def export_electrodes():
import csv
mu.make_dir(op.join(mu.get_user_fol(), 'electrodes'))
csv_fname = op.join(mu.get_user_fol(), 'electrodes', '{}_RAS.csv'.format(mu.get_user()))
electrodes = [e for e in bpy.data.objects[_addon().electrodes_panel_parent].children]
with open(csv_fname, 'w') as csv_file:
wr = csv.writer(csv_file, quoting=csv.QUOTE_ALL)
wr.writerow(['Electrode Name', 'R', 'A', 'S'])
for elc in electrodes:
wr.writerow([elc.name, *['{:.2f}'.format(loc * 10) for loc in elc.location]])
def grow_a_label():
closest_mesh_name, vertex_ind, _ = \
_addon().find_closest_vertex_index_and_mesh(use_shape_keys=True)
hemi = closest_mesh_name[len('infalted_'):] if _addon().is_inflated(
) else closest_mesh_name
subject, atlas = mu.get_user(), bpy.context.scene.subject_annot_files
label_name, label_r = bpy.context.scene.new_label_name, bpy.context.scene.new_label_r
flags = '-a {} --vertice_indice {} --hemi {} --label_name {} --label_r {}'.format(
atlas, vertex_ind, hemi, label_name, label_r)
mu.run_mmvt_func('src.preproc.anatomy', 'grow_label', flags=flags)
def load_surf_files(nii_fname, run_fmri_preproc=True, user_fol='', debug=True):
fmri_file_template = ''
if user_fol == '':
user_fol = mu.get_user_fol()
nii_fol = mu.get_fname_folder(nii_fname)
if debug:
print('load_surf_files: nii_fol: {}'.format(nii_fol))
hemi, fmri_hemis = mu.get_hemi_from_full_fname(nii_fname)
if debug:
print('load_surf_files: hemi, fmri_hemis: {}, {}'.format(
hemi, fmri_hemis))
if hemi == '':
hemi = mu.find_hemi_using_vertices_num(nii_fname)
if hemi == '':
return ''
# fmri_hemis = mu.get_both_hemis_files(nii_fname)
local_fname = build_local_fname(nii_fname, user_fol)
if debug:
print('load_surf_files: local_fname: {}'.format(local_fname))
mu.make_dir(op.join(user_fol, 'fmri'))
if nii_fol != op.join(user_fol, 'fmri'):
mu.make_link(nii_fname, local_fname, True)
other_hemi = mu.other_hemi(hemi)
if debug:
print('load_surf_files: other_hemi: {}'.format(other_hemi))
other_hemi_fname = fmri_hemis[other_hemi]
if debug:
print('load_surf_files: other_hemi_fname: {}'.format(other_hemi_fname))
# todo: if the other hemi file doens't exist, just create an empty one
output_fname_template = ''
if op.isfile(other_hemi_fname):
local_other_hemi_fname = build_local_fname(other_hemi_fname, user_fol)
if nii_fol != op.join(user_fol, 'fmri'):
mu.make_link(other_hemi_fname, local_other_hemi_fname, True)
fmri_file_template = mu.get_template_hemi_label_name(
mu.namebase_with_ext(local_fname))
if run_fmri_preproc:
mu.add_mmvt_code_root_to_path()
from src.preproc import fMRI
importlib.reload(fMRI)
ret, npy_output_fname_template = fMRI.load_surf_files(
mu.get_user(), fmri_file_template)
output_fname_template = op.join(
mu.get_parent_fol(npy_output_fname_template),
mu.namebase_with_ext(npy_output_fname_template)[len('fmri_'):])
else:
mu.run_mmvt_func(
'src.preproc.fMRI',
'load_surf_files',
flags='--fmri_file_template "{}"'.format(fmri_file_template))
# todo: find what should be the output_fname_template
else:
print(
"Couldn't find the other hemi file! ({})".format(other_hemi_fname))
return output_fname_template #, hemi, other_hemi
def open_freeview():
root = mu.get_user_fol()
sig_cmd = ''
if bpy.context.scene.fMRI_files_exist and bpy.context.scene.freeview_load_fMRI:
sig_fnames = glob.glob(op.join(root, 'freeview', '*{}*.mgz'.format(bpy.context.scene.fmri_files))) + \
glob.glob(op.join(root, 'freeview', '*{}*.nii'.format(bpy.context.scene.fmri_files)))
if len(sig_fnames) > 0:
sig_fname = sig_fnames[0]
sig_cmd = '-v "{}":colormap=heat:heatscale=2,3,6 '.format(
sig_fname) if op.isfile(sig_fname) else ''
ct_cmd = ''
if bpy.context.scene.freeview_load_CT:
mmvt_ct_fname = op.join(root, 'ct', 'ct_reg_to_mr.mgz')
