def create_movie(time_range, xticks, fol, dpi, fps, video_fname, cb_data_type,
data_to_show_in_graph, cb_title='', cb_min_max_eq=True, cb_norm_percs=None, color_map='jet',
bitrate=5000, fol2='', cb2_data_type='', cb2_title='', cb2_min_max_eq=True, color_map2='jet',
ylim=(), ylabels=(), xticklabels=(), xlabel='Time (ms)', pics_type='png', show_first_pic=False,
show_animation=False, overwrite=True, n_jobs=1):
images1 = get_pics(fol, pics_type)[:len(time_range)]
images1_chunks = utils.chunks(images1, len(images1) / n_jobs)
if fol2 != '':
images2 = get_pics(fol2, pics_type)
if len(images2) != len(images1):
raise Exception('fol and fol2 have different number of pictures!')
images2_chunks = utils.chunks(images2, int(len(images2) / n_jobs))
else:
images2_chunks = [''] * int(len(images1) / n_jobs)
params = [(images1_chunk, images2_chunk, time_range, xticks, dpi, fps,
video_fname, cb_data_type, data_to_show_in_graph, cb_title, cb_min_max_eq, cb_norm_percs, color_map,
bitrate, ylim, ylabels, xticklabels, xlabel, show_first_pic, fol, fol2,
cb2_data_type, cb2_title, cb2_min_max_eq, color_map2, run, show_animation, overwrite) for \
run, (images1_chunk, images2_chunk) in enumerate(zip(images1_chunks, images2_chunks))]
n_jobs = utils.get_n_jobs(n_jobs)
if n_jobs > 1:
utils.run_parallel(_create_movie_parallel, params, n_jobs)
video_name, video_type = op.splitext(video_fname)
mu.combine_movies(fol, video_name, video_type[1:])
else:
for p in params:
_create_movie_parallel(p)
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='MMVT stim preprocessing')
parser.add_argument('-s', '--subject', help='subject name', required=True, type=au.str_arr_type)
parser.add_argument('-c', '--conditions', help='conditions names', required=False, default='contrast', type=au.str_arr_type)
parser.add_argument('-a', '--atlas', help='atlas name', required=False, default='aparc.DKTatlas40')
parser.add_argument('-f', '--function', help='function name', required=False, default='all', type=au.str_arr_type)
parser.add_argument('--exclude', help='functions not to run', required=False, default='', type=au.str_arr_type)
parser.add_argument('--mat_fname', help='matlab connection file name', required=False, default='')
parser.add_argument('--mat_field', help='matlab connection field name', required=False, default='')
parser.add_argument('--labels_exclude', help='rois to exclude', required=False, default='unknown,corpuscallosum',
type=au.str_arr_type)
parser.add_argument('--norm_by_percentile', help='', required=False, default=1, type=au.is_true)
parser.add_argument('--norm_percs', help='', required=False, default='1,99', type=au.int_arr_type)
parser.add_argument('--stat', help='', required=False, default=STAT_DIFF, type=int)
parser.add_argument('--windows', help='', required=False, default=0, type=int)
parser.add_argument('--t_max', help='', required=False, default=0, type=int)
parser.add_argument('--threshold_percentile', help='', required=False, default=0, type=int)
parser.add_argument('--threshold', help='', required=False, default=0, type=float)
parser.add_argument('--color_map', help='', required=False, default='jet')
parser.add_argument('--symetric_colors', help='', required=False, default=1, type=au.is_true)
parser.add_argument('--data_max', help='', required=False, default=0, type=float)
parser.add_argument('--data_min', help='', required=False, default=0, type=float)
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if len(args.conditions) == 1:
args.stat = STAT_AVG
print(args)
return args
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='Description of your program')
parser.add_argument('-s', '--subject', help='subject name', required=True)
parser.add_argument('-f',
'--function',
help='function name',
required=False,
default='all')
parser.add_argument('-c',
'--contrast',
help='contrast name',
required=True)
parser.add_argument('-a',
'--atlas',
help='atlas name',
required=False,
default='aparc.DKTatlas40')
parser.add_argument('-t',
'--threshold',
help='clustering threshold',
required=False,
default='2')
parser.add_argument('-T', '--task', help='task', required=True)
parser.add_argument('--existing_format',
help='existing format',
required=False,
default='mgz')
parser.add_argument('--volume_type',
help='volume type',
required=False,
default='mni305')
parser.add_argument('--volume_name',
help='volume file name',
required=False,
default='')
parser.add_argument('--surface_name',
help='surface_name',
required=False,
default='pial')
parser.add_argument('--meg_subject',
help='meg_subject',
required=False,
default='')
parser.add_argument('--inverse_method',
