def import_evokes(evokes_fname):
import importlib
import mne
mu.add_mmvt_code_root_to_path()
from src.preproc import meg
importlib.reload(meg)
opt_trans_files = glob.glob(
op.join(mu.get_parent_fol(evokes_fname), '*.fif'))
trans_files = meg.filter_trans_files(opt_trans_files)
trans_file = mu.select_one_file(trans_files,
template='*.fif',
files_desc='MRI-Head transformation')
args = mu.get_remote_subject_info_args()
evokes = mne.read_evokeds(evokes_fname)
events_keys = [ev.comment for ev in evokes]
meg.read_sensors_layout(mu.get_user(),
args,
info=evokes[0].info,
trans_file=trans_file)
meg.save_evokes_to_mmvt(evokes, events_keys, mu.get_user())
_addon().import_meg_sensors()
_addon().add_data_to_meg_sensors()
# _addon().load_all_panels()
_addon().show_meg_sensors()
def dipole_fit():
mu.add_mmvt_code_root_to_path()
from src.preproc import meg
importlib.reload(meg)
subject = mu.get_user()
args = meg.read_cmd_args(
dict(subject=subject, mri_subject=subject, atlas=mu.get_atlas()))
meg.init(subject, args)
dipoles_times = [(bpy.context.scene.meg_dipole_fit_tmin,
bpy.context.scene.meg_dipole_fit_tmax)]
dipoloes_title = mask_roi = MEGPanel.current_cluster['intersects'][0][
'name']
meg.dipoles_fit(dipoles_times,
dipoloes_title,
None,
mu.get_real_fname('meg_noise_cov_fname'),
mu.get_real_fname('meg_evoked_fname'),
mu.get_real_fname('head_to_mri_trans_mat_fname'),
5.,
bpy.context.scene.meg_dipole_fit_use_meg,
bpy.context.scene.meg_dipole_fit_use_eeg,
mask_roi=mask_roi,
do_plot=False,
n_jobs=4)
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 other_hemi_fname == '':
other_hemi_fname = local_fname.replace(hemi, 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)
vertices_num = mu.get_vertices_num()
ret, npy_output_fname_template = fMRI.load_surf_files(
mu.get_user(), fmri_hemis, vertices_num=vertices_num)
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 calc_clusters():
import importlib
mu.add_mmvt_code_root_to_path()
from src.preproc import fMRI
importlib.reload(fMRI)
surf_template_fname = 'fmri_{}.?h.npy'.format(_addon().coloring.get_select_fMRI_contrast())
print(mu.get_user(), surf_template_fname, bpy.context.scene.fmri_clustering_threshold, bpy.context.scene.atlas)
fMRI.find_clusters(mu.get_user(), surf_template_fname, bpy.context.scene.fmri_clustering_threshold,
bpy.context.scene.subject_annot_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
