def init(addon):
from random import shuffle
ColoringMakerPanel.addon = addon
user_fol = mu.get_user_fol()
ColoringMakerPanel.faces_verts = None
labels_vertices_fname = op.join(user_fol, 'labels_vertices_{}.pkl'.format(bpy.context.scene.atlas))
if not op.isfile(labels_vertices_fname):
print("!!! Can't find {}!".format('labels_vertices_{}.pkl'.format(bpy.context.scene.atlas)))
return None
labels_names, labels_vertices = mu.load(labels_vertices_fname)
ColoringMakerPanel.labels_vertices = dict(labels_names=labels_names, labels_vertices=labels_vertices)
fmri_files = glob.glob(op.join(user_fol, 'fmri', 'fmri_*_lh.npy'))
if len(fmri_files) > 0:
files_names = [mu.namebase(fname)[5:-3] for fname in fmri_files]
clusters_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.fmri_files = bpy.props.EnumProperty(
items=clusters_items, description="fMRI files", update=fmri_files_update)
bpy.context.scene.fmri_files = files_names[0]
for hemi in mu.HEMIS:
ColoringMakerPanel.fMRI[hemi] = np.load('{}_{}.npy'.format(fmri_files[0][:-7], hemi))
electrodes_source_files = glob.glob(op.join(user_fol, 'electrodes', '*_labels_*-rh.npz'))
if len(electrodes_source_files) > 0:
files_names = [mu.namebase(fname)[:-len('-rh')] for fname in electrodes_source_files]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_sources_files = bpy.props.EnumProperty(
items=items, description="electrodes sources", update=electrodes_sources_files_update)
bpy.context.scene.electrodes_sources_files = files_names[0]
mu.make_dir(op.join(user_fol, 'coloring'))
manually_color_files = glob.glob(op.join(user_fol, 'coloring', '*.csv'))
if len(manually_color_files) > 0:
files_names = [mu.namebase(fname) for fname in manually_color_files]
coloring_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.coloring_files = bpy.props.EnumProperty(items=coloring_items, description="Coloring files")
bpy.context.scene.coloring_files = files_names[0]
vol_color_files = glob.glob(op.join(user_fol, 'coloring', 'volumetric', '*.csv'))
if len(vol_color_files) > 0:
files_names = [mu.namebase(fname) for fname in vol_color_files]
coloring_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.vol_coloring_files = bpy.props.EnumProperty(
items=coloring_items, description="Volumetric Coloring files")
bpy.context.scene.vol_coloring_files = files_names[0]
ColoringMakerPanel.colors = list(set(list(cu.NAMES_TO_HEX.keys())) - set(['black']))
shuffle(ColoringMakerPanel.colors)
ColoringMakerPanel.labels_groups = read_groups_labels(ColoringMakerPanel.colors)
if len(ColoringMakerPanel.labels_groups) > 0:
groups_items = [(gr, gr, '', ind) for ind, gr in enumerate(list(ColoringMakerPanel.labels_groups.keys()))]
bpy.types.Scene.labels_groups = bpy.props.EnumProperty(
items=groups_items, description="Groups")
ColoringMakerPanel.faces_verts = load_faces_verts()
register()
def import_hemis_for_functional_maps(base_path):
mu.change_layer(_addon().BRAIN_EMPTY_LAYER)
layers_array = bpy.context.scene.layers
emptys_names = ['Functional maps', 'Subcortical_meg_activity_map', 'Subcortical_fmri_activity_map']
for name in emptys_names:
create_empty_if_doesnt_exists(name, _addon().BRAIN_EMPTY_LAYER, layers_array, 'Functional maps')
# for ii in range(len(bpy.context.scene.layers)):
# bpy.context.scene.layers[ii] = (ii == brain_layer)
print("importing Hemispheres")
# # for cur_val in bpy.context.scene.layers:
# # print(cur_val)
# print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
now = time.time()
ply_files = glob.glob(op.join(base_path, 'surf', '*.ply'))
N = len(ply_files)
for ind, ply_fname in enumerate(ply_files):
try:
mu.time_to_go(now, ind, N, 10)
bpy.ops.object.select_all(action='DESELECT')
obj_name = mu.namebase(ply_fname).split(sep='.')[0]
surf_name = mu.namebase(ply_fname).split(sep='.')[1]
if surf_name == 'inflated':
obj_name = '{}_{}'.format(surf_name, obj_name)
mu.change_layer(_addon().INFLATED_ACTIVITY_LAYER)
elif surf_name == 'pial':
mu.change_layer(_addon().ACTIVITY_LAYER)
else:
raise Exception('The surface type {} is not supported!'.format(surf_name))
if bpy.data.objects.get(obj_name) is None:
bpy.ops.import_mesh.ply(filepath=op.join(base_path, 'surf', ply_fname))
cur_obj = bpy.context.selected_objects[0]
cur_obj.select = True
bpy.ops.object.shade_smooth()
cur_obj.scale = [0.1] * 3
cur_obj.hide = False
cur_obj.name = obj_name
if surf_name == 'inflated':
cur_obj.active_material = bpy.data.materials['Inflated_Activity_map_mat']
cur_obj.location[0] += 5.5 if obj_name == 'inflated_rh' else -5.5
else:
cur_obj.active_material = bpy.data.materials['Activity_map_mat']
cur_obj.parent = bpy.data.objects["Functional maps"]
cur_obj.hide_select = True
cur_obj.data.vertex_colors.new()
# else:
# print('{} already exists'.format(ply_fname))
except:
print('Error in importing {}'.format(ply_fname))
_addon().create_inflated_curv_coloring()
bpy.ops.object.select_all(action='DESELECT')
def import_rois(base_path):
anatomy_inputs = {'Cortex-rh': op.join(base_path, '{}.pial.rh'.format(bpy.context.scene.atlas)),
'Cortex-lh': op.join(base_path, '{}.pial.lh'.format(bpy.context.scene.atlas)),
'Cortex-inflated-rh': op.join(base_path, '{}.inflated.rh'.format(bpy.context.scene.atlas)),
'Cortex-inflated-lh': op.join(base_path, '{}.inflated.lh'.format(bpy.context.scene.atlas)),
'Subcortical_structures': op.join(base_path, 'subcortical'),
'Cerebellum': op.join(base_path, 'cerebellum')}
brain_layer = _addon().BRAIN_EMPTY_LAYER
bpy.context.scene.layers = [ind == brain_layer for ind in range(len(bpy.context.scene.layers))]
layers_array = bpy.context.scene.layers
emptys_names = ['Brain'] + list(anatomy_inputs.keys()) # ["Brain", "Subcortical_structures", "Cortex-lh", "Cortex-rh", 'Cortex-inflated-rh', 'Cortex-inflated-rh']
for name in emptys_names:
create_empty_if_doesnt_exists(name, brain_layer, layers_array)
bpy.context.scene.layers = [ind == DataMakerPanel.addon.ROIS_LAYER for ind in range(len(bpy.context.scene.layers))]
# todo: check each hemi
inflated_imported = False
for anatomy_name, anatomy_input_base_path in anatomy_inputs.items():
if not op.isdir(anatomy_input_base_path):
print('The anatomy folder {} does not exist'.format(anatomy_input_base_path))
continue
current_mat = bpy.data.materials['unselected_label_Mat_cortex']
if anatomy_name in ['Subcortical_structures', 'Cerebellum']:
current_mat = bpy.data.materials['unselected_label_Mat_subcortical']
print('importing from {}'.format(anatomy_input_base_path))
for ply_fname in glob.glob(op.join(anatomy_input_base_path, '*.ply')):
try:
new_obj_name = mu.namebase(ply_fname)
fol_name = anatomy_input_base_path.split(op.sep)[-1]
surf_name = 'pial' if fol_name == 'subcortical' or len(fol_name.split('.')) == 1 else fol_name.split('.')[-2]
if surf_name == 'inflated':
new_obj_name = '{}_{}'.format(surf_name, new_obj_name)
mu.change_layer(_addon().INFLATED_ROIS_LAYER)
elif surf_name == 'pial':
mu.change_layer(_addon().ROIS_LAYER)
if not bpy.data.objects.get(new_obj_name) is None:
# print('{} was already imported'.format(new_obj_name))
continue
if 'inflated' in new_obj_name:
inflated_imported = True
bpy.ops.object.select_all(action='DESELECT')
# print(ply_fname)
bpy.ops.import_mesh.ply(filepath=op.join(anatomy_input_base_path, ply_fname))
cur_obj = bpy.context.selected_objects[0]
cur_obj.select = True
bpy.ops.object.shade_smooth()
cur_obj.parent = bpy.data.objects[anatomy_name]
cur_obj.scale = [0.1] * 3
cur_obj.active_material = current_mat
cur_obj.hide = False
cur_obj.name = new_obj_name
except:
print('Error in importing {}'.format(ply_fname))