if FreeviewPanel.CT_files_exist:
ct_cmd = '-v "{}":opacity=0 '.format(mmvt_ct_fname)
else:
print("Can't find CT {}!".format(mmvt_ct_fname))
dura_cmd = ''
if bpy.context.scene.freeview_load_dura:
dura_fname = FreeviewPanel.dura_srf_fname
if FreeviewPanel.dura_srf_exist:
dura_cmd = '-f "{}":edgecolor=blue "{}":edgecolor=blue '.format(
dura_fname.format(hemi='rh'), dura_fname.format(hemi='lh'))
T1 = op.join(root, 'freeview', 'T1.mgz') # sometimes 'orig.mgz' is better
if not op.isfile(T1):
T1 = op.join(root, 'freeview', 'orig.mgz')
if not op.isfile(T1):
print(
'No T1 / orig files in freeview folder. Running preproc.freeview')
bpy.context.scene.freeview_messages = 'Preparing... Try to run again'
cmd = '{} -m src.preproc.freeview -s {} -a {} -b {} --ignore_missing 1'.format(
bpy.context.scene.python_cmd, mu.get_user(),
bpy.context.scene.atlas, bpy.context.scene.bipolar)
mu.run_command_in_new_thread(cmd, False)
return {'RUNNING_MODAL'}
bpy.context.scene.freeview_messages = ''
aseg = op.join(root, 'freeview',
'{}+aseg.mgz'.format(bpy.context.scene.atlas))
if op.isfile(aseg):
lut = op.join(root, 'freeview',
'{}ColorLUT.txt'.format(bpy.context.scene.atlas))
aseg_cmd = '"{}":opacity=0.05:colormap=lut:lut="{}"'.format(aseg, lut)
else:
aseg_cmd = ''
electrodes_cmd = get_electrodes_command(root)
cmd = '{} "{}":opacity=0.5 {}{}{}{}{}{}{}'.format(
FreeviewPanel.addon_prefs.freeview_cmd, T1, aseg_cmd, electrodes_cmd,
sig_cmd, ct_cmd, dura_cmd,
' -verbose' if FreeviewPanel.addon_prefs.freeview_cmd_verbose else '',
' -stdin' if FreeviewPanel.addon_prefs.freeview_cmd_stdin else '')
print(cmd)
FreeviewPanel.freeview_in_queue, FreeviewPanel.freeview_out_queue = mu.run_command_in_new_thread(
cmd
) #, read_stderr=reading_freeview_stderr_func, read_stdin=reading_freeview_stdin_func,
def grow_a_label():
closest_mesh_name, vertex_ind, _, _ = \
_addon().find_vertex_index_and_mesh_closest_to_cursor(use_shape_keys=True)
hemi = closest_mesh_name[len('infalted_'):] if _addon().is_inflated(
) else closest_mesh_name
subject, atlas = mu.get_user(), bpy.context.scene.subject_annot_files
label_name, label_r = bpy.context.scene.new_label_name, bpy.context.scene.new_label_r
cmd = '{} -m src.preproc.anatomy -s {} -a {} -f grow_label '.format(
bpy.context.scene.python_cmd, subject, atlas)
cmd += '--vertice_indice {} --hemi {} --label_name {} --label_r {}'.format(
vertex_ind, hemi, label_name, label_r)
mu.run_command_in_new_thread(cmd, False)
def init(modality, modality_data=None, colormap=None, subject='', mmvt_dir=''):
if subject == '':
subject = mu.get_user()
if mmvt_dir == '':
mmvt_dir = mu.file_fol()
if modality_data is None:
if modality == 'mri':
fname = op.join(mmvt_dir, subject, 'freeview', 'mri_data.npz')
elif modality == 't2':
fname = op.join(mmvt_dir, subject, 'freeview', 't2_data.npz')
elif modality == 'ct':
fname = op.join(mmvt_dir, subject, 'ct', 'ct_data.npz'.format(modality))
if op.isfile(fname):
modality_data = mu.Bag(np.load(fname))
else:
print('To see the slices the following command is being called:'.format(modality))
print('python -m src.preproc.anatomy -s {} -f save_images_data_and_header'.format(mu.get_user()))
mu.run_mmvt_func('src.preproc.anatom', 'save_subject_orig_trans,save_images_data_and_header')
# cmd = '{} -m src.preproc.anatomy -s {} -f save_subject_orig_trans,save_images_data_and_header --ignore_missing 1'.format(
# bpy.context.scene.python_cmd, mu.get_user())
# mu.run_command_in_new_thread(cmd, False, cwd=mu.get_mmvt_code_root())
return None
if colormap is None:
if op.isfile(op.join(mmvt_dir, 'color_maps', 'gray.npy')):
colormap_fname = op.join(mmvt_dir, 'color_maps', 'gray.npy')
print("Can't find The gray colormap!")
