def task_eeg_to_bids():
"""Step 00: Bring data set into a BIDS compliant directory structure."""
# Run the script for each subject in a sub-task.
for subject in subjects:
yield dict(
# This task should come after `task_check`
task_dep=['check'],
# A name for the sub-task: set to the name of the subject
name=subject,
# If any of these files change, the script needs to be re-run. Make
# sure that the script itself is part of this list!
file_dep=[fname.source(subject=subject,
source_type='eeg'),
fname.source(subject=subject,
source_type='demographics'),
'00_eeg_to_bids.py'],
# The files produced by the script
targets=[fname.bids_data(subject=subject)],
# How the script needs to be called. Here we indicate it should
# have one command line parameter: the name of the subject.
actions=['python 00_eeg_to_bids.py %s' % subject]
)
# All parameters are defined in config.py
from config import fname, task_name, montage, parser, LoggingFormat
###############################################################################
# Start processing step
# Handle command line arguments
args = parser.parse_args()
subject = args.subject
print(LoggingFormat.PURPLE + LoggingFormat.BOLD +
'Converting to BIDS: Subject %s' % subject + LoggingFormat.END)
###############################################################################
# 1) Import the data
input_file = fname.source(source_type='eeg', subject=subject)
raw = read_raw_bdf(input_file, preload=False)
# sampling rate
sfreq = raw.info['sfreq']
# channels in dataset
channels = raw.info['ch_names']
###############################################################################
# 2) Modify dataset info
# identify channel types based on matching names in montage
types = []
for channel in channels:
if channel in montage.ch_names:
types.append('eeg')
elif channel.startswith('EOG') | channel.startswith('EXG'):
# Handle command line arguments
args = parser.parse_args()
subject = args.subject
session = args.session
task = args.task
print(LoggingFormat.PURPLE + LoggingFormat.BOLD +
'Bad channel detection for subject %s (%s)' % (subject, task) +
LoggingFormat.END)
##############################################################################
# 1) import the data
# name of the file
input_file = fname.source(subject=subject, task=task, data_type='eeg')
# bids-formatted path to data
bids_path = BIDSPath(subject=str(subject).rjust(3, '0'),
task=task,
root=output_bids,
extension='.vhdr')
# check if file exists, otherwise terminate the script
if not os.path.isfile(input_file):
exit()
# import existing file
# raw = read_raw_brainvision(input_file, preload=True)
raw = read_raw_bids(bids_path, extra_params=dict(preload=True))
raw.set_montage(montage)
LoggingFormat
###############################################################################
# Start processing step
# Handle command line arguments
args = parser.parse_args()
subject = args.subject
print(LoggingFormat.PURPLE +
LoggingFormat.BOLD +
'Converting subject %s to BIDS' % subject +
LoggingFormat.END)
# Subject information (e.g., age, sex)
demo_path = fname.source(source_type='demographics',
subject=subject)
demo = pd.read_csv(demo_path, sep='\t', header=0)
###############################################################################
input_file = fname.source(source_type='eeg',
subject=subject)
# 1) Import the data
raw = read_raw_bdf(input_file,
preload=False)
# sampling rate
sfreq = raw.info['sfreq']
# channels in dataset
channels = raw.info['ch_names']