ibllib.io.extractors.training_trials

Functions

extract_all

Extract trials and wheel data.

Classes

`Choice`	Get the subject's choice in every trial.
`ContrastLR`	Get left and right contrasts from raw datafile.
`ErrorCueTriggerTimes`
`FeedbackTimes`	Get the times the water or error tone was delivered to the animal.
`FeedbackType`	Get the feedback that was delivered to subject.
`GoCueTimes`	Get trigger times of goCue from state machine.
`GoCueTriggerTimes`	Get trigger times of goCue from state machine.
`IncludedTrials`
`Intervals`	Trial start to trial end.
`ItiDuration`	Calculate duration of iti from state timestamps.
`ItiInTimes`
`PhasePosQuiescence`	Extracts stimulus phase, position and quiescence from Bpod data.
`ProbabilityLeft`
`RepNum`	Count the consecutive repeated trials.
`ResponseTimes`	Time (in absolute seconds from session start) when a response was recorded.
`RewardVolume`	Load reward volume delivered for each trial.
`StimFreezeTriggerTimes`
`StimOffTriggerTimes`
`StimOnOffFreezeTimes`	Extracts stim on / off and freeze times from Bpod BNC1 detected fronts
`StimOnTimes_deprecated`
`StimOnTriggerTimes`
`TrialType`
`TrialsTable`	Extracts the following into a table from Bpod raw data:

class FeedbackType(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get the feedback that was delivered to subject. Optional: saves _ibl_trials.feedbackType.npy

Checks in raw datafile for error and reward state. Will raise an error if more than one of the mutually exclusive states have been triggered.

Sets feedbackType to -1 if error state was triggered (applies to no-go) Sets feedbackType to +1 if reward state was triggered

save_names = '_ibl_trials.feedbackType.npy'

var_names = 'feedbackType'

class ContrastLR(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get left and right contrasts from raw datafile. Optionally, saves _ibl_trials.contrastLeft.npy and _ibl_trials.contrastRight.npy to alf folder.

Uses signed_contrast to create left and right contrast vectors.

save_names = ('_ibl_trials.contrastLeft.npy', '_ibl_trials.contrastRight.npy')

var_names = ('contrastLeft', 'contrastRight')

class ProbabilityLeft(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

save_names = '_ibl_trials.probabilityLeft.npy'

var_names = 'probabilityLeft'

class Choice(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get the subject’s choice in every trial. Optional: saves _ibl_trials.choice.npy to alf folder.

Uses signed_contrast and trial_correct. -1 is a CCW turn (towards the left) +1 is a CW turn (towards the right) 0 is a no_go trial If a trial is correct the choice of the animal was the inverse of the sign of the position.

>>> choice[t] = -np.sign(position[t]) if trial_correct[t]

save_names = '_ibl_trials.choice.npy'

var_names = 'choice'

class RepNum(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Count the consecutive repeated trials. Optional: saves _ibl_trials.repNum.npy to alf folder.

Creates trial_repeated from trial[‘contrast’][‘type’] == ‘RepeatContrast’

>>> trial_repeated = [0, 1, 1, 0, 1, 0, 1, 1, 1, 0]
>>> repNum =         [0, 1, 2, 0, 1, 0, 1, 2, 3, 0]

save_names = '_ibl_trials.repNum.npy'

var_names = 'repNum'

class RewardVolume(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Load reward volume delivered for each trial. Optional: saves _ibl_trials.rewardVolume.npy

Uses reward_current to accumulate the amount of

save_names = '_ibl_trials.rewardVolume.npy'

var_names = 'rewardVolume'

class FeedbackTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get the times the water or error tone was delivered to the animal. Optional: saves _ibl_trials.feedback_times.npy

Gets reward and error state init times vectors, checks if theintersection of nans is empty, then merges the 2 vectors.

save_names = '_ibl_trials.feedback_times.npy'

var_names = 'feedback_times'

static get_feedback_times_lt5(session_path, data=False)[source]

static get_feedback_times_ge5(session_path, data=False)[source]

class Intervals(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Trial start to trial end. Trial end includes 1 or 2 seconds after feedback, (depending on the feedback) and 0.5 seconds of iti. Optional: saves _ibl_trials.intervals.npy

Uses the corrected Trial start and Trial end timestamp values form PyBpod.

save_names = '_ibl_trials.intervals.npy'

var_names = 'intervals'

class ResponseTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Time (in absolute seconds from session start) when a response was recorded. Optional: saves _ibl_trials.response_times.npy

Uses the timestamp of the end of the closed_loop state.

save_names = '_ibl_trials.response_times.npy'

var_names = 'response_times'

class ItiDuration(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Calculate duration of iti from state timestamps. Optional: saves _ibl_trials.iti_duration.npy

Uses Trial end timestamp and get_response_times to calculate iti.

save_names = '_ibl_trials.itiDuration.npy'

var_names = 'iti_dur'

class GoCueTriggerTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get trigger times of goCue from state machine.