help='inverse method',
required=False,
default='dSPM')
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.n_jobs = utils.get_n_jobs(args.n_jobs)
print(args)
return args
def init_args(args):
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if args.necessary_files == '':
args.necessary_files = dict()
args.subject = decode_subjects(args.subject)
if 'sftp_password' not in args or args.sftp_password == '':
args.sftp_password = utils.get_sftp_password(
args.subject, SUBJECTS_DIR, args.necessary_files, args.sftp_username, args.overwrite_fs_files) \
if args.sftp else ''
set_default_args(args)
args.atlas = utils.get_real_atlas_name(args.atlas)
os.environ['SUBJECTS_DIR'] = SUBJECTS_DIR
return args
def run_on_subjects(args, main_func, subjects_itr=None, subject_func=None):
if subjects_itr is None:
subjects_itr = args.subject
subjects_flags, subjects_errors = {}, {}
args.n_jobs = utils.get_n_jobs(args.n_jobs)
args.sftp_password = utils.get_sftp_password(
args.subject, SUBJECTS_DIR, args.necessary_files, args.sftp_username, args.overwrite_fs_files) \
if args.sftp else ''
if '*' in args.subject:
args.subject = [utils.namebase(fol) for fol in glob.glob(op.join(SUBJECTS_DIR, args.subject))]
os.environ['SUBJECTS_DIR'] = SUBJECTS_DIR
for tup in subjects_itr:
subject = get_subject(tup, subject_func)
utils.make_dir(op.join(MMVT_DIR, subject, 'mmvt'))
remote_subject_dir = utils.build_remote_subject_dir(args.remote_subject_dir, subject)
print('****************************************************************')
print('subject: {}, atlas: {}'.format(subject, args.atlas))
print('remote dir: {}'.format(remote_subject_dir))
print('****************************************************************')
os.environ['SUBJECT'] = subject
flags = dict()
if args.necessary_files == '':
args.necessary_files = dict()
try:
if utils.should_run(args, 'prepare_local_subjects_folder'):
# *) Prepare the local subject's folder
flags['prepare_local_subjects_folder'] = prepare_local_subjects_folder(
subject, remote_subject_dir, args)
if not flags['prepare_local_subjects_folder'] and not args.ignore_missing:
ans = input('Do you which to continue (y/n)? ')
if not au.is_true(ans):
continue
flags = main_func(tup, remote_subject_dir, args, flags)
subjects_flags[subject] = flags
except:
subjects_errors[subject] = traceback.format_exc()
print('Error in subject {}'.format(subject))
print(traceback.format_exc())
errors = defaultdict(list)
for subject, flags in subjects_flags.items():
print('subject {}:'.format(subject))
for flag_type, val in flags.items():
print('{}: {}'.format(flag_type, val))
if not val:
errors[subject].append(flag_type)
if len(errors) > 0:
print('Errors:')
for subject, error in errors.items():
print('{}: {}'.format(subject, error))
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='MMVT anatomy preprocessing')
parser.add_argument('-s', '--subject', help='subject name', required=True, type=au.str_arr_type)
parser.add_argument('-a', '--atlas', help='atlas name', required=False, default='aparc.DKTatlas40')
parser.add_argument('-f', '--function', help='functions to run', required=False, default='all', type=au.str_arr_type)
parser.add_argument('--exclude', help='functions not to run', required=False, default='', type=au.str_arr_type)
parser.add_argument('--ignore_missing', help='ignore missing files', required=False, default=0, type=au.is_true)
parser.add_argument('--fsaverage', help='fsaverage', required=False, default='fsaverage')
parser.add_argument('--remote_subject_dir', help='remote_subject_dir', required=False, default='')
parser.add_argument('--remote_subjects_dir', help='remote_subjects_dir', required=False, default='')
parser.add_argument('--surf_name', help='surf_name', required=False, default='pial')
parser.add_argument('--overwrite', help='overwrite', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_fs_files', help='overwrite freesurfer files', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_annotation', help='overwrite_annotation', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_morphing_labels', help='overwrite_morphing_labels', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_hemis_srf', help='overwrite_hemis_srf', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_labels_ply_files', help='overwrite_labels_ply_files', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_faces_verts', help='overwrite_faces_verts', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_ply_files', help='overwrite_ply_files', required=False, default=0, type=au.is_true)
