
ctab_rgb = ctab[:, :3]
# make color dict (for annot ID, only R, G and B count)
labels_by_color = defaultdict(list)
for label, color in zip(hemi_labels, ctab_rgb):
labels_by_color[tuple(color)].append(label.name)
# check label colors
for color, names in labels_by_color.items():
if color == no_color_rgb:
continue
if color == (0, 0, 0):
# we cannot have an all-zero color, otherw. e.g. tksurfer
# refuses to read the parcellation
msg = ('At least one label contains a color with, "r=0, '
'g=0, b=0" value. Some FreeSurfer tools may fail '
'to read the parcellation')
logger.warning(msg)
if any(i > 255 for i in color):
msg = ("%s: %s (%s)" % (color, ', '.join(names), hemi))
invalid_colors.append(msg)
if len(names) > 1:
msg = "%s: %s (%s)" % (color, ', '.join(names), hemi)
duplicate_colors.append(msg)
# replace None values (labels with unspecified color)
if labels_by_color[no_color_rgb]:
default_colors = _n_colors(n_hemi_labels, bytes_=True,
cmap=colormap)
safe_color_i = 0 # keep track of colors known to be in hemi_colors
for i in xrange(n_hemi_labels):
if ctab[i, 0] == -1:
color = default_colors[i]
# make sure to add no duplicate color
while np.any(np.all(color[:3] == ctab_rgb, 1)):
color = default_colors[safe_color_i]
safe_color_i += 1
# assign the color
ctab[i] = color
# find number of vertices in surface
if subject is not None and subjects_dir is not None:
fpath = os.path.join(subjects_dir, subject, 'surf',
'%s.white' % hemi)
points, _ = read_surface(fpath)
n_vertices = len(points)
else:
if len(hemi_labels) > 0:
max_vert = max(np.max(label.vertices) for label in hemi_labels)
n_vertices = max_vert + 1
else:
n_vertices = 1
msg = (' Number of vertices in the surface could not be '
'verified because the surface file could not be found; '
'specify subject and subjects_dir parameters.')
logger.warning(msg)
# Create annot and color table array to write
annot = np.empty(n_vertices, dtype=np.int)
annot[:] = -1
# create the annotation ids from the colors
annot_id_coding = np.array((1, 2 ** 8, 2 ** 16))
annot_ids = list(np.sum(ctab_rgb * annot_id_coding, axis=1))
for label, annot_id in zip(hemi_labels, annot_ids):
# make sure the label is not overwriting another label
if np.any(annot[label.vertices] != -1):
other_ids = set(annot[label.vertices])
other_ids.discard(-1)
other_indices = (annot_ids.index(i) for i in other_ids)
other_names = (hemi_labels[i].name for i in other_indices)
other_repr = ', '.join(other_names)
msg = "%s: %s overlaps %s" % (hemi, label.name, other_repr)
overlap.append(msg)
annot[label.vertices] = annot_id
hemi_names = [label.name for label in hemi_labels]
# Assign unlabeled vertices to an "unknown" label
unlabeled = (annot == -1)
if np.any(unlabeled):
msg = ("Assigning %i unlabeled vertices to "
"'unknown-%s'" % (unlabeled.sum(), hemi))
logger.info(msg)
# find an unused color (try shades of gray first)
for i in range(1, 257):
if not np.any(np.all((i, i, i) == ctab_rgb, 1)):
break
if i < 256:
color = (i, i, i, 0)
else:
err = ("Need one free shade of gray for 'unknown' label. "
"Please modify your label colors, or assign the "
"unlabeled vertices to another label.")
raise ValueError(err)
# find the id
annot_id = np.sum(annot_id_coding * color[:3])
# update data to write
annot[unlabeled] = annot_id
ctab = np.vstack((ctab, color))
hemi_names.append("unknown")
# convert to FreeSurfer alpha values
ctab[:, 3] = 255 - ctab[:, 3]
# remove hemi ending in names
hemi_names = [name[:-3] if name.endswith(hemi) else name
for name in hemi_names]
to_save.append((fname, annot, ctab, hemi_names))
issues = []
if duplicate_colors:
msg = ("Some labels have the same color values (all labels in one "
"hemisphere must have a unique color):")
duplicate_colors.insert(0, msg)
issues.append(os.linesep.join(duplicate_colors))
if invalid_colors:
msg = ("Some labels have invalid color values (all colors should be "
"RGBA tuples with values between 0 and 1)")
invalid_colors.insert(0, msg)
issues.append(os.linesep.join(invalid_colors))
if overlap:
msg = ("Some labels occupy vertices that are also occupied by one or "
"more other labels. Each vertex can only be occupied by a "
"single label in *.annot files.")
overlap.insert(0, msg)
issues.append(os.linesep.join(overlap))
if issues:
raise ValueError('\n\n'.join(issues))
# write it
for fname, annot, ctab, hemi_names in to_save:
logger.info(' writing %d labels to %s' % (len(hemi_names), fname))
_write_annot(fname, annot, ctab, hemi_names)
logger.info('[done]')