# cur_obj.location[0] += 5.5 if 'rh' in anatomy_name else -5.5
# time.sleep(0.3)
if inflated_imported:
bpy.data.objects['Cortex-inflated-rh'].location[0] += 5.5
bpy.data.objects['Cortex-inflated-lh'].location[0] -= 5.5
bpy.ops.object.select_all(action='DESELECT')
def init(addon):
if not bpy.data.objects.get("full_colorbar", None):
return
ColorbarPanel.addon = addon
colorbar_files = glob.glob(op.join(mu.file_fol(), "color_maps", "*.npy"))
if len(colorbar_files) == 0:
return None
files_names = [mu.namebase(fname).replace("_", "-") for fname in colorbar_files]
colorbar_items = [(c, c, "", ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.colorbar_files = bpy.props.EnumProperty(
items=colorbar_items, description="colormaps files", update=colormap_update
)
bpy.context.scene.colorbar_files = files_names[0]
for space in mu.get_3d_spaces():
if space.lock_object and space.lock_object.name == "full_colorbar":
space.show_only_render = True
register()
ColorbarPanel.init = True
bpy.context.scene.show_cb_in_render = False
mu.select_hierarchy("colorbar_camera", False, False)
if not ColorbarPanel.colorbar_updated:
bpy.context.scene.colorbar_min = -1
bpy.context.scene.colorbar_max = 1
bpy.context.scene.colorbar_title = "MEG"
bpy.context.scene.colorbar_files = "BuPu-YlOrRd"
bpy.context.scene.colorbar_y = 0.18
bpy.context.scene.colorbar_text_y = -1.53
def init(addon):
user_fol = mu.get_user_fol()
clusters_labels_files = glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_*.pkl'))
# old code was saving those files as npy instead of pkl
clusters_labels_files.extend(glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_*.npy')))
# fmri_blobs = glob.glob(op.join(user_fol, 'fmri', 'blobs_*_rh.npy'))
fMRI_clusters_files_exist = len(clusters_labels_files) > 0 # and len(fmri_blobs) > 0
if not fMRI_clusters_files_exist:
return None
fMRIPanel.addon = addon
fMRIPanel.lookup, fMRIPanel.clusters_labels = {}, {}
fMRIPanel.cluster_labels = {}
files_names = [mu.namebase(fname)[len('clusters_labels_'):] for fname in clusters_labels_files]
clusters_labels_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.fmri_clusters_labels_files = bpy.props.EnumProperty(
items=clusters_labels_items, description="fMRI files", update=fmri_clusters_labels_files_update)
bpy.context.scene.fmri_clusters_labels_files = files_names[0]
for file_name, clusters_labels_file in zip(files_names, clusters_labels_files):
fMRIPanel.clusters_labels[file_name] = np.load(clusters_labels_file)
fMRIPanel.clusters_labels[file_name] = support_old_verions(fMRIPanel.clusters_labels[file_name])
fMRIPanel.lookup[file_name] = create_lookup_table(fMRIPanel.clusters_labels[file_name])
bpy.context.scene.fmri_cluster_val_threshold = 3
bpy.context.scene.fmri_cluster_size_threshold = 50
bpy.context.scene.search_closest_cluster_only_in_filtered = True
bpy.context.scene.fmri_what_to_plot = 'blob'
bpy.context.scene.fmri_how_to_sort = 'tval'
update_clusters()
# addon.clear_cortex()
register()
fMRIPanel.init = True
def import_rois(base_path):
anatomy_inputs = {'Cortex-rh': op.join(base_path, '{}.pial.rh'.format(bpy.context.scene.atlas)),
'Cortex-lh': op.join(base_path, '{}.pial.lh'.format(bpy.context.scene.atlas)),
'Subcortical_structures': op.join(base_path, 'subcortical')}
brain_layer = DataMakerPanel.addon.BRAIN_EMPTY_LAYER
bpy.context.scene.layers = [ind == brain_layer for ind in range(len(bpy.context.scene.layers))]
layers_array = bpy.context.scene.layers
emptys_names = ["Brain", "Subcortical_structures", "Cortex-lh", "Cortex-rh"]
for name in emptys_names:
create_empty_if_doesnt_exists(name, brain_layer, layers_array)
bpy.context.scene.layers = [ind == DataMakerPanel.addon.ROIS_LAYER for ind in range(len(bpy.context.scene.layers))]
for anatomy_name, base_path in anatomy_inputs.items():
current_mat = bpy.data.materials['unselected_label_Mat_cortex']
if anatomy_name == 'Subcortical_structures':
current_mat = bpy.data.materials['unselected_label_Mat_subcortical']
for ply_fname in glob.glob(op.join(base_path, '*.ply')):
new_obj_name = mu.namebase(ply_fname)
if not bpy.data.objects.get(new_obj_name) is None:
continue
bpy.ops.object.select_all(action='DESELECT')
print(ply_fname)
bpy.ops.import_mesh.ply(filepath=op.join(base_path, ply_fname))
cur_obj = bpy.context.selected_objects[0]
cur_obj.select = True
bpy.ops.object.shade_smooth()
cur_obj.parent = bpy.data.objects[anatomy_name]
cur_obj.scale = [0.1] * 3
cur_obj.active_material = current_mat
cur_obj.hide = False
cur_obj.name = new_obj_name
# time.sleep(0.3)
bpy.ops.object.select_all(action='DESELECT')
def load_meg_evoked():
evoked_fol = op.join(mu.get_user_fol(), 'meg_evoked_files')
if op.isdir(evoked_fol):
DataMakerPanel.evoked_files = evoked_files = glob.glob(op.join(evoked_fol, '*_labels_data_rh.npz'))
basenames = [mu.namebase(fname).split('_')[0] for fname in evoked_files]
files_items = [(name, name, '', ind) for ind, name in enumerate(basenames)]
bpy.types.Scene.meg_evoked_files = bpy.props.EnumProperty(
items=files_items, description="meg_evoked_files", update=meg_evoked_files_update)
def import_subcorticals(base_path, parent_name='Subcortical'):
empty_layer = DataMakerPanel.addon.BRAIN_EMPTY_LAYER
brain_layer = DataMakerPanel.addon.ACTIVITY_LAYER
bpy.context.scene.layers = [ind == empty_layer for ind in range(len(bpy.context.scene.layers))]
layers_array = bpy.context.scene.layers
emptys_names = ['Functional maps', '{}_meg_activity_map'.format(parent_name), '{}_fmri_activity_map'.format(parent_name)]
for name in emptys_names:
create_empty_if_doesnt_exists(name, empty_layer, layers_array, 'Functional maps')
bpy.context.scene.layers = [ind == brain_layer for ind in range(len(bpy.context.scene.layers))]
print("importing Subcortical structures")
# for cur_val in bpy.context.scene.layers:
# print(cur_val)
# print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
base_paths = [base_path] * 2 # Read the bast_path twice, for meg and fmri
PATH_TYPE_SUB_MEG, PATH_TYPE_SUB_FMRI = range(2)
for path_type, base_path in enumerate(base_paths):
for ply_fname in glob.glob(op.join(base_path, '*.ply')):
try:
obj_name = mu.namebase(ply_fname)
if path_type==PATH_TYPE_SUB_MEG and not bpy.data.objects.get('{}_meg_activity'.format(obj_name)) is None:
continue
if path_type==PATH_TYPE_SUB_FMRI and not bpy.data.objects.get('{}_fmri_activity'.format(obj_name)) is None:
continue
bpy.ops.object.select_all(action='DESELECT')
print(ply_fname)
bpy.ops.import_mesh.ply(filepath=op.join(base_path, ply_fname))
cur_obj = bpy.context.selected_objects[0]
cur_obj.select = True
bpy.ops.object.shade_smooth()
cur_obj.scale = [0.1] * 3
cur_obj.hide = False
cur_obj.name = obj_name
if path_type == PATH_TYPE_SUB_MEG:
cur_obj.name = '{}_meg_activity'.format(obj_name)
curMat = bpy.data.materials.get('{}_mat'.format(cur_obj.name))
if curMat is None:
# todo: Fix the succortical_activity_Mat to succortical_activity_mat
curMat = bpy.data.materials['succortical_activity_Mat'].copy()
curMat.name = '{}_mat'.format(cur_obj.name)
cur_obj.active_material = bpy.data.materials[curMat.name]
cur_obj.parent = bpy.data.objects['{}_meg_activity_map'.format(parent_name)]
elif path_type == PATH_TYPE_SUB_FMRI:
cur_obj.name = '{}_fmri_activity'.format(obj_name)
if 'cerebellum' in cur_obj.name.lower():
cur_obj.active_material = bpy.data.materials['Activity_map_mat']
else:
cur_obj.active_material = bpy.data.materials['subcortical_activity_mat']
cur_obj.parent = bpy.data.objects['{}_fmri_activity_map'.format(parent_name)]
else:
print('import_subcorticals: Wrong path_type! Nothing to do...')