Current software solution for triggering sounds uses PyBpod soft codes. Delays can be in the order of 10’s of ms. This is the time when the command to play the sound was executed. To measure accurate time, either getting the sound onset from xonar soundcard sync pulse (latencies may vary).

save_names = '_ibl_trials.goCueTrigger_times.npy'

var_names = 'goCueTrigger_times'

class TrialType(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

save_names = '_ibl_trials.type.npy'

var_name = 'trial_type'

class GoCueTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Get trigger times of goCue from state machine.

Current software solution for triggering sounds uses PyBpod soft codes. Delays can be in the order of 10-100s of ms. This is the time when the command to play the sound was executed. To measure accurate time, either getting the sound onset from the future microphone OR the new xonar soundcard and setup developed by Sanworks guarantees a set latency (in testing).

save_names = '_ibl_trials.goCue_times.npy'

var_names = 'goCue_times'

class IncludedTrials(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

save_names = '_ibl_trials.included.npy'

var_names = 'included'

static get_included_trials_lt5(data=False)[source]

static get_included_trials_ge5(data=False, settings=False)[source]

class ItiInTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

var_names = 'itiIn_times'

class ErrorCueTriggerTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

var_names = 'errorCueTrigger_times'

class StimFreezeTriggerTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

var_names = 'stimFreezeTrigger_times'

class StimOffTriggerTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

var_names = 'stimOffTrigger_times'

class StimOnTriggerTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

save_names = '_ibl_trials.stimOnTrigger_times.npy'

var_names = 'stimOnTrigger_times'

class StimOnTimes_deprecated(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

save_names = '_ibl_trials.stimOn_times.npy'

var_names = 'stimOn_times'

static get_stimOn_times_ge5(session_path, data=False)[source]: Find first and last stim_sync pulse of the trial. stimOn_times should be the first after the stim_on state. (Stim updates are in BNC1High and BNC1Low - frame2TTL device) Check that all trials have frame changes. Find length of stim_on_state [start, stop]. If either check fails the HW device failed to detect the stim_sync square change Substitute that trial’s missing or incorrect value with a NaN. return stimOn_times

static get_stimOn_times_lt5(session_path, data=False)[source]: Find the time of the statemachine command to turn on hte stim (state stim_on start or rotary_encoder_event2) Find the next frame change from the photodiodeafter that TS. Screen is not displaying anything until then. (Frame changes are in BNC1High and BNC1Low)

class StimOnOffFreezeTimes(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Extracts stim on / off and freeze times from Bpod BNC1 detected fronts

save_names = ('_ibl_trials.stimOn_times.npy', None, None)

var_names = ('stimOn_times', 'stimOff_times', 'stimFreeze_times')

class PhasePosQuiescence(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Extracts stimulus phase, position and quiescence from Bpod data. For extraction of pre-generated events, use the ProbaContrasts extractor instead.

save_names = (None, None, None)

var_names = ('phase', 'position', 'quiescence')

class TrialsTable(session_path=None)[source]

Bases: BaseBpodTrialsExtractor

Extracts the following into a table from Bpod raw data:: intervals, goCue_times, response_times, choice, stimOn_times, contrastLeft, contrastRight, feedback_times, feedbackType, rewardVolume, probabilityLeft, firstMovement_times
Additionally extracts the following wheel data:: wheel_timestamps, wheel_position, wheel_moves_intervals, wheel_moves_peak_amplitude

save_names = ('_ibl_trials.table.pqt', None, None, '_ibl_wheel.timestamps.npy', '_ibl_wheel.position.npy', '_ibl_wheelMoves.intervals.npy', '_ibl_wheelMoves.peakAmplitude.npy', None, None)

var_names = ('table', 'stimOff_times', 'stimFreeze_times', 'wheel_timestamps', 'wheel_position', 'wheel_moves_intervals', 'wheel_moves_peak_amplitude', 'peakVelocity_times', 'is_final_movement')

extract_all(session_path, save=False, bpod_trials=None, settings=None)[source]

Extract trials and wheel data.

For task versions >= 5.0.0, outputs wheel data and trials.table dataset (+ some extra datasets)

Parameters

session_path (str, pathlib.Path) – The path to the session
save (bool) – If true save the data files to ALF
bpod_trials (list of dicts) – The Bpod trial dicts loaded from the _iblrig_taskData.raw dataset
settings (dict) – The Bpod settings loaded from the _iblrig_taskSettings.raw dataset

Return type

A list of extracted data and a list of file paths if save is True (otherwise None)