def rotate_brain_via_lookup(elc_name, loc):
cortical_probs_max, subcortical_probs_max = 0, 0
cortical_probs_rois = \
[(p, r) for p, r in zip(loc['cortical_probs'], loc['cortical_rois']) if 'white' not in r.lower()]
subcortical_probs_rois = \
[(p, r) for p, r in zip(loc['subcortical_probs'], loc['subcortical_rois']) if 'white' not in r.lower()]
if len(cortical_probs_rois) > 0:
cortical_probs_ind = np.argmax(cortical_probs_rois, 0)[0]
cortical_probs_max = cortical_probs_rois[cortical_probs_ind][0]
if len(subcortical_probs_rois) > 0:
subcortical_probs_ind = np.argmax(subcortical_probs_rois, 0)[0]
subcortical_probs_max = subcortical_probs_rois[subcortical_probs_ind][0]
if cortical_probs_max > subcortical_probs_max:
max_roi = cortical_probs_rois[cortical_probs_ind][1]
max_roi_is_cortical = True
else:
max_roi = subcortical_probs_rois[subcortical_probs_ind][1]
max_roi_is_cortical = False
if max_roi_is_cortical:
atlas = bpy.context.scene.electrodes_labeling_files.split('_')[1]
hemi = mu.get_obj_hemi(max_roi)
annot_fname = mu.get_annot_fname(hemi, atlas)
max_roi_vertices_indices = mu.read_label_vertices_from_annot(annot_fname, max_roi)
if max_roi_vertices_indices is None:
print('Can\'t find {} vertices in {}!'.format(max_roi, annot_fname))
return
elc_pos = bpy.data.objects[elc_name].location
mesh = 'inflated_{}'.format(hemi)
vert_ind, vert_pos = _addon().vertex_data.find_closest_vertices(
elc_pos, max_roi_vertices_indices, mesh, False)
vert_pos *= 0.1
mu.rotate_view_to_vertice(vert_ind, mesh)
def plot_labels_probs(elc):
_addon().init_activity_map_coloring('FMRI')
if bpy.context.scene.electrodes_what_to_color == 'probs':
if len(elc['cortical_rois']) > 0:
hemi = mu.get_obj_hemi(elc['cortical_rois'][0])
if not hemi is None:
labels_data = dict(data=elc['cortical_probs'],
names=elc['cortical_rois'])
if not _addon().colorbar_values_are_locked():
_addon().set_colorbar_title('Electrodes probabilities')
_addon().set_colormap('YlOrRd')
atlas = bpy.context.scene.electrodes_labeling_files.split(
'_')[1:-6][0]
_addon().labels_coloring_hemi(labels_data,
ElecsPanel.faces_verts,
hemi,
0,
colors_min=0,
colors_max=1,
atlas=atlas)
colors = mu.get_distinct_colors(len(elc['cortical_rois']))
if bpy.context.scene.electrodes_label_contours:
_addon().color_contours(elc['cortical_rois'],
specific_colors=colors)
else:
print("Can't get the rois hemi!")
else:
_addon().clear_cortex()
_addon().clear_subcortical_regions()
if len(elc['subcortical_rois']) > 0:
cm = _addon().get_cm()
colors = mu.calc_colors_from_cm(elc['subcortical_probs'], 0, 256,
cm)
for region, color in zip(elc['subcortical_rois'], colors):
_addon().color_subcortical_region(region, color)
elif bpy.context.scene.electrodes_what_to_color == 'verts':
if len(elc['cortical_indices']) > 0:
hemi = bpy.data.objects[elc['hemi']]
if not hemi is None:
_addon().init_activity_map_coloring('FMRI', subcorticals=True)
vertices_num = np.max(elc['cortical_indices']) + 1
activity = np.ones((vertices_num, 4))
activity[:, 0] = 0
activity[elc['cortical_indices'], 0] = 1
activity[elc['cortical_indices'],
1:] = np.tile(cu.name_to_rgb('blue'),
(len(elc['cortical_indices']), 1))
print('Plot {} vertices with blue'.format(
len(elc['cortical_indices'])))
_addon().activity_map_obj_coloring(
hemi, activity, ElecsPanel.faces_verts[elc['hemi']], 0,
True)
else:
print("Can't get the elec's hemi!")
