def from_path(session_path, force=False, save=True):
"""
Extract a session from full ALF path (ex: '/scratch/witten/ibl_witten_01/2018-12-18/001')
:param force: (False) overwrite existing files
:param save: (True) boolean or list of ALF file names to extract
:return: None
"""
logger_.info('Extracting ' + str(session_path))
extractor_type = extractors_exist(session_path)
if is_extracted(session_path) and not force:
logger_.info(f"Session {session_path} already extracted.")
return
if extractor_type == 'training':
settings, data = raw.load_bpod(session_path)
logger_.info('training session on ' + settings['PYBPOD_BOARD'])
training_trials.extract_all(session_path, data=data, save=save)
training_wheel.extract_all(session_path, bp_data=data, save=save)
logger_.info('session extracted \n') # timing info in log
if extractor_type == 'biased':
settings, data = raw.load_bpod(session_path)
logger_.info('biased session on ' + settings['PYBPOD_BOARD'])
biased_trials.extract_all(session_path, data=data, save=save)
biased_wheel.extract_all(session_path, bp_data=data, save=save)
logger_.info('session extracted \n') # timing info in log
if extractor_type == 'ephys':
data = raw.load_data(session_path)
ephys_trials.extract_all(session_path, data=data, save=save)
ephys_fpga.extract_all(session_path, save=save)
def from_path(session_path, force=False, save=True):
"""
Extract a session from full ALF path (ex: '/scratch/witten/ibl_witten_01/2018-12-18/001')
:param force: (False) overwrite existing files
:param save: (True) boolean or list of ALF file names to extract
:return: None
"""
extractor_type = get_session_extractor_type(session_path)
logger_.info(f"Extracting {session_path} as {extractor_type}")
if is_extracted(session_path) and not force:
logger_.info(f"Session {session_path} already extracted.")
return
if extractor_type == 'training':
settings, data = rawio.load_bpod(session_path)
logger_.info('training session on ' + settings['PYBPOD_BOARD'])
training_trials.extract_all(session_path, data=data, save=save)
training_wheel.extract_all(session_path, bp_data=data, save=save)
logger_.info('session extracted \n') # timing info in log
if extractor_type == 'biased':
settings, data = rawio.load_bpod(session_path)
logger_.info('biased session on ' + settings['PYBPOD_BOARD'])
biased_trials.extract_all(session_path, data=data, save=save)
biased_wheel.extract_all(session_path, bp_data=data, save=save)
logger_.info('session extracted \n') # timing info in log
if extractor_type == 'ephys':
data = rawio.load_data(session_path)
logger_.info('extract BPOD for ephys session')
ephys_trials.extract_all(session_path, data=data, save=save)
logger_.info('extract FPGA information for ephys session')
tmax = data[-1]['behavior_data']['States timestamps']['exit_state'][0][-1] + 60
ephys_fpga.extract_all(session_path, save=save, tmax=tmax)
if extractor_type == 'sync_ephys':
ephys_fpga.extract_sync(session_path, save=save)
def extract_all(session_path, save=True, bpod_trials=None, settings=None):
"""
Extracts a training session from its path. NB: Wheel must be extracted first in order to
extract trials.firstMovement_times.
:param session_path: the path to the session to be extracted
:param save: if true a subset of the extracted data are saved as ALF
:param bpod_trials: list of Bpod trial data
:param settings: the Bpod session settings
:return: trials: Bunch/dict of trials
:return: wheel: Bunch/dict of wheel positions
:return: out_Files: list of output files
"""
extractor_type = ibllib.io.extractors.base.get_session_extractor_type(
session_path)
_logger.info(f"Extracting {session_path} as {extractor_type}")
bpod_trials = bpod_trials or rawio.load_data(session_path)
settings = settings or rawio.load_settings(session_path)
if extractor_type == 'training':
_logger.info('training session on ' + settings['PYBPOD_BOARD'])
wheel, files_wheel = training_wheel.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
trials, files_trials = training_trials.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
elif extractor_type == 'biased' or extractor_type == 'ephys':
_logger.info('biased session on ' + settings['PYBPOD_BOARD'])
wheel, files_wheel = training_wheel.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
trials, files_trials = biased_trials.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
elif extractor_type == 'habituation':
from ibllib.misc import version
_logger.info('habituation session on ' + settings['PYBPOD_BOARD'])
if version.le(settings['IBLRIG_VERSION_TAG'], '5.0.0'):
_logger.warning("No extraction of legacy habituation sessions")
return None, None, None
trials, files_trials = habituation_trials.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
wheel = None
files_wheel = []
else:
raise ValueError(f"No extractor for task {extractor_type}")
_logger.info('session extracted \n') # timing info in log
return trials, wheel, (files_trials + files_wheel) if save else None
def extract_training(session_path, save=True):
"""
Extracts a training session from its path. NB: Wheel must be extracted first in order to
extract trials.firstMovement_times.
:param session_path:
:param save:
:return: trials: Bunch/dict of trials
:return: wheel: Bunch/dict of wheel positions
:return: out_Files: list of output files
"""
extractor_type = rawio.get_session_extractor_type(session_path)
_logger.info(f"Extracting {session_path} as {extractor_type}")
settings, bpod_trials = rawio.load_bpod(session_path)
if extractor_type == 'training':
_logger.info('training session on ' + settings['PYBPOD_BOARD'])
wheel, files_wheel = training_wheel.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
trials, files_trials = training_trials.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
elif extractor_type == 'biased':
_logger.info('biased session on ' + settings['PYBPOD_BOARD'])
wheel, files_wheel = training_wheel.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
trials, files_trials = biased_trials.extract_all(
session_path,
bpod_trials=bpod_trials,
settings=settings,
save=save)
else:
raise ValueError(f"No extractor for task {extractor_type}")
_logger.info('session extracted \n') # timing info in log
return trials, wheel, files_trials + files_wheel