else:
colormap_fname = glob.glob(op.join(mmvt_dir, 'color_maps', '*.npy'))[0]
colormap = np.load(colormap_fname)
affine = np.array(modality_data.affine, float)
data = modality_data.data
clim = modality_data.precentiles
if IN_BLENDER:
bpy.context.scene.slices_x_min, bpy.context.scene.slices_x_max = clim
colors_ratio = modality_data.colors_ratio
codes = axcodes2ornt(aff2axcodes(affine))
order = np.argsort([c[0] for c in codes])
print(modality, order)
flips = np.array([c[1] < 0 for c in codes])[order]
flips[0] = not flips[0]
sizes = [data.shape[order] for order in order]
scalers = voxel_sizes(affine)
r = [scalers[order[2]] / scalers[order[1]],
scalers[order[2]] / scalers[order[0]],
scalers[order[1]] / scalers[order[0]]]
extras = [0] * 3
pial_vol_mask_fname = op.join(mmvt_dir, subject, 'freeview', 'pial_vol_mask.npy')
pial_vol_mask = np.load(pial_vol_mask_fname) if op.isfile(pial_vol_mask_fname) else None
self = mu.Bag(dict(
data=data, affine=affine, order=order, sizes=sizes, flips=flips, clim=clim, r=r, colors_ratio=colors_ratio,
colormap=colormap, coordinates=[], modality=modality, extras=extras, pial_vol_mask=pial_vol_mask))
return self
def init(addon):
try:
trans_fname = op.join(mu.get_user_fol(), 'orig_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(trans_fname):
WhereAmIPanel.subject_orig_trans = mu.Bag(np.load(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)
subjects_dir = mu.get_link_dir(mu.get_links_dir(), 'subjects')
annot_files = glob.glob(
op.join(subjects_dir, mu.get_user(), 'label', 'rh.*.annot'))
if len(annot_files) > 0:
files_names = [mu.namebase(fname)[3:] for fname in annot_files]
items = [(c, c, '', ind) for ind, c in enumerate(files_names)]
bpy.types.Scene.subject_annot_files = bpy.props.EnumProperty(
items=items)
bpy.context.scene.subject_annot_files = files_names[0]
else:
bpy.types.Scene.subject_annot_files = bpy.props.EnumProperty(
items=[])
# bpy.context.scene.subject_annot_files = ''
bpy.context.scene.closest_label_output = ''
bpy.context.scene.new_label_r = 5
mri_data_fname = op.join(mu.get_user_fol(), 'freeview',
'{}_data.npz'.format('mri'))
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 = slicer.init('mri')
create_slices('mri', bpy.context.scene.cursor_location)
save_slices_cursor_pos()
register()
except:
print("Can't init where-am-I panel!")