else:
_addon().clear_cortex()
print('No cortical vertices for {}'.format(elc['name']))
def plot_labels_probs(elc):
_addon().init_activity_map_coloring('FMRI')
if bpy.context.scene.electrodes_what_to_color == 'probs':
if len(elc['cortical_rois']) > 0:
hemi = mu.get_obj_hemi(elc['cortical_rois'][0])
if not hemi is None:
labels_data = dict(data=elc['cortical_probs'],
names=elc['cortical_rois'])
_addon().set_colorbar_title('Electrodes probabilities')
_addon().set_colormap('YlOrRd')
_addon().labels_coloring_hemi(labels_data,
ElecsPanel.faces_verts,
hemi,
0,
colors_min=0,
colors_max=1)
else:
print("Can't get the rois hemi!")
else:
_addon().clear_cortex()
_addon().clear_subcortical_regions()
if len(elc['subcortical_rois']) > 0:
for region, color in zip(elc['subcortical_rois'],
elc['subcortical_colors'][:, :3]):
_addon().color_subcortical_region(region, color)
elif bpy.context.scene.electrodes_what_to_color == 'verts':
if len(elc['cortical_indices']) > 0:
hemi = bpy.data.objects[elc['hemi']]
if not hemi is None:
_addon().init_activity_map_coloring('FMRI', subcorticals=True)
vertices_num = np.max(elc['cortical_indices']) + 1
activity = np.ones((vertices_num, 4))
activity[:, 0] = 0
activity[elc['cortical_indices'], 0] = 1
activity[elc['cortical_indices'],
1:] = np.tile(cu.name_to_rgb('blue'),
(len(elc['cortical_indices']), 1))
print('Plot {} vertices with blue'.format(
len(elc['cortical_indices'])))
_addon().activity_map_obj_coloring(
hemi, activity, ElecsPanel.faces_verts[elc['hemi']], 0,
True)
else:
print("Can't get the elec's hemi!")
else:
_addon().clear_cortex()
print('No cortical vertices for {}'.format(elc['name']))
def plot_labels_probs(elc):
ElecsPanel.addon.init_activity_map_coloring('FMRI')
if bpy.context.scene.electrodes_what_to_color == 'probs':
if len(elc['cortical_rois']) > 0:
hemi = mu.get_obj_hemi(elc['cortical_rois'][0])
if not hemi is None:
# if no matplotlib should calculate the colors offline :(
labels_data = dict(data=elc['cortical_probs'],
colors=elc['cortical_colors'][:, :3],
names=elc['cortical_rois'])
ElecsPanel.addon.meg_labels_coloring_hemi(
labels_data, ElecsPanel.faces_verts, hemi, 0)
else:
print("Can't get the rois hemi!")
else:
ElecsPanel.addon.clear_cortex()
ElecsPanel.addon.clear_subcortical_regions()
if len(elc['subcortical_rois']) > 0:
for region, color in zip(elc['subcortical_rois'],
elc['subcortical_colors'][:, :3]):
ElecsPanel.addon.color_subcortical_region(region, color)
elif bpy.context.scene.electrodes_what_to_color == 'verts':
if len(elc['cortical_indices']) > 0:
hemi = bpy.data.objects[elc['hemi']]
if not hemi is None:
ElecsPanel.addon.init_activity_map_coloring('FMRI',
subcorticals=True)
vertices_num = np.max(elc['cortical_indices']) + 1
activity = np.ones((vertices_num, 4))
activity[:, 0] = 0
activity[elc['cortical_indices'], 0] = 1
activity[elc['cortical_indices'],
1:] = np.tile(cu.name_to_rgb('blue'),
(len(elc['cortical_indices']), 1))
print('Plot {} vertices with blue'.format(
len(elc['cortical_indices'])))
ElecsPanel.addon.activity_map_obj_coloring(
hemi, activity, ElecsPanel.faces_verts[elc['hemi']], 0,
True)
else:
print("Can't get the elec's hemi!")