cur_obj.hide_select = True
except:
print('Error in importing {}!'.format(ply_fname))
bpy.ops.object.select_all(action='DESELECT')
def render_all_images():
camera_files = glob.glob(op.join(bpy.path.abspath(bpy.context.scene.output_path), 'camera_*.pkl'))
for camera_file in camera_files:
load_camera(camera_file)
camera_name = mu.namebase(camera_file)
for hemi in mu.HEMIS:
if hemi in camera_name:
RenderingMakerPanel.addon.show_hide_hemi(False, hemi)
RenderingMakerPanel.addon.show_hide_hemi(True, mu.other_hemi(hemi))
render_image('{}_fig'.format(camera_name[len('camera') + 1:]))
def execute(self, context):
stc_fname = self.filepath
user_fol = mu.get_user_fol()
stc_fol = mu.get_fname_folder(stc_fname)
if stc_fol != op.join(user_fol, 'meg'):
other_hemi_stc_fname = op.join(stc_fol, '{}.stc'.format(mu.get_other_hemi_label_name(mu.namebase(stc_fname))))
shutil.copy(stc_fname, op.join(user_fol, 'meg', mu.namesbase_with_ext(stc_fname)))
shutil.copy(other_hemi_stc_fname, op.join(user_fol, 'meg', mu.namesbase_with_ext(other_hemi_stc_fname)))
_addon().init_meg_activity_map()
_, _, label, hemi = mu.get_hemi_delim_and_pos(mu.namebase(stc_fname))
bpy.context.scene.meg_files = label
return {'FINISHED'}
def init_contours_coloring():
user_fol = mu.get_user_fol()
contours_files = glob.glob(op.join(user_fol, 'labels', '*contours*lh.npz'))
if len(contours_files) > 0:
LabelsPanel.contours_coloring_exist = True
LabelsPanel.existing_contoures = files_names = \
[mu.namebase(fname)[:-len('_contours_lh')] for fname in contours_files]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.contours_coloring = bpy.props.EnumProperty(items=items, update=contours_coloring_update,
description='Selects the atlas to plot the labels contour\n\nCurrent atlas')
bpy.context.scene.contours_coloring = files_names[0]
bpy.context.scene.cumulate_contours = False
def init(addon, first=True):
ScriptsPanel.addon = addon
user_fol = mu.get_user_fol()
scripts_files = glob.glob(
op.join(mu.get_mmvt_code_root(), 'src', 'examples', 'scripts', '*.py'))
scripts_files_names = [mu.namebase(f) for f in scripts_files]
scripts_files += [
f for f in glob.glob(
op.join(mu.get_parent_fol(user_fol), 'scripts', '*.py'))
if mu.namebase(f) not in scripts_files_names
]
if len(scripts_files) == 0:
return None
sys.path.append(
op.join(mu.get_mmvt_code_root(), 'src', 'examples', 'scripts'))
sys.path.append(op.join(mu.get_parent_fol(user_fol), 'scripts'))
scripts_files = sorted(
[f for f in scripts_files if check_script(mu.namebase(f))])[::-1]
ScriptsPanel.scripts_names = files_names = [
mu.namebase(fname).replace('_', ' ') for fname in scripts_files
]
scripts_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.scripts_files = bpy.props.EnumProperty(
items=scripts_items,
update=scripts_items_update,
description=
'List of script in the folder:\n..\mmvt_root\mmvtcode\src\examples\scripts\n\nCurrent script'
)
bpy.context.scene.scripts_files = files_names[0]
bpy.context.scene.scripts_overwrite = True
try:
bpy.context.scene.report_use_script = bpy.context.scene.reports_files in ScriptsPanel.scripts_names
except:
pass
# bpy.context.scene.scripts_threshold = 2
# bpy.context.scene.scripts_cb_min = 2
# bpy.context.scene.scripts_cb_max = 6
if first:
register()
ScriptsPanel.init = True
def init(addon):
TempaltePanel.addon = addon
user_fol = mu.get_user_fol()
template_files = glob.glob(op.join(user_fol, 'template', 'template*.npz'))
if len(template_files) == 0:
return None
files_names = [mu.namebase(fname)[len('template'):].replace('_', ' ') for fname in template_files]
template_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.template_files = bpy.props.EnumProperty(
items=template_items, description="tempalte files",update=template_files_update)
bpy.context.scene.template_files = files_names[0]
register()
TempaltePanel.init = True
def render_all_images():
camera_files = glob.glob(
op.join(bpy.path.abspath(bpy.context.scene.output_path),
'camera_*.pkl'))
for camera_file in camera_files:
load_camera(camera_file)
camera_name = mu.namebase(camera_file)
for hemi in mu.HEMIS:
if hemi in camera_name:
RenderingMakerPanel.addon.show_hide_hemi(False, hemi)
RenderingMakerPanel.addon.show_hide_hemi(
True, mu.other_hemi(hemi))
render_image('{}_fig'.format(camera_name[len('camera') + 1:]))
def modal(self, context, event):
if event.type == 'TIMER':
output_file = op.join(bpy.context.scene.output_path, 'combine_images_cmd.txt')
if op.isfile(output_file):
movies = glob.glob(op.join(bpy.context.scene.output_path, '**', '*.mp4'), recursive=True)
if len(movies) > 0:
os.rename(movies[0], op.join(mu.get_user_fol(), 'figures', '{}.mp4'.format(
mu.namebase(bpy.context.scene.output_path))))
temp_fol = op.join(bpy.context.scene.output_path, 'new_images')
if op.isdir(temp_fol):
shutil.rmtree(temp_fol)
self.cancel(context)
return {'PASS_THROUGH'}
def init(addon):
DataMakerPanel.addon = addon
bpy.context.scene.electrodes_radius = 0.15
load_meg_evoked()
_meg_evoked_files_update()
electrodes_positions_files = glob.glob(op.join(mu.get_user_fol(), 'electrodes', 'electrodes*positions*.npz'))
if len(electrodes_positions_files) > 0:
files_names = [mu.namebase(fname) for fname in electrodes_positions_files]
positions_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_positions_files = bpy.props.EnumProperty(
items=positions_items,description="Electrodes positions")
bpy.context.scene.electrodes_positions_files = files_names[0]
register()
def update_camera_files():
camera_files = glob.glob(op.join(mu.get_user_fol(), 'camera', '*camera*.pkl'))
if len(camera_files) > 0:
files_names = [mu.namebase(fname) for fname in camera_files]
if _addon().is_inflated():
files_names = [name for name in files_names if 'inf' in name]
files_names.append('camera')
else:
files_names = [name for name in files_names if 'inf' not in name]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.camera_files = bpy.props.EnumProperty(
items=items, description="electrodes sources", update=camera_files_update)
bpy.context.scene.camera_files = 'camera'
def play_panel_draw(context, layout):
play_type = bpy.context.scene.play_type
if play_type in ['meg', 'meg_elecs', 'meg_elecs_coh']:
layout.prop(context.scene, "meg_threshold", text="MEG threshold")
if play_type in ['elecs', 'meg_elecs', 'elecs_act_coh', 'meg_elecs_coh']:
layout.prop(context.scene, "electrodes_threshold", text="Electrodes threshold")
if play_type in ['elecs_coh', 'elecs_act_coh', 'meg_elecs_coh']:
layout.prop(context.scene, "connectivity_threshold", text="Conectivity threshold")
row = layout.row(align=0)
row.prop(context.scene, "play_from", text="From")
row.operator(GrabFromPlay.bl_idname, text="", icon='BORDERMOVE')
row.prop(context.scene, "play_to", text="To")
row.operator(GrabToPlay.bl_idname, text="", icon='BORDERMOVE')
row = layout.row(align=0)
row.prop(context.scene, "play_dt", text="dt")
row.prop(context.scene, "play_time_step", text="time step")
layout.prop(context.scene, "play_type", text="")
row = layout.row(align=True)
# row.operator(Play.bl_idname, text="", icon='PLAY' if not PlayPanel.is_playing else 'PAUSE')
row.operator(PrevKeyFrame.bl_idname, text="", icon='PREV_KEYFRAME')
row.operator(Reverse.bl_idname, text="", icon='PLAY_REVERSE')
row.operator(Pause.bl_idname, text="", icon='PAUSE')
row.operator(Play.bl_idname, text="", icon='PLAY')
row.operator(NextKeyFrame.bl_idname, text="", icon='NEXT_KEYFRAME')
layout.prop(context.scene, 'render_movie', text="Render to a movie")
layout.prop(context.scene, 'save_images', text="Save images")
layout.prop(context.scene, 'rotate_brain_while_playing', text='Rotate the brain while playing')
layout.operator(ExportGraph.bl_idname, text="Export graph", icon='SNAP_NORMAL')
files_with_numbers = sum([len(re.findall('\d+', mu.namebase(f))) for f in
glob.glob(op.join(bpy.context.scene.output_path, '*.png'))])
if files_with_numbers > 0:
if not CreateMovie.running:
layout.operator(CreateMovie.bl_idname, text="Create Movie", icon='RENDER_ANIMATION')
layout.label(text='From images in {}'.format(mu.namebase(bpy.context.scene.output_path)))
layout.prop(context.scene, 'frames_num', text="frames per second")
else:
layout.label(text='Rendering the movie...')