print(traceback.format_exc())
def export_electrodes():
import csv
output_fol = op.join(mu.get_user_fol(), 'electrodes')
subject = mu.get_user()
csv_fname = op.join(output_fol, '{}_RAS.csv'.format(subject))
with open(csv_fname, 'w') as csv_file:
wr = csv.writer(csv_file, quoting=csv.QUOTE_NONE)
wr.writerow(['Electrode Name', 'R', 'A', 'S'])
for group, electrodes in ElecsPanel.groups_electrodes.items():
for elc_name in electrodes:
coords = get_elc_pos(elc_name) * 10
wr.writerow([elc_name, *['{:.2f}'.format(loc) for loc in coords]])
print('The electrodes file was exported to {}'.format(csv_fname))
def invoke(self, context, event=None):
subject = mu.get_user()
threshold = bpy.context.scene.fmri_clustering_threshold
contrast = bpy.context.scene.fmri_clusters_labels_files
atlas = bpy.context.scene.atlas
task = contrast.split('_')[0]
context.window_manager.modal_handler_add(self)
self._timer = context.window_manager.event_timer_add(0.1, context.window)
mu.change_fol_to_mmvt_root()
cmd = '{} -m src.preproc.fMRI_preproc -s {} -T {} -c {} -t {} -a {} -f find_clusters'.format(
bpy.context.scene.python_cmd, subject, task, contrast, threshold, atlas)
print('Running {}'.format(cmd))
self.in_q, self.out_q = mu.run_command_in_new_thread(cmd)
return {'RUNNING_MODAL'}
def invoke(self, context, event=None):
subject = mu.get_user()
threshold = bpy.context.scene.fmri_clustering_threshold
contrast = bpy.context.scene.fmri_clusters_labels_files
atlas = bpy.context.scene.atlas
task = contrast.split('_')[0]
context.window_manager.modal_handler_add(self)
self._timer = context.window_manager.event_timer_add(0.1, context.window)
mu.change_fol_to_mmvt_root()
cmd = '{} -m src.preproc.fMRI_preproc -s {} -T {} -c {} -t {} -a {} -f find_clusters'.format(
bpy.context.scene.python_cmd, subject, task, contrast, threshold, atlas)
print('Running {}'.format(cmd))
self.in_q, self.out_q = mu.run_command_in_new_thread(cmd)
return {'RUNNING_MODAL'}
def run_ela_alg():
mmvt_code_fol = mu.get_mmvt_code_root()
ela_code_fol = op.join(mu.get_parent_fol(mmvt_code_fol), 'electrodes_rois')
if not op.isdir(ela_code_fol) or not op.isfile(
op.join(ela_code_fol, 'find_rois', 'find_rois.py')):
print("Can't find ELA folder!")
return
import importlib
import sys
if ela_code_fol not in sys.path:
sys.path.append(ela_code_fol)
from find_rois import find_rois
importlib.reload(find_rois)
args = find_rois.get_args([
'-s',
mu.get_user(), '-a', bpy.context.scene.ela_atlas, '-b',
str(bpy.context.scene.ela_bipolar)
])
find_rois.run_for_all_subjects(args)
import shutil
ela_output_fname_template = op.join(
ela_code_fol, 'electrodes',
'{}_{}_electrodes_cigar_r_*_l_*{}.pkl'.format(
mu.get_user(), bpy.context.scene.ela_atlas,
'_bipolar' if bpy.context.scene.ela_bipolar else ''))
ela_output_fnames = glob.glob(ela_output_fname_template)
if len(ela_output_fnames) > 0:
for ela_output_fname in ela_output_fnames:
shutil.copyfile(
ela_output_fname,
op.join(mu.get_user_fol(), 'electrodes',
mu.namebase_with_ext(ela_output_fname)))
else:
print('couldn\'t find any ELA output! ({})'.format(
ela_output_fname_template))
init(_addon(), False)
def render_image(image_name='',
image_fol='',
quality=0,
use_square_samples=None,
render_background=None):
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
# print('@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@')
print('use_square_samples: {}'.format(use_square_samples))
# print('@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@')
cur_frame = bpy.context.scene.frame_current
if image_name == '':
image_name = 't{}'.format(cur_frame)
image_fol = bpy.path.abspath(
bpy.context.scene.output_path) if image_fol == '' else image_fol
print('file name: {}'.format(op.join(image_fol, image_name)))
bpy.context.scene.render.filepath = op.join(image_fol, image_name)
# Render and save the rendered scene to file. ------------------------------
print('Image quality:')
print(bpy.context.scene.render.resolution_percentage)
print("Rendering...")