parser.add_argument('--solve_labels_collisions', help='solve_labels_collisions', required=False, default=0, type=au.is_true)
parser.add_argument('--morph_labels_from_fsaverage', help='morph_labels_from_fsaverage', required=False, default=1, type=au.is_true)
parser.add_argument('--fs_labels_fol', help='fs_labels_fol', required=False, default='')
parser.add_argument('--sftp', help='copy subjects files over sftp', required=False, default=0, type=au.is_true)
parser.add_argument('--sftp_username', help='sftp username', required=False, default='')
parser.add_argument('--sftp_domain', help='sftp domain', required=False, default='')
parser.add_argument('--print_traceback', help='print_traceback', required=False, default=1, type=au.is_true)
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.necessary_files = {'mri': ['aseg.mgz', 'norm.mgz', 'ribbon.mgz'],
'surf': ['rh.pial', 'lh.pial', 'rh.sphere.reg', 'lh.sphere.reg', 'lh.white', 'rh.white', 'rh.smoothwm','lh.smoothwm']}
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if args.overwrite:
args.overwrite_annotation = True
args.overwrite_morphing_labels = True
args.overwrite_hemis_srf = True
args.overwrite_labels_ply_files = True
args.overwrite_faces_verts = True
args.overwrite_fs_files = True
print(args)
return args
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='MMVT anatomy preprocessing')
parser.add_argument('-s', '--subject', help='subject name', required=True, type=au.str_arr_type)
parser.add_argument('-a', '--atlas', help='atlas name', required=False, default='aparc.DKTatlas40')
parser.add_argument('-f', '--function', help='functions to run', required=False, default='all', type=au.str_arr_type)
parser.add_argument('--exclude', help='functions not to run', required=False, default='', type=au.str_arr_type)
parser.add_argument('--ignore_missing', help='ignore missing files', required=False, default=0, type=au.is_true)
parser.add_argument('--fsaverage', help='fsaverage', required=False, default='fsaverage')
parser.add_argument('--remote_subject_dir', help='remote_subject_dir', required=False, default='')
parser.add_argument('--surf_name', help='surf_name', required=False, default='pial')
parser.add_argument('--overwrite', help='overwrite', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_fs_files', help='overwrite freesurfer files', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_annotation', help='overwrite_annotation', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_morphing_labels', help='overwrite_morphing_labels', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_hemis_srf', help='overwrite_hemis_srf', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_labels_ply_files', help='overwrite_labels_ply_files', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_faces_verts', help='overwrite_faces_verts', required=False, default=0, type=au.is_true)
parser.add_argument('--overwrite_ply_files', help='overwrite_ply_files', required=False, default=0, type=au.is_true)
parser.add_argument('--solve_labels_collisions', help='solve_labels_collisions', required=False, default=0, type=au.is_true)
parser.add_argument('--morph_labels_from_fsaverage', help='morph_labels_from_fsaverage', required=False, default=1, type=au.is_true)
parser.add_argument('--fs_labels_fol', help='fs_labels_fol', required=False, default='')
parser.add_argument('--sftp', help='copy subjects files over sftp', required=False, default=0, type=au.is_true)
parser.add_argument('--sftp_username', help='sftp username', required=False, default='')
parser.add_argument('--sftp_domain', help='sftp domain', required=False, default='')
parser.add_argument('--print_traceback', help='print_traceback', required=False, default=1, type=au.is_true)
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.necessary_files = {'mri': ['aseg.mgz', 'norm.mgz', 'ribbon.mgz', 'T1.mgz'],
'surf': ['rh.pial', 'lh.pial', 'rh.inflated', 'lh.inflated', 'lh.curv', 'rh.curv', 'rh.sphere.reg', 'lh.sphere.reg', 'lh.white', 'rh.white', 'rh.smoothwm','lh.smoothwm'],
'mri:transforms' : ['talairach.xfm']}
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if args.overwrite:
args.overwrite_annotation = True
args.overwrite_morphing_labels = True
args.overwrite_hemis_srf = True
args.overwrite_labels_ply_files = True
args.overwrite_faces_verts = True
args.overwrite_fs_files = True
print(args)
return args
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='Description of your program')
parser.add_argument('-s', '--subject', help='subject name', required=True)
parser.add_argument('-f', '--function', help='function name', required=False, default='all')