def init_hnn_files():
hnn_folder = bpy.path.abspath(bpy.context.scene.hnn_folder)
HNNPanel.data_files_names = [
mu.namebase(fname)
for fname in glob.glob(op.join(hnn_folder, 'data', '*.txt'))
]
if len(HNNPanel.data_files_names) > 0:
hnn_items = [(c, c, '', ind)
for ind, c in enumerate(HNNPanel.data_files_names)]
bpy.types.Scene.hnn_data_files = bpy.props.EnumProperty(
items=hnn_items, description="data files")
bpy.context.scene.hnn_data_files = HNNPanel.data_files_names[0]
HNNPanel.params_files_names = [
mu.namebase(fname)
for fname in glob.glob(op.join(hnn_folder, 'param', '*.param'))
]
if len(HNNPanel.params_files_names) > 0:
hnn_items = [(c, c, '', ind)
for ind, c in enumerate(HNNPanel.params_files_names)]
bpy.types.Scene.hnn_param_files = bpy.props.EnumProperty(
items=hnn_items, description="param files")
bpy.context.scene.hnn_param_files = HNNPanel.params_files_names[0]
def load_meg_evoked():
evoked_fol = op.join(mu.get_user_fol(), 'meg_evoked_files')
if op.isdir(evoked_fol):
DataMakerPanel.evoked_files = evoked_files = glob.glob(
op.join(evoked_fol, '*_labels_data_rh.npz'))
basenames = [
mu.namebase(fname).split('_')[0] for fname in evoked_files
]
files_items = [(name, name, '', ind)
for ind, name in enumerate(basenames)]
bpy.types.Scene.meg_evoked_files = bpy.props.EnumProperty(
items=files_items,
description="meg_evoked_files",
update=meg_evoked_files_update)
def update_camera_files():
if not RenderingMakerPanel.init:
return
camera_files = glob.glob(op.join(mu.get_user_fol(), 'camera', '*camera*.pkl'))
if len(camera_files) > 0:
files_names = [mu.namebase(fname) for fname in camera_files]
if _addon().is_inflated():
files_names = [name for name in files_names if 'inf' in name]
files_names.append('camera')
else:
files_names = [name for name in files_names if 'inf' not in name]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.camera_files = bpy.props.EnumProperty(
items=items, description="electrodes sources", update=camera_files_update)
bpy.context.scene.camera_files = 'camera'
def save_image(image_type='image', view_selected=None, index=-1, zoom_val=0, add_index_to_name=True,
add_colorbar=None, cb_ticks_num=None, cb_ticks_font_size=None):
if add_colorbar is None:
add_colorbar = bpy.context.scene.save_views_with_cb
if cb_ticks_num is None:
cb_ticks_num = bpy.context.scene.cb_ticks_num
if cb_ticks_font_size is None:
cb_ticks_font_size = bpy.context.scene.cb_ticks_font_size
if view_selected is None:
view_selected = bpy.context.scene.save_selected_view
if index == -1:
fol = bpy.path.abspath(bpy.context.scene.output_path)
files = [mu.namebase(f) for f in glob.glob(op.join(fol, '{}*.{}'.format(image_type, get_figure_format())))]
files_with_numbers = sum([len(re.findall('\d+', f)) for f in files])
if files_with_numbers > 0:
index = max([int(re.findall('\d+', f)[0]) for f in files]) + 1 if len(files) > 0 else 0
else:
index = 0
switch_to_object_mode()
index = bpy.context.scene.frame_current if index == -1 else index
mu.show_only_render(True)
fol = bpy.path.abspath(bpy.context.scene.output_path)
if add_index_to_name:
image_name = op.join(fol, '{}_{}.{}'.format(image_type, index, get_figure_format()))
else:
image_name = op.join(fol, '{}.{}'.format(image_type, get_figure_format()))
print('Image saved in {}'.format(image_name))
bpy.context.scene.render.filepath = image_name
view3d_context = mu.get_view3d_context()
if view_selected:
_addon().view_all()
# todo: Understand when zoom(-1) is needed
# if not _addon().subcorticals_are_hiding():
# _addon().zoom(-1)
# mu.select_all_brain(True)
# bpy.ops.view3d.camera_to_view_selected(view3d_context)
# mu.view_selected()
if zoom_val != 0:
_addon().zoom(zoom_val)
# _addon().zoom(1)
# mu.center_view()
bpy.ops.render.opengl(view3d_context, write_still=True)
if add_colorbar:
add_colorbar_to_image(image_name, cb_ticks_num, cb_ticks_font_size)
# if view_selected:
# _addon().zoom(1)
return image_name
def init_labels_data_files():
user_fol = mu.get_user_fol()
mu.make_dir(op.join(user_fol, 'labels', 'labels_data'))
LabelsPanel.labels_data_files = labels_data_files = \
glob.glob(op.join(user_fol, 'labels', 'labels_data', '*.npz')) + \
glob.glob(op.join(user_fol, 'labels', 'labels_data', '*.mat'))
if len(labels_data_files) > 0:
files_names = [
mu.namebase(fname).replace('_', ' ') for fname in labels_data_files
]
labels_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.labels_data_files = bpy.props.EnumProperty(
items=labels_items,
description="label files",
update=labels_data_files_update)
bpy.context.scene.labels_data_files = files_names[0]
def init(addon):
user_fol = mu.get_user_fol()
stim_files = glob.glob(op.join(user_fol, 'electrodes', 'stim_electrodes_*.npz'))
stim_files = [sf for sf in stim_files if 'positions' not in sf]
# stim_positions_files = glob.glob(op.join(user_fol, 'electrodes', 'stim_electrodes*positions.npz'))
if len(stim_files) == 0:
return None
StimPanel.addon = addon
files_names = [mu.namebase(fname)[len('stim_electrodes_'):].replace('_', ' ') for fname in stim_files]
stim_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.stim_files = bpy.props.EnumProperty(
items=stim_items, description='stim files', update=stim_files_update)
bpy.context.scene.stim_files = files_names[0]
load_conditions()
register()
StimPanel.init = True
def init(addon):
user_fol = mu.get_user_fol()
stim_files = glob.glob(op.join(user_fol, 'electrodes', 'stim_electrodes_*.npz'))
stim_files = [sf for sf in stim_files if 'positions' not in sf]
# stim_positions_files = glob.glob(op.join(user_fol, 'electrodes', 'stim_electrodes*positions.npz'))
if len(stim_files) == 0:
return None
StimPanel.addon = addon
files_names = [mu.namebase(fname)[len('stim_electrodes_'):].replace('_', ' ') for fname in stim_files]
stim_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.stim_files = bpy.props.EnumProperty(
items=stim_items, description='stim files', update=stim_files_update)
bpy.context.scene.stim_files = files_names[0]
load_conditions()
register()
StimPanel.init = True
def init(addon):
if not bpy.data.objects.get('full_colorbar', None):
print("No full_colorbar object, Can't load the colorbar panel")
return
ColorbarPanel.addon = addon
colorbar_files_fol = mu.make_dir(op.join(mu.get_parent_fol(mu.get_user_fol()), 'color_maps'))
colorbar_files_code_fol = op.join(mu.get_resources_dir(), 'color_maps')
colorbar_files_template = op.join(colorbar_files_fol, '*.npy')
colorbar_files_code_template = op.join(colorbar_files_code_fol, '*.npy')
# colorbar_files_template = op.join(mu.file_fol(), 'color_maps', '*.npy')
colorbar_files = glob.glob(colorbar_files_template)
colorbar_code_files = glob.glob(colorbar_files_code_template)
extra_files = list(set([mu.namebase_with_ext(f) for f in colorbar_code_files]) -
set([mu.namebase_with_ext(f) for f in colorbar_files]))
for extra_file in extra_files:
print('Coping missing cb file: {}'.format(mu.namebase_with_ext(extra_file)))
shutil.copyfile(op.join(colorbar_files_code_fol, extra_file),
op.join(colorbar_files_fol, mu.namebase_with_ext(extra_file)))
if len(colorbar_files) == 0:
print("No colorbar files ({}), Can't load the colorbar panel".format(colorbar_files_template))
return None
colorbar_files = glob.glob(colorbar_files_template)
files_names = [mu.namebase(fname) for fname in colorbar_files] # .replace('_', '-')
ColorbarPanel.maps_names = files_names
colorbar_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.colorbar_files = bpy.props.EnumProperty(
items=colorbar_items,update=colormap_update, description='Selects the colorbar color palette.\n\nCurrent palette')
if not colorbar_values_are_locked():
bpy.context.scene.colorbar_files = files_names[0]
else:
load_colormap()
for space in mu.get_3d_spaces():
if space.lock_object and space.lock_object.name == 'full_colorbar':
space.show_only_render = True
register()
ColorbarPanel.init = True
bpy.context.scene.show_cb_in_render = False
mu.select_hierarchy('colorbar_camera', False, False)
if not ColorbarPanel.colorbar_updated and not colorbar_values_are_locked():
ColorbarPanel.should_not_lock_values = True
# bpy.context.scene.colorbar_min = -1
# bpy.context.scene.colorbar_max = 1
# bpy.context.scene.colorbar_title = ' MEG'
bpy.context.scene.colorbar_y = 0.18
bpy.context.scene.colorbar_text_y = -1.53
bpy.context.scene.colorbar_prec = 2
ColorbarPanel.should_not_lock_values = False
def init(addon):
DataMakerPanel.addon = addon
bpy.context.scene.electrodes_radius = 0.15
load_meg_evoked()
_meg_evoked_files_update()
electrodes_positions_files = glob.glob(
op.join(mu.get_user_fol(), 'electrodes', 'electrodes*positions*.npz'))
if len(electrodes_positions_files) > 0:
files_names = [
mu.namebase(fname) for fname in electrodes_positions_files
]
positions_items = [(c, c, '', ind)
for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_positions_files = bpy.props.EnumProperty(
items=positions_items, description="Electrodes positions")
bpy.context.scene.electrodes_positions_files = files_names[0]
register()
def init_labels_data_files():
user_fol = mu.get_user_fol()
mu.make_dir(op.join(user_fol, 'labels', 'labels_data'))
LabelsPanel.labels_data_files = labels_data_files = \
glob.glob(op.join(user_fol, 'labels', 'labels_data', '*.npz')) + \
glob.glob(op.join(user_fol, 'labels', 'labels_data', '*.mat'))
try:
if len(labels_data_files) > 0:
files_names = [mu.namebase(fname).replace('_', ' ') for fname in labels_data_files]
labels_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.labels_data_files = bpy.props.EnumProperty(
items=labels_items, update=labels_data_files_update,
description='Selects labels file from the subject’s labels folder:'
'\n../mmvt_root/mmvt_blend/colin27/labels/labels_data\n\nCurrent file')
bpy.context.scene.labels_data_files = files_names[0]
except:
print('init_labels_data_files: Error!')