if not bpy.context.scene.render_background:
bpy.ops.render.render(write_still=True)
else:
grab_camera()
mu.change_fol_to_mmvt_root()
electrode_marked = RenderingMakerPanel.addon.is_current_electrode_marked(
)
script = 'src.mmvt_addon.scripts.render_image'
cmd = '{} -m {} -s {} -a {} -q {} -b {} '.format(
bpy.context.scene.python_cmd, script, mu.get_user(), bpy.context.scene.atlas,
bpy.context.scene.render.resolution_percentage, bpy.context.scene.bipolar) + \
'--hide_lh {} --hide_rh {} --hide_subs {} --show_elecs {} --curr_elec {} --show_only_lead {} '.format(
bpy.context.scene.objects_show_hide_lh, bpy.context.scene.objects_show_hide_rh,
bpy.context.scene.objects_show_hide_sub_cortical, bpy.context.scene.appearance_show_electrodes_layer,
bpy.context.scene.electrodes if electrode_marked else None,
bpy.context.scene.show_only_lead if electrode_marked else None) + \
'--show_connections {}'.format(
RenderingMakerPanel.addon.connections_visible())
print('Running {}'.format(cmd))
mu.save_blender_file()
mu.run_command_in_new_thread(cmd, queues=False)
print("Finished")
def create_slices(modalities='mri', pos=None):
if WhereAmIPanel.slicer_state is None:
return
if pos is None:
pos = bpy.context.scene.cursor_location
if WhereAmIPanel.run_slices_listener:
init_listener()
xyz = ','.join(map(str, pos * 10))
ret = mu.conn_to_listener.send_command(
dict(cmd='slice_viewer_change_pos',
data=dict(subject=mu.get_user(),
xyz=xyz,
modalities=modalities,
coordinates_system='tk_ras')))
flag_fname = op.join(
mu.get_user_fol(), 'figures', 'slices',
'{}_slices.txt'.format('_'.join(modalities.split(','))))
bpy.ops.mmvt.wait_for_slices()
return
if WhereAmIPanel.mri_data is None or WhereAmIPanel.gray_colormap is None:
print('To be able to see the slices, you need to do the following:')
if WhereAmIPanel.mri_data is None:
print(
'python -m src.preproc.anatomy -s {} -f save_images_data_and_header'
.format(mu.get_user()))
if WhereAmIPanel.gray_colormap is None:
print('python -m src.setup -f copy_resources_files')
return
pos = np.array(pos) * 10
x, y, z = apply_trans(_trans().ras_tkr2vox,
np.array([pos])).astype(np.int)[0]
xyz = [x, y, z]
images = slicer.create_slices(xyz, WhereAmIPanel.slicer_state, 'mri')
update_slices(modality='mri', ratio=1, images=images)
def find_closest_label():
subjects_dir = mu.get_link_dir(mu.get_links_dir(), 'subjects')
closest_mesh_name, vertex_ind, vertex_co, _ = \
_addon().find_vertex_index_and_mesh_closest_to_cursor(use_shape_keys=True)
hemi = closest_mesh_name[len('infalted_'):] if _addon().is_inflated(
) else closest_mesh_name
annot_fname = op.join(
subjects_dir, mu.get_user(), 'label',
'{}.{}.annot'.format(hemi, bpy.context.scene.subject_annot_files))
labels = mu.read_labels_from_annot(annot_fname)
vert_labels = [l for l in labels if vertex_ind in l.vertices]
if len(vert_labels) > 0:
label = vert_labels[0]
bpy.context.scene.closest_label_output = label.name
return label.name, hemi
else:
return 'unknown', hemi
def init(modality, modality_data=None, colormap=None):
if modality_data is None:
fname = op.join(mu.get_user_fol(), 'freeview',
'{}_data.npz'.format(modality))
if op.isfile(fname):
modality_data = mu.Bag(np.load(fname))
else:
print(
'To see the slices you need to create the file {}_data.npz by calling:'
.format(modality))
print(
'python -m src.preproc.anatomy -s {} -f save_images_data_and_header'
.format(mu.get_user()))
return None
if colormap is None:
colormap_fname = op.join(mu.file_fol(), 'color_maps', 'gray.npy')
colormap = np.load(colormap_fname)
affine = np.array(modality_data.affine, float)
data = modality_data.data
clim = modality_data.precentiles
colors_ratio = modality_data.colors_ratio
codes = axcodes2ornt(aff2axcodes(affine))
order = np.argsort([c[0] for c in codes])
flips = np.array([c[1] < 0 for c in codes])[order]
flips[0] = not flips[0]
sizes = [data.shape[order] for order in order]
scalers = voxel_sizes(affine)
r = [
scalers[order[2]] / scalers[order[1]],
scalers[order[2]] / scalers[order[0]],
scalers[order[1]] / scalers[order[0]]
]
self = mu.Bag(
dict(data=data,
affine=affine,
order=order,
sizes=sizes,
flips=flips,
clim=clim,
r=r,
colors_ratio=colors_ratio,
colormap=colormap))
return self
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 find_elecrode_labeling_files():
files = []
blender_electrodes_names = set([o.name for o in bpy.data.objects['Deep_electrodes'].children])
# labeling_template = '{}_{}_electrodes_cigar_r_*_l_*.pkl'.format(mu.get_user(), bpy.context.scene.atlas)
labeling_template = '{}_*_electrodes_cigar_r_*_l_*.pkl'.format(mu.get_user(), bpy.context.scene.atlas)
labling_files = glob.glob(op.join(mu.get_user_fol(), 'electrodes', labeling_template))
for labling_file in labling_files:
try:
d = mu.load(labling_file)
electrodes_names = set([e['name'] for e in d])
# todo: find what is the problem... (mg96)
# if len(electrodes_names - blender_electrodes_names) == 0:
files.append(labling_file)