parser.add_argument('-c', '--contrast', help='contrast name', required=True)
parser.add_argument('-a', '--atlas', help='atlas name', required=False, default='aparc.DKTatlas40')
parser.add_argument('-t', '--threshold', help='clustering threshold', required=False, default='2')
parser.add_argument('-T', '--task', help='task', required=True)
parser.add_argument('--existing_format', help='existing format', required=False, default='mgz')
parser.add_argument('--volume_type', help='volume type', required=False, default='mni305')
parser.add_argument('--volume_name', help='volume file name', required=False, default='')
parser.add_argument('--surface_name', help='surface_name', required=False, default='pial')
parser.add_argument('--meg_subject', help='meg_subject', required=False, default='')
parser.add_argument('--inverse_method', help='inverse method', required=False, default='dSPM')
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.n_jobs = utils.get_n_jobs(args.n_jobs)
print(args)
return args
# subject, clips_dict['ictal'], modality, inverse_method, seizure_times, windows_length, windows_shift)
# calc_accumulate_stc_as_time(
# subject, clips_dict['ictal'], modality, seizure_times, windows_length, windows_shift, mean_baseline,
# inverse_method, n_jobs)
# calc_rois_connectivity(
# subject, clips_dict, modality, atlas, inverse_method, min_order, max_order, con_crop_times, onset_time,
# windows_length, windows_shift, overwrite=True, n_jobs=n_jobs)
normalize_connectivity(
subject, clips_dict, modality, atlas, divide_by_baseline_std=False,
threshold=0.5, reduce_to_3d=True, time_axis=np.mean(con_windows, 1), overwrite=False, n_jobs=n_jobs)
# plot_connectivity(subject, clips_dict, modality, inverse_method)
pass
if __name__ == '__main__':
n_jobs = utils.get_n_jobs(40)
n_jobs = n_jobs if n_jobs >= 1 else 4
print('{} jobs'.format(n_jobs))
fif_files, clips_dict = [], {}
atlas = 'aparc.DKTatlas' # 'laus125'
run_num = 3
subject, remote_subject_dir, meg_fol, bad_channels, raw_fname, empty_room_fname = init_nmr01391()
for subfol in ['baseline', 'ictal']:
files = glob.glob(op.join(meg_fol, subfol, 'run{}_*.fif'.format(run_num)))
fif_files += files
clips_dict[subfol] = files
main(subject, run_num, clips_dict, raw_fname, empty_room_fname, bad_channels, modality='meg',inverse_method='MNE',
downsample_r=2, seizure_times=(-0.2, .5), windows_length=0.1, windows_shift=0.05, mean_baseline=10,
atlas=atlas, min_cluster_size=50, min_order=1, max_order=20, con_windows_length=100, con_windows_shift=10,
# calc_stcs(subject, modality, clips_dict, inverse_method, downsample_r, overwrite=True, n_jobs=n_jobs)
# calc_stc_zvals(subject, modality, clips_dict['ictal'], inverse_method, overwrite=True, n_jobs=n_jobs)
# find_functional_rois(
# subject, clips_dict['ictal'], modality, seizure_times, atlas, min_cluster_size,
# inverse_method, overwrite=True, n_jobs=n_jobs)
# calc_rois_connectivity(
# subject, clips_dict, modality, inverse_method, min_order, max_order, con_crop_times, onset_time,
# windows_length, windows_shift, overwrite=True, n_jobs=n_jobs)
# normalize_connectivity(
# subject, clips_dict['ictal'], modality, divide_by_baseline_std=False,
# threshold=0.5, reduce_to_3d=True, overwrite=False, n_jobs=n_jobs)
plot_connectivity(subject, clips_dict, modality, inverse_method)
if __name__ == '__main__':
n_jobs = utils.get_n_jobs(10)
n_jobs = n_jobs if n_jobs > 1 else 1
print('{} jobs'.format(n_jobs))
fif_files, clips_dict = [], {}
subject, remote_subject_dir, meg_fol, bad_channels, raw_fname, empty_room_fname = init_nmr01391(
)
for subfol in ['baseline', 'ictal']:
files = glob.glob(op.join(meg_fol, subfol, '*.fif'))
fif_files += files
clips_dict[subfol] = files
main(subject,
clips_dict,
modality='meg',
inverse_method='MNE',
default='')
parser.add_argument('--print_only',
required=False,
default=False,
type=au.is_true)
parser.add_argument('--sftp',
required=False,
default=False,
type=au.is_true)
parser.add_argument('--sftp_username',
help='sftp username',
required=False,
default='npeled')
parser.add_argument('--sftp_domain',
help='sftp domain',
required=False,
default='door.nmr.mgh.harvard.edu')
parser.add_argument('--n_jobs', help='cpu num', required=False, default=1)
args = utils.Bag(au.parse_parser(parser))
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if len(args.subject) == 0:
args.subject = subjects
with warnings.catch_warnings():
warnings.simplefilter("ignore")
main(args.subject, template_system, remote_subject_templates, bipolar,
save_as_bipolar, overwrite, prefix, args.sftp, args.sftp_username,
args.sftp_domain, args.print_only, args.n_jobs)
print('Done!')