def init_electrodes_labeling(addon):
#todo: this panel should work also without labeling file
labling_files = find_elecrode_labeling_files()
if len(labling_files) > 0:
files_names = [
mu.namebase(fname) for fname in labling_files if mu.load(fname)
]
labeling_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_labeling_files = bpy.props.EnumProperty(
items=labeling_items,
description='Labeling files',
update=electrodes_labeling_files_update)
bpy.context.scene.electrodes_labeling_files = files_names[0]
# ElecsPanel.electrodes_locs = mu.load(labling_files[0])
# ElecsPanel.lookup = create_lookup_table(ElecsPanel.electrodes_locs, ElecsPanel.electrodes)
ElecsPanel.faces_verts = addon.get_faces_verts()
return len(labling_files) > 0
def init(addon):
if not bpy.data.objects.get('full_colorbar', None):
print("No full_colorbar object, Can't load the colorbar panel")
return
ColorbarPanel.addon = addon
colorbar_files_template = op.join(mu.get_resources_dir(), 'color_maps',
'*.npy')
# colorbar_files_template = op.join(mu.file_fol(), 'color_maps', '*.npy')
colorbar_files = glob.glob(colorbar_files_template)
if len(colorbar_files) == 0:
print("No colorbar files ({}), Can't load the colorbar panel".format(
colorbar_files_template))
return None
files_names = [
mu.namebase(fname).replace('_', '-') for fname in colorbar_files
]
ColorbarPanel.maps_names = files_names
colorbar_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.colorbar_files = bpy.props.EnumProperty(
items=colorbar_items,
description="colormaps files",
update=colormap_update)
if not colorbar_values_are_locked():
bpy.context.scene.colorbar_files = files_names[0]
else:
load_colormap()
for space in mu.get_3d_spaces():
if space.lock_object and space.lock_object.name == 'full_colorbar':
space.show_only_render = True
register()
ColorbarPanel.init = True
bpy.context.scene.show_cb_in_render = False
mu.select_hierarchy('colorbar_camera', False, False)
if not ColorbarPanel.colorbar_updated and not colorbar_values_are_locked():
# bpy.context.scene.colorbar_min = -1
# bpy.context.scene.colorbar_max = 1
# bpy.context.scene.colorbar_title = ' MEG'
bpy.context.scene.colorbar_y = 0.18
bpy.context.scene.colorbar_text_y = -1.53
bpy.context.scene.colorbar_prec = 2
if not colorbar_values_are_locked():
if 'fMRI' in bpy.context.scene.colorbar_title:
bpy.context.scene.colorbar_files = 'PuBu-RdOrYl'
else:
bpy.context.scene.colorbar_files = 'BuPu-YlOrRd'
def init(addon):
TemplatePanel.addon = addon
user_fol = mu.get_user_fol()
template_files = glob.glob(op.join(user_fol, 'template', 'template*.npz'))
if len(template_files) == 0:
return None
files_names = [
mu.namebase(fname)[len('template'):].replace('_', ' ')
for fname in template_files
]
template_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.template_files = bpy.props.EnumProperty(
items=template_items,
description="template files",
update=template_files_update)
bpy.context.scene.template_files = files_names[0]
register()
TemplatePanel.init = True
def load_connections_file(connectivity_files=''):
if connectivity_files == '':
connectivity_files = bpy.context.scene.connectivity_files
d, vertices, vertices_lookup = None, None, None
conn_file_name = connectivity_files.replace(' ', '_')
connectivity_file = op.join(mu.get_user_fol(), 'connectivity',
'{}.npz'.format(conn_file_name))
vertices_file = op.join(
mu.get_user_fol(), 'connectivity',
'{}_vertices.pkl'.format(conn_file_name.replace('_static', '')))
if op.isfile(connectivity_file):
print('loading connectivity: {}'.format(connectivity_file))
d = mu.Bag(np.load(connectivity_file))
d.labels = [l.astype(str) for l in d.labels]
d.hemis = [l.astype(str) for l in d.hemis]
d.con_names = np.array([l.astype(str) for l in d.con_names],
dtype=np.str)
d.conditions = [l.astype(str) for l in d.conditions]
if d.con_values.ndim == 2:
d.con_values = d.con_values[:, :, np.newaxis]
conditions_items = [(cond, cond, '', cond_ind)
for cond_ind, cond in enumerate(d.conditions)]
if len(d.conditions) > 1:
diff_cond = '{}-{} difference'.format(d.conditions[0],
d.conditions[1])
conditions_items.append(
(diff_cond, diff_cond, '', len(d.conditions)))
bpy.types.Scene.conditions = bpy.props.EnumProperty(
items=conditions_items, description="Conditions")
# bpy.context.scene.connections_max, bpy.context.scene.connections_min = d['data_max'], d['data_min']
else:
print('No connections file! {}'.format(connectivity_file))
if op.isfile(vertices_file):
vertices, vertices_lookup = mu.load(vertices_file)
else:
name_parts = mu.namebase(vertices_file).split('_')
vertices_files = glob.glob(
op.join(mu.get_parent_fol(vertices_file),
'{}*_{}.pkl'.format(name_parts[0], name_parts[-1])))
if len(vertices_files) == 1:
vertices, vertices_lookup = mu.load(vertices_files[0])
else:
print('No vertices file! ({})'.format(vertices_file))
ConnectionsPanel.d, ConnectionsPanel.vertices, ConnectionsPanel.vertices_lookup = d, vertices, vertices_lookup
def init_electrodes_labeling(addon):
#todo: this panel should work also without labeling file
labeling_fname = '{}_{}_electrodes_cigar_r_*_l_*{}*.pkl'.format(mu.get_user(), bpy.context.scene.atlas,
'_bipolar' if bpy.context.scene.bipolar else '')
labling_files = glob.glob(op.join(mu.get_user_fol(), 'electrodes', labeling_fname))
if not bpy.context.scene.bipolar:
labling_files = [fname for fname in labling_files if 'bipolar' not in fname]
if len(labling_files) == 0:
print("!!! Can't find any electrodes labeling file in {} !!!".format(
op.join(mu.get_user_fol(), 'electrodes', labeling_fname)))
else:
files_names = [mu.namebase(fname) for fname in labling_files if mu.load(fname)]
labeling_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_labeling_files = bpy.props.EnumProperty(
items=labeling_items, description='Labeling files', update=electrodes_labeling_files_update)
bpy.context.scene.electrodes_labeling_files = files_names[0]
# ElecsPanel.electrodes_locs = mu.load(labling_files[0])
# ElecsPanel.lookup = create_lookup_table(ElecsPanel.electrodes_locs, ElecsPanel.electrodes)
ElecsPanel.faces_verts = addon.get_faces_verts()
