ActivationFunction

class spidet.domain.ActivationFunction.ActivationFunction(label: str, unique_id: str, times: ndarray[dtype[float]], data_array: ndarray[dtype[float]], detected_events_on: ndarray[dtype[int]], detected_events_off: ndarray[dtype[int]], event_threshold: float)

This class represents the activation levels of a given EEG metapattern (i.e., a BasisFunction) in the time domain and contains periods of abnormal EEG activity, represented as detected events (see DetectedEvent).

Attributes:

label: str

The label of the ActivationFunction; the label of a given ActivationFunction contains the row index in the \(H\) matrix prefixed by a capital H.

unique_id: str

times: numpy.ndarray[numpy.dtype[float]]

An array containing the timestamps of each data point

data_array: numpy.ndarray[numpy.dtype[float]]

An array containing the activation level at each point in time

detected_events_on: numpy.ndarray[numpy.dtype[int]]

An array with the indices in the data array corresponding to the onsets of the detected events.

detected_events_off: numpy.ndarray[numpy.dtype[int]]

An array with the indices in the data array corresponding to the offsets of the detected events.

event_threshold: float

the threshold used for the computation of the detected events.

get_detected_events() → List[DetectedEvent]

Returns a list of DetectedEvent objects representing the computed events detected on the given ActivationFunction.

get_event_mask()

Returns a binary numpy array indicating the indices of all detected events of the given ActivationFunction.

get_sub_period(offset: float, duration: float) → ndarray[dtype[float]]

Computes a sub period of the ActivationFunction.

Parameters:

offset: float

Offset from the start of the recording in seconds.

duration: float

Duration of the sub period in seconds.

Returns:

numpy.ndarray[numpy.dtype[float]]

Array containing the data points within the defined sub period.