except:
print('Error reading {}'.format(labling_file))
continue
if len(files) == 0:
print("Can't find any labeling file that match the electrodes names in{}!".format(
op.join(mu.get_user_fol(), 'electrodes')))
return files
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 render_in_background(image_name, image_fol, camera_fname, hide_subcorticals, overwrite=True):
hide_subs_in_background = True if hide_subcorticals else bpy.context.scene.objects_show_hide_sub_cortical
mu.change_fol_to_mmvt_root()
electrode_marked = _addon().is_current_electrode_marked()
script = 'src.mmvt_addon.scripts.render_image'
cmd = '{} -m {} -s {} -a {} -i {} -o {} -q {} -b {} -c "{}"'.format(
bpy.context.scene.python_cmd, script, mu.get_user(), bpy.context.scene.atlas,
image_name, image_fol, bpy.context.scene.render.resolution_percentage,
bpy.context.scene.bipolar, camera_fname) + \
' --hide_lh {} --hide_rh {} --hide_subs {} --show_elecs {} --curr_elec {} --show_only_lead {}'.format(
bpy.context.scene.objects_show_hide_lh, bpy.context.scene.objects_show_hide_rh,
hide_subs_in_background, bpy.context.scene.show_hide_electrodes,
bpy.context.scene.electrodes if electrode_marked else None,
bpy.context.scene.show_only_lead if electrode_marked else None) + \
' --show_connections {} --interactive 0 --overwrite {}'.format(
_addon().connections_visible(), overwrite)
print('Running {}'.format(cmd))
RenderingMakerPanel.background_rendering = True
mu.save_blender_file()
_, RenderingMakerPanel.render_in_queue = mu.run_command_in_new_thread(
cmd, read_stderr=False, read_stdin=False, stdout_func=reading_from_rendering_stdout_func)
def load_surf_files(nii_fname):
fmri_file_template = ''
user_fol = mu.get_user_fol()
nii_fol = mu.get_fname_folder(nii_fname)
fmri_hemis = mu.get_both_hemis_files(nii_fname)
hemi = mu.get_hemi_from_full_fname(nii_fname)
local_fname = build_local_fname(nii_fname, user_fol)
mu.make_dir(op.join(user_fol, 'fmri'))
if nii_fol != op.join(user_fol, 'fmri'):
mu.make_link(nii_fname, local_fname, True)
other_hemi = mu.other_hemi(hemi)
other_hemi_fname = fmri_hemis[other_hemi]
if op.isfile(other_hemi_fname):
local_other_hemi_fname = build_local_fname(other_hemi_fname, user_fol)
if nii_fol != op.join(user_fol, 'fmri'):
mu.make_link(other_hemi_fname, local_other_hemi_fname, True)
fmri_file_template = mu.get_template_hemi_label_name(mu.namesbase_with_ext(local_fname))
cmd = '{} -m src.preproc.fMRI -s {} -f load_surf_files --fmri_file_template "{}"'.format(
bpy.context.scene.python_cmd, mu.get_user(), fmri_file_template)
mu.run_command_in_new_thread(cmd, False)
return fmri_file_template, hemi
def render_in_background(image_name, image_fol, camera_fname, hide_subcorticals, overwrite=True):
hide_subs_in_background = True if hide_subcorticals else bpy.context.scene.objects_show_hide_sub_cortical
mu.change_fol_to_mmvt_root()
electrode_marked = _addon().is_current_electrode_marked()
script = 'src.mmvt_addon.scripts.render_image'
cmd = '{} -m {} -s {} -a {} -i {} -o {} -q {} -b {} -c "{}"'.format(
bpy.context.scene.python_cmd, script, mu.get_user(), bpy.context.scene.atlas,
image_name, image_fol, bpy.context.scene.render.resolution_percentage,
bpy.context.scene.bipolar, camera_fname) + \
' --hide_lh {} --hide_rh {} --hide_subs {} --show_elecs {} --curr_elec {} --show_only_lead {}'.format(
bpy.context.scene.objects_show_hide_lh, bpy.context.scene.objects_show_hide_rh,
hide_subs_in_background, bpy.context.scene.show_hide_electrodes,
bpy.context.scene.electrodes if electrode_marked else None,
bpy.context.scene.show_only_lead if electrode_marked else None) + \
' --show_connections {} --interactive 0 --overwrite {}'.format(
_addon().connections_visible(), overwrite)
print('Running {}'.format(cmd))
RenderingMakerPanel.background_rendering = True
mu.save_blender_file()
_, RenderingMakerPanel.render_in_queue = mu.run_command_in_new_thread(
cmd, read_stderr=False, read_stdin=False, stdout_func=reading_from_rendering_stdout_func)
def render_image(image_name='', image_fol='', quality=0, use_square_samples=None, render_background=None):
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
# print('@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@')
print('use_square_samples: {}'.format(use_square_samples))
# print('@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@')
cur_frame = bpy.context.scene.frame_current
if image_name == '':
image_name = 't{}'.format(cur_frame)
image_fol = bpy.path.abspath(bpy.context.scene.output_path) if image_fol == '' else image_fol
print('file name: {}'.format(op.join(image_fol, image_name)))
bpy.context.scene.render.filepath = op.join(image_fol, image_name)
# Render and save the rendered scene to file. ------------------------------
print('Image quality:')
print(bpy.context.scene.render.resolution_percentage)
print("Rendering...")