def init(addon):
user_fol = mu.get_user_fol()
# clusters_labels_files = glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_*.pkl'))
# old code was saving those files as npy instead of pkl
# clusters_labels_files.extend(glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_*.npy')))
# fmri_blobs = glob.glob(op.join(user_fol, 'fmri', 'blobs_*_rh.npy'))
fMRIPanel.addon = addon
fMRIPanel.lookup, fMRIPanel.clusters_labels = {}, {}
fMRIPanel.cluster_labels = {}
files_names, clusters_labels_files = get_clusters_files(user_fol)
fMRIPanel.fMRI_clusters_files_exist = len(files_names) > 0 # and len(fmri_blobs) > 0
if not fMRIPanel.fMRI_clusters_files_exist:
return None
# files_names = [mu.namebase(fname)[len('clusters_labels_'):] for fname in clusters_labels_files]
fMRIPanel.clusters_labels_file_names = files_names
clusters_labels_items = [(c, c, '', ind) for ind, c in enumerate(list(set(files_names)))]
bpy.types.Scene.fmri_clusters_labels_files = bpy.props.EnumProperty(
items=clusters_labels_items, description="fMRI files", update=fmri_clusters_labels_files_update)
bpy.context.scene.fmri_clusters_labels_files = files_names[0]
for file_name, clusters_labels_file in zip(files_names, clusters_labels_files):
# Check if the constrast files exist
if mu.hemi_files_exists(op.join(user_fol, 'fmri', 'fmri_{}_{}.npy'.format(file_name, '{hemi}'))):
perc = mu.namebase(clusters_labels_file).split('_')[-1]
key = '{}_{}'.format(file_name, perc)
fMRIPanel.clusters_labels[key] = np.load(clusters_labels_file)
# fMRIPanel.clusters_labels[key] = support_old_verions(fMRIPanel.clusters_labels[file_name])
fMRIPanel.lookup[key] = create_lookup_table(fMRIPanel.clusters_labels[key])
# bpy.context.scene.fmri_cluster_val_threshold = 2
# bpy.context.scene.fmri_cluster_size_threshold = 20
bpy.context.scene.search_closest_cluster_only_in_filtered = True
bpy.context.scene.fmri_what_to_plot = 'blob'
bpy.context.scene.fmri_how_to_sort = 'tval'
update_clusters()
fMRIPanel.blobs_activity, _ = calc_blobs_activity(
fMRIPanel.constrast, fMRIPanel.clusters_labels_filtered, fMRIPanel.colors_in_hemis)
bpy.context.scene.plot_fmri_cluster_per_click = False
fMRIPanel.dont_show_clusters_info = True
# addon.clear_cortex()
register()
fMRIPanel.init = True
def load_fmri_volume(nii_fname):
import importlib
mu.add_mmvt_code_root_to_path()
from src.preproc import fMRI
importlib.reload(fMRI)
fmri_file_template = mu.namebase(nii_fname)
subject = mu.get_user()
flag, fmri_contrast_file_template = fMRI.project_volume_to_surface(
subject, fmri_file_template, remote_fmri_dir=mu.get_parent_fol(nii_fname))
if not flag:
print('load_fmri_volume: Error in fMRI.project_volume_to_surface!')
return False
flag = fMRI.calc_fmri_min_max(subject, fmri_contrast_file_template)
if not flag:
print('load_fmri_volume: Error in fMRI.calc_fmri_min_max!')
return False
# _addon().coloring.init(_addon(), register=False)
fMRI_file_name = fmri_contrast_file_template.replace('fmri_', '')
_addon().coloring.plot_fmri_file(fMRI_file_name)
return True
def load_camera(camera_fname=''):
if camera_fname == '':
camera_fname = op.join(mu.get_user_fol(), 'camera', '{}.pkl'.format(bpy.context.scene.camera_files))
if op.isfile(camera_fname):
camera_name = mu.namebase(camera_fname)
for hemi in mu.HEMIS:
if hemi in camera_name:
_addon().show_hide_hemi(False, hemi)
_addon().show_hide_hemi(True, mu.other_hemi(hemi))
X_rotation, Y_rotation, Z_rotation, X_location, Y_location, Z_location = mu.load(camera_fname)
RenderFigure.update_camera = False
bpy.context.scene.X_rotation = X_rotation
bpy.context.scene.Y_rotation = Y_rotation
bpy.context.scene.Z_rotation = Z_rotation
bpy.context.scene.X_location = X_location
bpy.context.scene.Y_location = Y_location
bpy.context.scene.Z_location = Z_location
RenderFigure.update_camera = True
update_camera()
else:
print('No camera file was found in {}!'.format(camera_fname))
def execute(self, context):
_addon().clear_colors()
self.fmri_file_template, hemi, other_hemi = load_surf_files(
self.filepath[:-2])
if hemi == '':
bpy.context.scene.nii_label_prompt = "Can't determine the hemi!"
return {'RUNNING_MODAL'}
self.fmri_npy_template_fname = op.join(
mu.get_user_fol(), 'fmri',
'fmri_{}.npy'.format(mu.namebase(self.fmri_file_template)))
print('Waiting for both hemi files to be created ({})'.format(
self.fmri_npy_template_fname))
if self.fmri_file_template != '':
bpy.context.scene.nii_label_output = 'Loading nii file...'
ChooseNiftiiFile.running = True
context.window_manager.modal_handler_add(self)
self._timer = context.window_manager.event_timer_add(
0.1, context.window)
else:
bpy.context.scene.nii_label_prompt = 'Please select the nii file for the {} hemi'.format(
'right' if hemi == 'lh' else 'left')
return {'RUNNING_MODAL'}
def render_image(image_name='', image_fol='', quality=20, use_square_samples=None, render_background=None,
camera_fname='', hide_subcorticals=False, overwrite=True):
bpy.context.scene.render.resolution_percentage = bpy.context.scene.quality if quality == 0 else quality
bpy.context.scene.cycles.use_square_samples = bpy.context.scene.smooth_figure if use_square_samples is None \
else use_square_samples
if not render_background is None:
bpy.context.scene.render_background = render_background
if camera_fname == '':
camera_fname = op.join(mu.get_user_fol(), 'camera', '{}.pkl'.format(bpy.context.scene.camera_files))
camera_fnames = [camera_fname] if isinstance(camera_fname, str) else camera_fname
images_names = [image_name] if isinstance(image_name, str) else image_name
for camera_fname in camera_fnames:
if image_name == '':
cur_frame = bpy.context.scene.frame_current
camera_name = mu.namebase(camera_fname)
images_names.append('{}_{}'.format(camera_name[len('camera') + 1:], cur_frame))
image_fol = bpy.path.abspath(bpy.context.scene.output_path) if image_fol == '' else image_fol
print('Image quality: {}'.format(bpy.context.scene.render.resolution_percentage))
print("Rendering...")
