WaterCalibration

class WaterCalibration[source]

Bases: Task

Task class for calibrating water delivery valves.

Methods

`__init__`()	Initializes the WaterCalibration task.
`after_trial`()	Executes logic after a trial completes.
`close`()	Cleanly closes the calibration task.
`concatenate_trial_data`()	Appends the current trial's data to the session DataFrame.
`create_paths`()	Sets up file and directory paths for the session.
`create_trial`()	Creates the state machine for a calibration trial.
`disconnect_and_save`(run_mode)	Stops the task, disconnects devices, and saves session data.
`do_trial`([send_to_cam])	Executes a single trial.
`get_name`()	Returns the name of the task class.
`get_trial_data`()	Retrieves and processes data from the last executed trial.
`register_default_values`()	Registers standard session metadata values (task, subject, system, date).
`register_value`(name, value)	Registers a custom value to be saved with the trial data.
`run`()	Runs the task in the main thread until completion or forced stop.
`run_in_thread`([daemon])	Runs the task in a separate background thread.
`save_csv`(run_mode)	Saves the session data to CSV files.
`save_json`(run_mode)	Saves the session settings to a JSON file.
`send_softcode_to_bpod`(code)	Sends a softcode to the Bpod device.
`start`()	Prepares the calibration task by defining states and output actions.
`transform`(df)	Transforms raw session data into a wide format suitable for analysis.

start() → None[source]: Prepares the calibration task by defining states and output actions.

create_trial() → None[source]

Creates the state machine for a calibration trial.

Adds states for each valve to be calibrated and a final wait state.

concatenate_trial_data() → None: Appends the current trial’s data to the session DataFrame.

disconnect_and_save(run_mode: str) → Tuple[Save, float, int, int, str]

Stops the task, disconnects devices, and saves session data.

Parameters:: run_mode (str) – The mode in which the task was run (e.g., “Manual”).
Returns:: A tuple containing the save status, session duration, number of trials, water consumed, and settings string.
Return type:: Tuple[Save, float, int, int, str]

do_trial(send_to_cam: bool = False) → None

Executes a single trial.

Initializes the state machine, runs it, collects data, and performs post-trial updates.

Parameters:: send_to_cam (bool, optional) – Whether to update the camera with the trial number. Defaults to False.

get_trial_data() → None

Retrieves and processes data from the last executed trial.

Extracts timestamps, events, and states from the Bpod session and updates self.trial_data.

register_default_values() → None: Registers standard session metadata values (task, subject, system, date).

register_value(name: str, value: Any) → None

Registers a custom value to be saved with the trial data.

Parameters:

run() → None: Runs the task in the main thread until completion or forced stop.

run_in_thread(daemon: bool = True) → None

Runs the task in a separate background thread.

Parameters:: daemon (bool, optional) – Whether to run as a daemon thread. Defaults to True.

save_csv(run_mode: str) → Tuple[float, int, int, bool]

Saves the session data to CSV files.

Processes raw data, saves raw and clean session files, and updates the subject’s cumulative data file.

save_json(run_mode: str) → str

Saves the session settings to a JSON file.

send_softcode_to_bpod(code: int) → None

Sends a softcode to the Bpod device.

transform(df: pandas.DataFrame) → pandas.DataFrame

Transforms raw session data into a wide format suitable for analysis.