def make_chunks(physiological_file_id, config_file, verbose):
"""
Call the function create_chunks_for_visualization of the Physiology class on
the PhysiologicalFileID provided as argument to this function.
:param physiological_file_id: PhysiologicalFileID of the file to chunk
:type physiological_file_id: int
:param config_file: path to the config file with database connection information
:type config_file: str
:param verbose : flag for more printing if set
:type verbose : bool
"""
# database connection
db = Database(config_file.mysql, verbose)
db.connect()
# grep config settings from the Config module
data_dir = db.get_config('dataDirBasepath')
# making sure that there is a final / in data_dir
data_dir = data_dir if data_dir.endswith('/') else data_dir + "/"
# load the Physiological object
physiological = Physiological(db, verbose)
# create the chunked dataset
if physiological.grep_file_path_from_file_id(physiological_file_id):
print('Chunking physiological file ID ' + str(physiological_file_id))
physiological.create_chunks_for_visualization(physiological_file_id,
data_dir)
def register_raw_data(self):
"""
Registers raw EEG data and related files into the following tables:
- physiological_file
- physiological_parameter_file
- physiological_electrode
- physiological_channel
- physiological_task_event
"""
# insert EEG file
inserted_eeg = self.fetch_and_insert_eeg_file()
eeg_file_id = inserted_eeg['file_id']
eeg_file_path = inserted_eeg['eeg_path']
# insert related electrode, channel and event information
electrode_file_path = self.fetch_and_insert_electrode_file(eeg_file_id)
channel_file_path = self.fetch_and_insert_channel_file(eeg_file_id)
event_file_path = self.fetch_and_insert_event_file(eeg_file_id)
# grep the path to the fdt file is present in
# physiological_parameter_file for that PhysiologicalFileID
physiological = Physiological(self.db, self.verbose)
results = physiological.grep_parameter_value_from_file_id(
eeg_file_id, 'fdt_file')
fdt_file_path = results['Value'] if results else None
# archive all files in a tar ball for downloading all files at once
files_to_archive = (self.data_dir + eeg_file_path, )
if electrode_file_path:
files_to_archive = files_to_archive + (self.data_dir +
electrode_file_path, )
if fdt_file_path: # add the fdt file path to the tuple if present
files_to_archive = files_to_archive + (self.data_dir +
fdt_file_path, )
if event_file_path:
files_to_archive = files_to_archive + (self.data_dir +
event_file_path, )
if channel_file_path:
files_to_archive = files_to_archive + (self.data_dir +
channel_file_path, )
archive_rel_name = os.path.splitext(eeg_file_path)[0] + ".tgz"
self.create_and_insert_archive(files_to_archive, archive_rel_name,
eeg_file_id)
# create data chunks for React visualization in
# data_dir/bids_import/bids_dataset_name_BIDSVersion_chunks directory
physiological.create_chunks_for_visualization(eeg_file_id,
self.data_dir)