if not bpy.context.scene.render_background:
for image_name, camera_fname in zip(images_names, camera_fnames):
print('file name: {}'.format(op.join(image_fol, image_name)))
bpy.context.scene.render.filepath = op.join(image_fol, image_name)
if overwrite or len(glob.glob('{}.*'.format(bpy.context.scene.render.filepath))) == 0:
_addon().load_camera(camera_fname)
_addon().change_to_rendered_brain()
if hide_subcorticals:
_addon().show_hide_sub_corticals()
bpy.ops.render.render(write_still=True)
print("Finished")
else:
camera_fnames = ','.join(camera_fnames)
images_names = ','.join(images_names)
render_func = partial(render_in_background, image_name=images_names, image_fol=image_fol,
camera_fname=camera_fnames, hide_subcorticals=hide_subcorticals, overwrite=overwrite)
put_func_in_queue(render_func)
if queue_len() == 1:
run_func_in_queue()
def init_electrodes_labeling(addon):
ela_code_fol = op.join(mu.get_parent_fol(mu.get_mmvt_code_root()), 'electrodes_rois')
ElecsPanel.ela_code_exist = op.isfile(op.join(ela_code_fol, 'find_rois', 'find_rois.py'))
ElecsPanel.labling_files = labling_files = find_elecrode_labeling_files()
if len(labling_files) > 0:
files_names = [mu.namebase(fname) for fname in labling_files if mu.load(fname)]
labeling_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_labeling_files = bpy.props.EnumProperty(
items=labeling_items, update=electrodes_labeling_files_update,
description='List of electrodes labeling type.\n\nCurrent')
bpy.context.scene.electrodes_labeling_files = files_names[0]
# ElecsPanel.electrodes_locs = mu.load(labling_files[0])
# ElecsPanel.lookup = create_lookup_table(ElecsPanel.electrodes_locs, ElecsPanel.electrodes)
ElecsPanel.faces_verts = addon.get_faces_verts()
atlases = mu.get_annot_files()
if len(atlases) > 0:
ElecsPanel.atlases_exist = True
atlases_items = [(c, c, '', ind) for ind, c in enumerate(atlases)]
bpy.types.Scene.ela_atlas = bpy.props.EnumProperty(items=atlases_items, description='atlases')
bpy.context.scene.ela_atlas = atlases[0]
bpy.context.scene.ela_bipolar = bpy.context.scene.bipolar
return len(labling_files) > 0
def import_hemis_for_functional_maps(current_root_path):
brain_layer = DataMakerPanel.addon.BRAIN_EMPTY_LAYER
bpy.context.scene.layers = [ind == brain_layer for ind in range(len(bpy.context.scene.layers))]
layers_array = bpy.context.scene.layers
emptys_names = ['Functional maps', 'Subcortical_meg_activity_map', 'Subcortical_fmri_activity_map']
for name in emptys_names:
create_empty_if_doesnt_exists(name, brain_layer, layers_array, 'Functional maps')
brain_layer = DataMakerPanel.addon.ACTIVITY_LAYER
bpy.context.scene.layers = [ind == brain_layer for ind in range(len(bpy.context.scene.layers))]
# for ii in range(len(bpy.context.scene.layers)):
# bpy.context.scene.layers[ii] = (ii == brain_layer)
print("importing Hemispheres")
# # for cur_val in bpy.context.scene.layers:
# # print(cur_val)
# print("~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
base_path = current_root_path
for ply_fname in glob.glob(op.join(base_path, '*.ply')):
bpy.ops.object.select_all(action='DESELECT')
print(ply_fname)
obj_name = mu.namebase(ply_fname).split(sep='.')[0]
if bpy.data.objects.get(obj_name) is None:
bpy.ops.import_mesh.ply(filepath=op.join(base_path, ply_fname))
cur_obj = bpy.context.selected_objects[0]
cur_obj.select = True
bpy.ops.object.shade_smooth()
cur_obj.scale = [0.1] * 3
cur_obj.hide = False
cur_obj.name = obj_name
cur_obj.active_material = bpy.data.materials['Activity_map_mat']
cur_obj.parent = bpy.data.objects["Functional maps"]
cur_obj.hide_select = True
cur_obj.data.vertex_colors.new()
print('did hide_select')
bpy.ops.object.select_all(action='DESELECT')
def load_camera(camera_fname=''):
if camera_fname == '':
camera_fname = op.join(mu.get_user_fol(), 'camera', '{}.pkl'.format(bpy.context.scene.camera_files))
if op.isfile(camera_fname):
camera_name = mu.namebase(camera_fname)
for hemi in mu.HEMIS:
if hemi in camera_name:
_addon().show_hide_hemi(False, hemi)
_addon().show_hide_hemi(True, mu.other_hemi(hemi))
X_rotation, Y_rotation, Z_rotation, X_location, Y_location, Z_location = mu.load(camera_fname)
RenderFigure.update_camera = False
bpy.context.scene.X_rotation = X_rotation
bpy.context.scene.Y_rotation = Y_rotation
bpy.context.scene.Z_rotation = Z_rotation
bpy.context.scene.X_location = X_location
bpy.context.scene.Y_location = Y_location
bpy.context.scene.Z_location = Z_location
# print('Camera loaded: rotation: {},{},{} locatioin: {},{},{}'.format(
# X_rotation, Y_rotation, Z_rotation, X_location, Y_location, Z_location))
# print('Camera loaded: {}'.format(camera_fname))
RenderFigure.update_camera = True
update_camera()
else:
pass
def get_parcs_files(user_fol, fmri_file_name):
fMRIPanel.clusters_labels_files = clusters_labels_files = \
glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_{}*.pkl'.format(fmri_file_name)))
return list(set([mu.namebase(fname).split('_')[-1] for fname in clusters_labels_files]))
def init(addon):
try:
t1_trans_fname = op.join(mu.get_user_fol(), 't1_trans.npz')
if not op.isfile(t1_trans_fname):
# backward compatibility
t1_trans_fname = op.join(mu.get_user_fol(), 'orig_trans.npz')
t2_trans_fname = op.join(mu.get_user_fol(), 't2_trans.npz')
ct_trans_fname = op.join(mu.get_user_fol(), 'ct', 'ct_trans.npz')
volumes = glob.glob(op.join(mu.get_user_fol(), 'freeview', '*+aseg.npy'))
luts = glob.glob(op.join(mu.get_user_fol(), 'freeview', '*ColorLUT.npz'))
if op.isfile(t1_trans_fname):
WhereAmIPanel.subject_t1_trans = mu.Bag(np.load(t1_trans_fname))
if op.isfile(t2_trans_fname):
WhereAmIPanel.subject_t2_trans = mu.Bag(np.load(t2_trans_fname))
if op.isfile(ct_trans_fname):
WhereAmIPanel.subject_ct_trans = mu.Bag(np.load(ct_trans_fname))
for atlas_vol_fname, atlas_vol_lut_fname in zip(volumes, luts):
atlas = mu.namebase(atlas_vol_fname)[:-len('+aseg')]
WhereAmIPanel.vol_atlas[atlas] = np.load(atlas_vol_fname)
WhereAmIPanel.vol_atlas_lut[atlas] = np.load(atlas_vol_lut_fname)
try:
subjects_dir = mu.get_link_dir(mu.get_links_dir(), 'subjects')
annot_files = [mu.namebase(fname)[3:] for fname in glob.glob(
op.join(subjects_dir, mu.get_user(), 'label', 'rh.*.annot'))]
annot_files += [mu.namebase(fname)[3:] for fname in glob.glob(
op.join(mu.get_user_fol(), 'labels', 'rh.*.annot'))]
WhereAmIPanel.annot_files = annot_files = list(set(annot_files))
if len(annot_files) > 0:
items = [(c, c, '', ind) for ind, c in enumerate(annot_files)]
bpy.types.Scene.subject_annot_files = bpy.props.EnumProperty(
items=items, update=subject_annot_files_update, description='List of different atlases.\n\nCurrent atlas')
ind = mu.index_in_list(bpy.context.scene.atlas, annot_files, 0)
bpy.context.scene.subject_annot_files = annot_files[ind]
else:
bpy.types.Scene.subject_annot_files = bpy.props.EnumProperty(items=[])
# bpy.context.scene.subject_annot_files = ''
except:
bpy.types.Scene.subject_annot_files = bpy.props.EnumProperty(items=[])
bpy.context.scene.closest_label_output = ''
bpy.context.scene.new_label_r = 5
bpy.context.scene.find_closest_label_on_click = False
bpy.context.scene.plot_closest_label_contour = False
mri_data_fname = op.join(mu.get_user_fol(), 'freeview', 'mri_data.npz')
if op.isfile(mri_data_fname):
WhereAmIPanel.mri_data = mu.Bag(np.load(mri_data_fname))
gray_colormap_fname = op.join(mu.file_fol(), 'color_maps', 'gray.npy')
if op.isfile(gray_colormap_fname):
WhereAmIPanel.gray_colormap = np.load(gray_colormap_fname)
WhereAmIPanel.addon = addon
WhereAmIPanel.init = True
WhereAmIPanel.run_slices_listener = False
init_slices()
if WhereAmIPanel.run_slices_listener:
start_slicer_server()
else:
WhereAmIPanel.slicer_state = mu.Bag({})
WhereAmIPanel.slicer_state['mri'] = slicer.init(_addon(), 'mri')
create_slices(None, bpy.context.scene.cursor_location)
save_slices_cursor_pos()
register()
except:
print("Can't init where-am-I panel!")