else:
ElecsPanel.addon.clear_cortex()
print('No cortical vertices for {}'.format(elc['name']))
def invoke(self, context, event=None):
label_name = context.scene.labels_regex
SearchMark.marked_objects_select = {}
objects = mu.get_non_functional_objects()
SearchPanel.marked_objects = []
for obj in objects:
SearchFilter.marked_objects_select[obj.name] = obj.select
obj.select = label_name in obj.name
try:
import fnmatch
if fnmatch.fnmatch(obj.name, '*{}*'.format(label_name)):
SearchPanel.marked_objects.append(obj.name)
except:
if label_name in obj.name:
SearchPanel.marked_objects.append(obj.name)
if len(SearchPanel.marked_objects) == 0:
print('No objects found for "{}"'.format(
context.scene.labels_regex))
return
# todo: show rois only if the object is an ROI. Also, move the cursor
selected_obj = bpy.data.objects[SearchPanel.marked_objects[0]]
verts = np.array([vert.co for vert in selected_obj.data.vertices])
center = np.mean(verts, axis=0)
if any([mu.obj_is_cortex(o) for o in SearchPanel.marked_objects]):
selected_roi = [
o for o in SearchPanel.marked_objects if mu.obj_is_cortex(o)
][0]
hemi = mu.get_obj_hemi(selected_roi)
center = _addon().where_am_i.pos_to_current_inflation(center,
hemis=[hemi])
else:
center = mathutils.Vector(center) * mu.get_matrix_world()
# if bpy.context.scene.search_plot_contour:
# _addon().where_am_i.plot_closest_label_contour(selected_roi, hemi)
# bpy.context.scene.cursor_location = tuple(center)
_addon().where_am_i.set_cursor_location(center)
# _addon().set_cursor_pos()
# _addon().set_tkreg_ras(bpy.context.scene.cursor_location * 10, False)
if bpy.context.scene.slices_rotate_view_on_click:
mu.rotate_view_to_vertice()
# if any([mu.obj_is_cortex(o.name) for o in SearchPanel.marked_objects]):
# SearchPanel.addon.show_rois()
return {"FINISHED"}
def plot_labels_probs(elc):
ElecsPanel.addon.init_activity_map_coloring('FMRI')
if bpy.context.scene.electrodes_what_to_color == 'probs':
if len(elc['cortical_rois']) > 0:
hemi = mu.get_obj_hemi(elc['cortical_rois'][0])
if not hemi is None:
# if no matplotlib should calculate the colors offline :(
labels_data = dict(data=elc['cortical_probs'], colors=elc['cortical_colors'][:, :3],
names=elc['cortical_rois'])
ElecsPanel.addon.meg_labels_coloring_hemi(labels_data, ElecsPanel.faces_verts, hemi, 0)
else:
print("Can't get the rois hemi!")
else:
ElecsPanel.addon.clear_cortex()
ElecsPanel.addon.clear_subcortical_regions()
if len(elc['subcortical_rois']) > 0:
for region, color in zip(elc['subcortical_rois'], elc['subcortical_colors'][:, :3]):
ElecsPanel.addon.color_subcortical_region(region, color)
elif bpy.context.scene.electrodes_what_to_color == 'verts':
if len(elc['cortical_indices']) > 0:
hemi = bpy.data.objects[elc['hemi']]
if not hemi is None:
ElecsPanel.addon.init_activity_map_coloring('FMRI', subcorticals=True)
vertices_num = np.max(elc['cortical_indices']) + 1
activity = np.ones((vertices_num, 4))
activity[:, 0] = 0
activity[elc['cortical_indices'], 0] = 1
activity[elc['cortical_indices'], 1:] = np.tile(
cu.name_to_rgb('blue'), (len(elc['cortical_indices']), 1))
print('Plot {} vertices with blue'.format(len(elc['cortical_indices'])))
ElecsPanel.addon.activity_map_obj_coloring(hemi, activity, ElecsPanel.faces_verts[elc['hemi']], 0, True)
else:
print("Can't get the elec's hemi!")
else:
ElecsPanel.addon.clear_cortex()
print('No cortical vertices for {}'.format(elc['name']))