eeglabio.epochs.export_set#

eeglabio.epochs.export_set(fname, data, sfreq, events, tmin, tmax, ch_names, event_id=None, ch_locs=None, annotations=None, ref_channels='common', precision='single')#

Export epoch data to EEGLAB’s .set format.

Parameters:

fnamestr: Name of the export file.
datanumpy.ndarray, shape (n_epochs, n_channels, n_samples): Data array containing epochs. Follows the same format as MNE Epochs’ data array.
sfreqint: sample frequency of data
eventsnumpy.ndarray, shape (n_events, 3): Event array, the first column contains the event time in samples, the second column contains the value of the stim channel immediately before the event/step, and the third column contains the event id. Follows the same format as MNE’s event arrays.
tminfloat: Start time (seconds) before event.
tmaxfloat: End time (seconds) after event.
ch_nameslist of str: Channel names.
event_iddict: Names of conditions corresponding to event ids (last column of events). If None, event names will default to string versions of the event ids.
ch_locsnumpy.ndarray, shape (n_channels, 3): Array containing channel locations in Cartesian coordinates (x, y, z)
annotationslist, shape (3, n_annotations): List containing three annotation subarrays: first array (str) is description/name, second array (float) is onset (starting time in seconds), third array (float) is duration (in seconds) This roughly follows MNE’s Annotations structure.
ref_channelslist of str | str: The name(s) of the channel(s) used to construct the reference, ‘average’ for average reference, or ‘common’ (default) when there’s no specific reference set. Note that this parameter is only used to inform EEGLAB of the existing reference, this method will not reference the data for you.
precision“single” or “double”: Precision of the exported data (specifically EEG.data in EEGLAB)