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neuralset.extractors.base.EventDetector

pydantic model neuralset.extractors.base.EventDetector

Extracts time-aligned extractors from event annotations.

Parameters:

• event_types (str) – the event type to detect (e.g., “Keystroke”).

• frequency (float) – sampling frequency in Hz.

• mode (str) – mode of labeling (“dense”, “start”, “center”, “duration”).

• allow_missing (bool) – if True, missing events are allowed without raising errors.

Fields:

• aggregation (Literal['sum'])

• allow_missing (bool)

• event_types (str)

• frequency (float)

• mode (Literal['dense', 'start', 'duration', 'center'])

field event_types: str = 'Event'

field frequency: float = 100.0

field mode: Literal['dense', 'start', 'duration', 'center'] = 'dense'

field allow_missing: bool = True

field aggregation: Literal['sum'] = 'sum'

requirements: tp.ClassVar[tuple[str, ...]] = ()

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