eegprep.eeg_picard#

eegprep.eeg_picard(EEG, engine=None, posact='off', sortcomps='off', **kwargs)#

Perform ICA decomposition using Picard algorithm.

This function can use either a Python implementation or an EEGLAB (via MATLAB or Octave) implementation.

Parameters#

EEGdict: EEGLAB-like data structure.
engineobject, optional: MATLAB or Octave engine instance. If None (default), the Python implementation is used.
posactstr | bool, optional: If ‘on’ or True, normalize component signs so max(abs(activations)) is positive. Default is ‘off’.
sortcompsstr | bool, optional: If ‘on’ or True, sort components by descending activation variance. Default is ‘off’.
**kwargsdict: Additional keyword arguments to be passed to the Picard algorithm. For example, {‘maxiter’: 500}.