print('finish')
parser.add_argument('--pics_type', help='pics_type', required=False, default='png')
parser.add_argument('--show_first_pic', help='show_first_pic', required=False, type=au.is_true, default=0)
parser.add_argument('--images_folder', help='images_folder', required=False)
parser.add_argument('--data_in_graph', help='data_in_graph', required=False)
parser.add_argument('--time_range', help='time_range_from', required=False, type=au.float_arr_type)
parser.add_argument('--xtick_dt', help='xtick_dt', required=False, type=float)
parser.add_argument('--xlabel', help='xlabel', required=False)
parser.add_argument('--ylabels', help='ylabels', required=False, type=au.str_arr_type)
parser.add_argument('--xticklabels', help='xticklabels', required=False, type=au.str_arr_type)
parser.add_argument('--ylim', help='ylim', required=False, type=au.float_arr_type)
parser.add_argument('--do_show', help='do_show', required=False, type=au.is_true, default=0)
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser))
args.xticklabels = au.str_arr_to_markers(args, 'xticklabels')
print(args)
n_jobs = utils.get_n_jobs(args.n_jobs)
# fol = '/home/noam/Pictures/mmvt/mg99'
# fol = '/homes/5/npeled/space1/Pictures/mmvt/stim/mg99/lvf6_5'
# fol2 = ''
# data_to_show_in_graph = 'stim'
# video_fname = 'mg99_LVF6-5_stim.mp4'
# cb_title = 'Electrodes PSD'
# ylabels = ['Electrodes PSD']
# time_range = np.arange(-1, 1.5, 0.01)
# xticks = [-1, -0.5, 0, 0.5, 1]
# xticklabels = [(-1, 'stim onset'), (0, 'end of stim')]
# ylim = (0, 500)
# xlabel = 'Time(s)'
# cb_data_type = 'stim'
# cb_min_max_eq = False
def read_cmd_args(argv=None):
import argparse
from src.utils import args_utils as au
parser = argparse.ArgumentParser(description='MMVT stim preprocessing')
parser.add_argument('-s',
'--subject',
help='subject name',
required=True,
type=au.str_arr_type)
parser.add_argument('-c',
'--conditions',
help='conditions names',
required=False,
default='contrast',
type=au.str_arr_type)
parser.add_argument('-a',
'--atlas',
help='atlas name',
required=False,
default='aparc.DKTatlas40')
parser.add_argument('-f',
'--function',
help='function name',
required=False,
default='all',
type=au.str_arr_type)
parser.add_argument('--exclude',
help='functions not to run',
required=False,
default='',
type=au.str_arr_type)
parser.add_argument('--mat_fname',
help='matlab connection file name',
required=False,
default='')
parser.add_argument('--mat_field',
help='matlab connection field name',
required=False,
default='')
parser.add_argument('--labels_exclude',
help='rois to exclude',
required=False,
default='unknown,corpuscallosum',
type=au.str_arr_type)
parser.add_argument('--norm_by_percentile',
help='',
required=False,
default=1,
type=au.is_true)
parser.add_argument('--norm_percs',
help='',
required=False,
default='1,99',
type=au.int_arr_type)
parser.add_argument('--stat',
help='',
required=False,
default=STAT_DIFF,
type=int)
parser.add_argument('--windows',
help='',
required=False,
default=0,
type=int)
parser.add_argument('--t_max',
help='',
required=False,
default=0,
type=int)
parser.add_argument('--threshold_percentile',
help='',
required=False,
default=0,
type=int)
parser.add_argument('--threshold',
help='',
required=False,
default=0,
type=float)
parser.add_argument('--color_map', help='', required=False, default='jet')
parser.add_argument('--symetric_colors',
help='',
required=False,
default=1,
type=au.is_true)