print(traceback.format_exc())
def save_all_views(views=None,
inflated_ratio_in_file_name=False,
rot_lh_axial=None,
render_images=False,
quality=0,
img_name_prefix='',
add_colorbar=None,
cb_ticks_num=None,
cb_ticks_font_size=None,
overwrite=True):
if not render_images:
_addon().change_to_solid_brain()
if add_colorbar is None:
add_colorbar = bpy.context.scene.save_views_with_cb
if cb_ticks_num is None:
cb_ticks_num = bpy.context.scene.cb_ticks_num
if cb_ticks_font_size is None:
cb_ticks_font_size = bpy.context.scene.cb_ticks_font_size
_addon().show_hemis()
if not bpy.context.scene.save_split_views:
rot_lh_axial = False if rot_lh_axial is None else rot_lh_axial
_save_all_views(views, inflated_ratio_in_file_name, rot_lh_axial,
render_images, quality, img_name_prefix, add_colorbar,
cb_ticks_num, cb_ticks_font_size, overwrite)
else:
if views is None:
views = list(
set(_addon().ANGLES_DICT.keys()) -
set([_addon().ROT_MEDIAL_LEFT,
_addon().ROT_MEDIAL_RIGHT]))
images_names = []
rot_lh_axial = True if rot_lh_axial is None else rot_lh_axial
org_hide = {hemi: mu.get_hemi_obj(hemi).hide for hemi in mu.HEMIS}
for hemi in mu.HEMIS:
mu.get_hemi_obj(hemi).hide = False
mu.get_hemi_obj(mu.other_hemi(hemi)).hide = True
images_names.extend(
_save_all_views(views,
inflated_ratio_in_file_name,
rot_lh_axial,
render_images,
quality,
img_name_prefix,
False,
overwrite=overwrite))
for hemi in mu.HEMIS:
mu.get_hemi_obj(hemi).hide = org_hide[hemi]
images_hemi_inv_list = set([
mu.namebase(fname)[3:] for fname in images_names
if mu.namebase(fname)[:2] in ['rh', 'lh']
])
files = [[
fname for fname in images_names
if mu.namebase(fname)[3:] == img_hemi_inv
] for img_hemi_inv in images_hemi_inv_list]
fol = mu.get_fname_folder(files[0][0])
for files_coup in files:
hemi = 'rh' if mu.namebase(
files_coup[0]).startswith('rh') else 'lh'
coup_template = files_coup[0].replace(hemi, '{hemi}')
coup = {hemi: coup_template.format(hemi=hemi) for hemi in mu.HEMIS}
new_image_fname = op.join(fol,
mu.namebase_with_ext(files_coup[0])[3:])
combine_two_images_and_add_colorbar(coup['lh'], coup['rh'],
new_image_fname, cb_ticks_num,
cb_ticks_font_size)
_addon().show_hemis()
def render_image(image_name='',
image_fol='',
quality=0,
use_square_samples=None,
render_background=None,
camera_fname='',
hide_subcorticals=False,
overwrite=True,
set_to_camera_mode=True):
if not is_camera_view() and set_to_camera_mode:
set_to_camera_view()
bpy.context.scene.render.resolution_percentage = bpy.context.scene.quality if quality == 0 else quality
bpy.context.scene.cycles.use_square_samples = bpy.context.scene.smooth_figure if use_square_samples is None \
else use_square_samples
if not render_background is None:
bpy.context.scene.render_background = render_background
if camera_fname == '':
camera_fname = op.join(mu.get_user_fol(), 'camera',
'{}.pkl'.format(bpy.context.scene.camera_files))
current_frame = bpy.context.scene.frame_current
camera_fnames = [camera_fname] if isinstance(camera_fname,
str) else camera_fname
if image_name == '':
images_names = [
'{}_{}.{}'.format(
mu.namebase(camera_fname).replace('camera', ''), current_frame,
_addon().get_figure_format()) for camera_fname in camera_fnames
]
images_names = [
n[1:] if n.startswith('_') else n for n in images_names
]
else:
images_names = [image_name] if isinstance(image_name,
str) else image_name
image_fol = bpy.path.abspath(
bpy.context.scene.output_path) if image_fol == '' else image_fol
image_fname = op.join(image_fol, '{}.{}'.format(images_names[0],
get_figure_format()))
if op.isfile(image_fname):
files = glob.glob(
op.join(
image_fol, '{}_*.{}'.format(mu.namebase(image_fname),
get_figure_format())))
image_fname = op.join(
image_fol, '{}_{}.{}'.format(mu.namebase(image_fname), len(files),
get_figure_format()))
if op.isfile(image_fname):
print('{} already exist!'.format(image_fname))
return ''
print('Image quality: {}'.format(
bpy.context.scene.render.resolution_percentage))
print("Rendering...")
if not bpy.context.scene.render_background:
for image_name, camera_fname in zip(images_names, camera_fnames):
print('file name: {}'.format(image_fname))
bpy.context.scene.render.filepath = image_fname
if overwrite or len(
glob.glob('{}.*'.format(
bpy.context.scene.render.filepath))) == 0:
# _addon().load_camera(camera_fname)
_addon().change_to_rendered_brain()
if hide_subcorticals:
_addon().show_hide_sub_corticals()
bpy.ops.render.render(write_still=True)
print("Finished")
return image_fname
else:
camera_fnames = ','.join(camera_fnames)
images_names = ','.join(images_names)
render_func = partial(render_in_background,
image_name=images_names,
image_fol=image_fol,
camera_fname=camera_fnames,
hide_subcorticals=hide_subcorticals,
overwrite=overwrite)
put_func_in_queue(render_func)
if queue_len() == 1:
run_func_in_queue()
return bpy.context.scene.render.filepath
def init(addon):
from random import shuffle
ColoringMakerPanel.addon = addon
user_fol = mu.get_user_fol()
ColoringMakerPanel.faces_verts = None
labels_vertices_fname = op.join(user_fol, 'labels_vertices_{}.pkl'.format(bpy.context.scene.atlas))
if not op.isfile(labels_vertices_fname):
print("!!! Can't find {}!".format('labels_vertices_{}.pkl'.format(bpy.context.scene.atlas)))
return None
labels_names, labels_vertices = mu.load(labels_vertices_fname)
ColoringMakerPanel.labels_vertices = dict(labels_names=labels_names, labels_vertices=labels_vertices)
ColoringMakerPanel.max_labels_vertices_num = {}
meg_files_exist = mu.hemi_files_exists(op.join(user_fol, 'activity_map_{hemi}', 't0.npy'))
meg_data_maxmin_fname = op.join(mu.get_user_fol(), 'meg_activity_map_minmax.pkl')
if meg_files_exist and op.isfile(meg_data_maxmin_fname):
data_min, data_max = mu.load(meg_data_maxmin_fname)
ColoringMakerPanel.meg_activity_colors_ratio = 256 / (data_max - data_min)
ColoringMakerPanel.meg_activity_data_min = data_min
ColoringMakerPanel.meg_activity_data_max = data_max
print('data meg: {}-{}'.format(data_min, data_max))
_addon().set_colorbar_max_min(data_max, data_min, True)
_addon().set_colorbar_title('MEG')
fmri_files = glob.glob(op.join(user_fol, 'fmri', 'fmri_*_lh.npy'))
if len(fmri_files) > 0:
files_names = [mu.namebase(fname)[5:-3] for fname in fmri_files]
clusters_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.fmri_files = bpy.props.EnumProperty(
items=clusters_items, description="fMRI files", update=fmri_files_update)
bpy.context.scene.fmri_files = files_names[0]
for hemi in mu.HEMIS:
ColoringMakerPanel.fMRI[hemi] = np.load('{}_{}.npy'.format(fmri_files[0][:-7], hemi))
# Check separately for each contrast
fmri_data_maxmin_fname = op.join(mu.get_user_fol(), 'fmri', 'fmri_activity_map_minmax.pkl')
if op.isfile(fmri_data_maxmin_fname):
data_min, data_max = mu.load(fmri_data_maxmin_fname)
ColoringMakerPanel.fmri_activity_colors_ratio = 256 / (data_max - data_min)
ColoringMakerPanel.fmri_activity_data_min = data_min
ColoringMakerPanel.fmri_activity_data_max = data_max
electrodes_source_files = glob.glob(op.join(user_fol, 'electrodes', '*_labels_*-rh.npz'))
if len(electrodes_source_files) > 0:
files_names = [mu.namebase(fname)[:-len('-rh')] for fname in electrodes_source_files]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.electrodes_sources_files = bpy.props.EnumProperty(
items=items, description="electrodes sources", update=electrodes_sources_files_update)
bpy.context.scene.electrodes_sources_files = files_names[0]
mu.make_dir(op.join(user_fol, 'coloring'))
manually_color_files = glob.glob(op.join(user_fol, 'coloring', '*.csv'))
if len(manually_color_files) > 0:
files_names = [mu.namebase(fname) for fname in manually_color_files]
coloring_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.coloring_files = bpy.props.EnumProperty(items=coloring_items, description="Coloring files")
bpy.context.scene.coloring_files = files_names[0]
vol_color_files = glob.glob(op.join(user_fol, 'coloring', 'volumetric', '*.csv'))
if len(vol_color_files) > 0:
files_names = [mu.namebase(fname) for fname in vol_color_files]
coloring_items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.vol_coloring_files = bpy.props.EnumProperty(
items=coloring_items, description="Volumetric Coloring files")
bpy.context.scene.vol_coloring_files = files_names[0]
ColoringMakerPanel.colors = list(set(list(cu.NAMES_TO_HEX.keys())) - set(['black']))
shuffle(ColoringMakerPanel.colors)
ColoringMakerPanel.labels_groups = read_groups_labels(ColoringMakerPanel.colors)
if len(ColoringMakerPanel.labels_groups) > 0:
groups_items = [(gr, gr, '', ind) for ind, gr in enumerate(list(ColoringMakerPanel.labels_groups.keys()))]
bpy.types.Scene.labels_groups = bpy.props.EnumProperty(
items=groups_items, description="Groups")
ColoringMakerPanel.faces_verts = load_faces_verts()
bpy.context.scene.coloring_meg_subcorticals = False
# ColoringMakerPanel.cm = np.load(op.join(mu.file_fol(), 'color_maps', 'BuPu_YlOrRd.npy'))
register()
def set_electrodes_labeling_file(fname):
bpy.context.scene.electrodes_labeling_files = mu.namebase(fname)
def get_group_name(pkl_fname):
pathway = mu.namebase(pkl_fname)
pathway = pathway[:-len(TRACULA_POSTFIX)]
return pathway
def get_clusters_files(user_fol=''):
clusters_labels_files = glob.glob(op.join(user_fol, 'fmri', 'clusters_labels_*.pkl'))
files_names = [mu.namebase(fname)[len('clusters_labels_'):] for fname in clusters_labels_files]
clusters_labels_items = [(c, c, '', ind) for ind, c in enumerate(list(set(files_names)))]
return files_names, clusters_labels_files, clusters_labels_items
def set_electrodes_labeling_file(fname):
bpy.context.scene.electrodes_labeling_files = mu.namebase(fname)