if not bpy.context.scene.render_background:
bpy.ops.render.render(write_still=True)
else:
mu.change_fol_to_mmvt_root()
electrode_marked = RenderingMakerPanel.addon.is_current_electrode_marked()
script = 'src.mmvt_addon.scripts.render_image'
cmd = '{} -m {} -s {} -a {} -q {} -b {} --hide_lh {} --hide_rh {} --hide_subs {} --show_elecs {} --curr_elec {} --show_only_lead {}'.format(
bpy.context.scene.python_cmd, script, mu.get_user(), bpy.context.scene.atlas,
bpy.context.scene.render.resolution_percentage, bpy.context.scene.bipolar,
bpy.context.scene.objects_show_hide_lh, bpy.context.scene.objects_show_hide_rh,
bpy.context.scene.objects_show_hide_sub_cortical, bpy.context.scene.appearance_show_electrodes_layer,
bpy.context.scene.electrodes if electrode_marked else None,
bpy.context.scene.show_only_lead if electrode_marked else None)
print('Running {}'.format(cmd))
mu.save_blender_file()
mu.run_command_in_new_thread(cmd, queues=False)
print("Finished")
def color_manually():
ColoringMakerPanel.what_is_colored.add(WIC_MANUALLY)
init_activity_map_coloring('FMRI')
subject_fol = mu.get_user_fol()
objects_names, colors, data = defaultdict(list), defaultdict(list), defaultdict(list)
for line in mu.csv_file_reader(op.join(subject_fol, 'coloring', '{}.csv'.format(bpy.context.scene.coloring_files))):
obj_name, color_name = line[0], line[1:]
if obj_name[0] == '#':
continue
if isinstance(color_name, list) and len(color_name) == 1:
color_name = color_name[0]
obj_type = mu.check_obj_type(obj_name)
if isinstance(color_name, str) and color_name.startswith('mark'):
import filter_panel
filter_panel.filter_roi_func(obj_name, mark=color_name)
else:
if isinstance(color_name, str):
color_rgb = cu.name_to_rgb(color_name)
# Check if the color is already in RBG
elif len(color_name) == 3:
color_rgb = color_name
else:
print('Unrecognize color! ({})'.format(color_name))
continue
color_rgb = list(map(float, color_rgb))
if obj_type is not None:
objects_names[obj_type].append(obj_name)
colors[obj_type].append(color_rgb)
data[obj_type].append(1.)
color_objects(objects_names, colors, data)
if op.isfile(op.join(subject_fol, 'coloring', '{}_legend.jpg'.format(bpy.context.scene.coloring_files))):
cmd = '{} -m src.preproc.electrodes_preproc -s {} -a {} -f show_labeling_coloring'.format(
bpy.context.scene.python_cmd, mu.get_user(), bpy.context.scene.atlas)
print('Running {}'.format(cmd))
mu.run_command_in_new_thread(cmd, False)
def color_manually():
ColoringMakerPanel.what_is_colored.add(WIC_MANUALLY)
init_activity_map_coloring('FMRI')
subject_fol = mu.get_user_fol()
objects_names, colors, data = defaultdict(list), defaultdict(list), defaultdict(list)
for line in mu.csv_file_reader(op.join(subject_fol, 'coloring', '{}.csv'.format(bpy.context.scene.coloring_files))):
obj_name, color_name = line[0], line[1:]
if obj_name[0] == '#':
continue
if isinstance(color_name, list) and len(color_name) == 1:
color_name = color_name[0]
obj_type = mu.check_obj_type(obj_name)
if isinstance(color_name, str) and color_name.startswith('mark'):
import filter_panel
filter_panel.filter_roi_func(obj_name, mark=color_name)
else:
if isinstance(color_name, str):
color_rgb = cu.name_to_rgb(color_name)
# Check if the color is already in RBG
elif len(color_name) == 3:
color_rgb = color_name
else:
print('Unrecognize color! ({})'.format(color_name))
continue
color_rgb = list(map(float, color_rgb))
if obj_type is not None:
objects_names[obj_type].append(obj_name)
colors[obj_type].append(color_rgb)
data[obj_type].append(1.)