parser.add_argument('--data_max',
help='',
required=False,
default=0,
type=float)
parser.add_argument('--data_min',
help='',
required=False,
default=0,
type=float)
parser.add_argument('--n_jobs', help='cpu num', required=False, default=-1)
args = utils.Bag(au.parse_parser(parser, argv))
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if len(args.conditions) == 1:
args.stat = STAT_AVG
print(args)
return args
label_name, label_time = line
label_pos = labels_dict.get(label_name, None)
if label_pos is not None:
dist_from_dipole = np.linalg.norm(dipole_pos - label_pos)
dists.append(dist_from_dipole)
else:
dist_from_dipole = -1
dists.append(np.nan)
output.append('{}: {} ({:.4f})'.format(label_name, label_time, dist_from_dipole))
for ind, dist in enumerate(dists):
if dist < dist_threshold:
output[ind] = '{} ***'.format(output[ind])
title = '{}: {} {:.4f} dist from outer skin: {:.4f} '.format(
dipole_name, closest_label, dists_min, dists_from_outer_skin)
utils.save_arr_to_file(output, output_fname, title)
if __name__ == '__main__':
subject = 'nmr01426'# 'nmr01391'
atlas = 'aparc.DKTatlas40' # 'laus125'
# dip_fname = op.join(MEG_DIR, subject, 'run3_Ictal.dip') # _ictal
dip_fname = '/autofs/space/frieda_003/users/valia/epilepsy_clin/6966926_1426/200618/1426_EPI_lang.dip'
# dip_fname = op.join(MEG_DIR, subject, 'EPI.dip') # _ictal
n_jobs = utils.get_n_jobs(20)
n_jobs = n_jobs if n_jobs > 0 else 4
print('jobs: {}'.format(n_jobs))
#plot_dipole(dip_fname, subject)
dipoles = parse_dip_file(dip_fname)
mri_dipoles = convert_dipoles_to_mri_space(subject, dipoles, overwrite=True)
# calc_distances_from_rois(subject)
calc_dipoles_rois(subject, atlas=atlas, overwrite=True, n_jobs=n_jobs)
def run_on_subjects(args, main_func, subjects_itr=None, subject_func=None):
if subjects_itr is None:
subjects_itr = args.subject
subjects_flags, subjects_errors = {}, {}
args.n_jobs = utils.get_n_jobs(args.n_jobs)
if args.necessary_files == '':
args.necessary_files = dict()
args.subject = decode_subjects(args.subject)
if 'sftp_password' not in args or args.sftp_password == '':
args.sftp_password = utils.get_sftp_password(
args.subject, SUBJECTS_DIR, args.necessary_files, args.sftp_username, args.overwrite_fs_files) \
if args.sftp else ''
set_default_args(args)
os.environ['SUBJECTS_DIR'] = SUBJECTS_DIR
for tup in subjects_itr:
subject = get_subject(tup, subject_func)
utils.make_dir(op.join(MMVT_DIR, subject, 'mmvt'))
remote_subject_dir = utils.build_remote_subject_dir(
args.remote_subject_dir, subject)
args.atlas = utils.get_real_atlas_name(args.atlas)
logging.info(args)
print(
'****************************************************************')
print('subject: {}, atlas: {}'.format(subject, args.atlas))
print('remote dir: {}'.format(remote_subject_dir))
print(
'****************************************************************')
os.environ['SUBJECT'] = subject
flags = dict()
try:
# if utils.should_run(args, 'prepare_subject_folder'):
# I think we always want to run this
# *) Prepare the local subject's folder
flags['prepare_subject_folder'] = prepare_subject_folder(
subject, remote_subject_dir, args)
if not flags['prepare_subject_folder'] and not args.ignore_missing:
ans = input('Do you wish to continue (y/n)? ')
if not au.is_true(ans):
continue
flags['prepare_subject_folder'] = True
flags = main_func(tup, remote_subject_dir, args, flags)
subjects_flags[subject] = flags
except:
subjects_errors[subject] = traceback.format_exc()
