yasa.SpindlesResults#
- class yasa.SpindlesResults(events, data, sf, ch_names, hypno, data_filt)#
Output class for spindles detection.
- Attributes:
- _events
pandas.DataFrame Output detection dataframe
- _dataarray_like
Original EEG data of shape (n_chan, n_samples).
- _data_filtarray_like
Sigma-filtered EEG data of shape (n_chan, n_samples).
- _sffloat
Sampling frequency of data.
- _ch_nameslist
Channel names.
- _hypnoarray_like or None
Sleep staging vector.
- _events
- __init__(events, data, sf, ch_names, hypno, data_filt)#
Methods
__init__(events, data, sf, ch_names, hypno, ...)compare_channels([score, max_distance_sec])Compare detected spindles across channels.
compare_detection(other[, max_distance_sec, ...])Compare the detected spindles against either another YASA detection or against custom annotations (e.g. ground-truth human scoring).
get_coincidence_matrix([scaled])Return the (scaled) coincidence matrix.
get_mask()Return a boolean array indicating for each sample in data if this sample is part of a detected event (True) or not (False).
get_sync_events([center, time_before, ...])Return the raw or filtered data of each detected event after centering to a specific timepoint.
plot_average([center, hue, time_before, ...])Plot the average spindle.
plot_detection()Plot an overlay of the detected spindles on the EEG signal.
summary([grp_chan, grp_stage, mask, ...])Return a summary of the spindles detection, optionally grouped across channels and/or stage.