color_objects(objects_names, colors, data)
if op.isfile(op.join(subject_fol, 'coloring', '{}_legend.jpg'.format(bpy.context.scene.coloring_files))):
cmd = '{} -m src.preproc.electrodes_preproc -s {} -a {} -f show_labeling_coloring'.format(
bpy.context.scene.python_cmd, mu.get_user(), bpy.context.scene.atlas)
print('Running {}'.format(cmd))
mu.run_command_in_new_thread(cmd, False)
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 invoke(self, context, event=None):
cmd = '{} -m src.preproc.anatomy_preproc -s {} -a {}'.format(
bpy.context.scene.python_cmd, mu.get_user(), bpy.context.scene.atlas)
print('Running {}'.format(cmd))
mu.run_command_in_new_thread(cmd, False)
return {"FINISHED"}
def create_slices(modality=None,
pos=None,
zoom_around_voxel=None,
zoom_voxels_num=-1,
smooth=None,
clim=None,
plot_cross=None,
mark_voxel=None):
if zoom_around_voxel is None:
zoom_around_voxel = bpy.context.scene.slices_zoom_around_voxel
if zoom_voxels_num == -1:
zoom_voxels_num = bpy.context.scene.slices_zoom_voxels_num
if smooth is None:
smooth = bpy.context.scene.slices_zoom_interpolate
if clim is None:
clim = (bpy.context.scene.slices_x_min, bpy.context.scene.slices_x_max)
if plot_cross is None:
plot_cross = bpy.context.scene.slices_plot_cross
if mark_voxel is None:
mark_voxel = bpy.context.scene.slices_mark_voxel
if WhereAmIPanel.slicer_state.mri is None:
return
if modality is None:
modality = bpy.context.scene.slices_modality
pos_was_none = pos is None
if pos is None:
pos = bpy.context.scene.cursor_location * 10
# if bpy.context.scene.cursor_is_snapped and pos_was_none:
# pos = calc_tkreg_ras_from_snapped_cursor()
if pos_was_none:
pos = calc_tkreg_ras_from_cursor()
if pos is None:
print(
"Can't calc slices if the cursor isn't snapped and the brain is inflated!"
)
return
# pos = np.array(pos) * 10
if WhereAmIPanel.run_slices_listener:
init_listener()
xyz = ','.join(map(str, pos))
ret = mu.conn_to_listener.send_command(
dict(cmd='slice_viewer_change_pos',
data=dict(subject=mu.get_user(),
xyz=xyz,
modalities=modality,
coordinates_system='tk_ras')))
flag_fname = op.join(
mu.get_user_fol(), 'figures', 'slices',
'{}_slices.txt'.format('_'.join(modality.split(','))))
bpy.ops.mmvt.wait_for_slices()
return
if WhereAmIPanel.mri_data is None or WhereAmIPanel.gray_colormap is None:
print('To be able to see the slices, you need to do the following:')
if WhereAmIPanel.mri_data is None:
print(
'python -m src.preproc.anatomy -s {} -f save_images_data_and_header'
.format(mu.get_user()))
if WhereAmIPanel.gray_colormap is None:
print('python -m src.setup -f copy_resources_files')
return
if modality == 'mri':
x, y, z = np.rint(
apply_trans(t1_trans().ras_tkr2vox,
np.array([pos]))[0]).astype(int)
elif modality == 't2':
x, y, z = np.rint(
apply_trans(t2_trans().ras_tkr2vox,
np.array([pos]))[0]).astype(int)
elif modality == 'ct':
vox = apply_trans(t1_trans().ras_tkr2vox, np.array([pos]))[0]
ras = apply_trans(t1_trans().vox2ras, np.array([vox]))[0]
x, y, z = np.rint(
apply_trans(_ct_trans().ras2vox, np.array([ras]))[0]).astype(int)
xyz = [x, y, z]
# print('Create slices, slicer_state.coordinates: {}'.format(WhereAmIPanel.slicer_state.coordinates))
create_slices_from_vox_coordinates(xyz, modality, zoom_around_voxel,
zoom_voxels_num, smooth, clim,
plot_cross, mark_voxel)