print('Error in subject {}'.format(subject))
print(traceback.format_exc())
errors = defaultdict(list)
ret = True
good_subjects, bad_subjects = [], []
logs_fol = utils.make_dir(op.join(MMVT_DIR, subject, 'logs'))
logging.basicConfig(filename=op.join(logs_fol, 'preproc.log'),
level=logging.DEBUG)
for subject, flags in subjects_flags.items():
print('subject {}:'.format(subject))
logging.info('subject {}:'.format(subject))
for flag_type, val in flags.items():
print('{}: {}'.format(flag_type, val))
logging.info('{}: {}'.format(flag_type, val))
if not val:
errors[subject].append(flag_type)
if len(errors) > 0:
ret = False
print('Errors:')
logging.info('Errors:')
for subject, error in errors.items():
print('{}: {}'.format(subject, error))
logging.info('{}: {}'.format(subject, error))
for subject in subjects_flags.keys():
if len(errors[subject]) == 0:
good_subjects.append(subject)
else:
bad_subjects.append(subject)
print('Good subjects:\n {}'.format(good_subjects))
logging.info('Good subjects:\n {}'.format(good_subjects))
print('Bad subjects:\n {}'.format(bad_subjects))
logging.info('Good subjects:\n {}'.format(good_subjects))
utils.write_list_to_file(
good_subjects, op.join(utils.get_logs_fol(), 'good_subjects.txt'))
utils.write_list_to_file(bad_subjects,
op.join(utils.get_logs_fol(), 'bad_subjects.txt'))
return ret
g = nx.from_numpy_matrix(con_t)
# x = nx.closeness_centrality(g)
x = nx.degree_centrality(g)
vals.append([x[k] for k in range(len(x))])
vals = np.array(vals)
return vals, times_chunk
def plot_values(subject, con_name, func_name, ma_win_size=10):
vals = np.load(op.join(MMVT_DIR, subject, 'connectivity', '{}_{}.npy'.format(con_name, func_name)))
# inds = np.argsort(np.max(vals, axis=1) - np.min(vals, axis=1))[::-1]
# vals = vals[inds[:10]]
# vals = utils.moving_avg(vals, ma_win_size)
t_axis = np.linspace(-2, 5, vals.shape[1])
# plt.plot(t_axis, np.diff(vals).T)
plt.plot(t_axis, vals.T)
plt.title('{} {}'.format(con_name, func_name))
plt.show()
if __name__ == '__main__':
n_jobs = utils.get_n_jobs(-5)
print('n_jobs: {}'.format(n_jobs))
subject = 'nmr00857'
func_name = 'degree_centrality' #, #'closeness_centrality' # 'clustering'
bands = dict(theta=[4, 8], alpha=[8, 15], beta=[15, 30], gamma=[30, 55], high_gamma=[65, 120])
for band_name in bands.keys():
con_name = 'meg_{}_mi'.format(band_name)
# plot_con(subject, con_name)
# calc_measures(subject, con_name, func_name, n_jobs)
plot_values(subject, con_name, func_name)
if __name__ == '__main__':
subject = os.environ['SUBJECT'] = '277S0203'
os.environ['SUBJECTS_DIR'] = SUBJECTS_DIR
sites = [
'131-NeuroBeh_ACH', '277-NDC', '800-Hoglund', '829-EmoryUniversity',
'960-VitalImaging'
]
months = [''] #, '_6', '_12']
atlas = 'aparc' # 'aparc.DKTatlas'
low_threshold, high_threshold = 0, 100
cortex_frac_threshold = 0.9
overwrite = True
print_only = False
do_plot = False
n_jobs = max(utils.get_n_jobs(30), 4)
print('n_jobs: {}'.format(n_jobs))
# read_hippocampus_volumes()
# calc_volume_fractions_all_subjects(subjects, site, overwrite, print_only)
params = []
for site in sites:
subjects = get_subjects(site)
good_subjects = preproc_anat(subjects, overwrite_files=False)
for sub_ind, subject in enumerate(good_subjects):
# utils.time_to_go(now, sub_ind, len(subjects), 1)
# get_labels_data(subject, atlas)
subjects_0_6_12_dirs = [
op.join(HOME_FOL, site, '{}{}'.format(subject, month))
for month in months if op.isdir(
