graduation

Object that implement Graduation criteria to move between different tasks in a protocol.

Classes:

`Graduation`([id])	Base Graduation object.
`Accuracy`([threshold, window])	Graduate stage based on percent accuracy over some window of trials.
`NTrials`(n_trials[, current_trial])	Graduate after doing n trials

class Graduation(id: str | None = None)[source]

Bases: Autopilot_Object

Base Graduation object.

All Graduation objects need to populate PARAMS, COLS, and define an update method.

Attributes:

`PARAMS`	list of parameters to be defined
`COLS`	list of any data columns that this object should be given.

Methods:

update(row)

Parameters:: :class:`~tables.tableextension.Row` -- Trial row

PARAMS = []

list of parameters to be defined

Type:: list

COLS = []

list of any data columns that this object should be given.

Type:: list

abstract update(row: Row)[source]

Parameters:: :class:`~tables.tableextension.Row` – Trial row

class Accuracy(threshold=0.75, window=500, **kwargs)[source]

Bases: Graduation

Graduate stage based on percent accuracy over some window of trials.

Parameters:

threshold (float) – Accuracy above this threshold triggers graduation
window (int) – number of trials to consider in the past.
**kwargs – should have ‘correct’ corresponding to the corrects/incorrects of the past.

Attributes:

`PARAMS`	list of parameters to be defined
`COLS`	list of any data columns that this object should be given.

Methods:

update(row)

Get 'correct' from the row object.

PARAMS = ['threshold', 'window']

list of parameters to be defined

Type:: list

COLS = ['correct']

list of any data columns that this object should be given.

Type:: list

update(row)[source]

Get ‘correct’ from the row object. If this trial puts us over the threshold, return True, else False.

Parameters:: row (Row) – Trial row
Returns:: Did we _graduate this time or not?
Return type:: bool

class NTrials(n_trials, current_trial=0, **kwargs)[source]

Bases: Graduation

Graduate after doing n trials

Variables:

counter (itertools.count) – Counts the trials.

Parameters:

n_trials (int) – Number of trials to _graduate after
current_trial (int) – If not starting from zero, start from here
**kwargs

Attributes:

PARAMS

list of parameters to be defined

Methods:

update(row)

If we're past n_trials in this trial, return True, else False.

PARAMS = ['n_trials', 'current_trial']

list of parameters to be defined

Type:: list

update(row)[source]

If we’re past n_trials in this trial, return True, else False.

Parameters:: row – ignored
Returns:: Did we _graduate or not?
Return type:: bool