moabb.paradigms.p300.BaseP300#

class moabb.paradigms.p300.BaseP300(filters=([1, 24],), events=None, tmin=0.0, tmax=None, baseline=None, channels=None, resample=None, ignore_relabelling=False, scorer=None)[source]#

Base P300 paradigm.

Please use one of the child classes

Parameters:

filters (list of list (defaults [[1, 24]])) – bank of bandpass filter to apply.
ignore_relabelling (bool (default False)) – If True, ignore the relabelling of the events. This is useful for datasets where the events are already in the correct format.

property datasets#: Property that define the list of compatible datasets.

is_valid(dataset)[source]#

Verify the dataset is compatible with the paradigm.

This method is called to verify dataset is compatible with the paradigm.

This method should raise an error if the dataset is not compatible with the paradigm. This is for example the case if the dataset is an ERP dataset for motor imagery paradigm, or if the dataset does not contain any of the required events.

Parameters:: dataset (dataset instance) – The dataset to verify.

property scoring#: Property that defines scoring metric (e.g. ROC-AUC or accuracy or f-score), given as a sklearn-compatible string or a compatible sklearn scorer.