@verbose
def lcmv_epochs(epochs, forward, noise_cov, data_cov, reg=0.01, label=None, pick_ori=None, return_generator=False, picks=None, rank=None, verbose=None):
 _check_reference(epochs)
 info = epochs.info
 tmin = epochs.times[0]
 picks = _setup_picks(picks, info, forward, noise_cov)
 data = epochs.get_data()[:, picks, :]
 stcs = _apply_lcmv(data=data, info=info, tmin=tmin, forward=forward, noise_cov=noise_cov, data_cov=data_cov, reg=reg, label=label, picks=picks, rank=rank, pick_ori=pick_ori)
 if (not return_generator):
  stcs = [s for s in stcs]
 return stcs

@ verbose def lcmv_epochs ( epochs , forward , noise_cov , data_cov , reg = 0.01 , label = None , pick_ori = None , return_generator = False , picks = None , rank = None , verbose = None ) : _check_reference ( epochs ) info = epochs . info tmin = epochs . times [ 0 ] picks = _setup_picks ( picks , info , forward , noise_cov ) data = epochs . get_data ( ) [ : , picks , : ] stcs = _apply_lcmv ( data = data , info = info , tmin = tmin , forward = forward , noise_cov = noise_cov , data_cov = data_cov , reg = reg , label = label , picks = picks , rank = rank , pick_ori = pick_ori ) if ( not return_generator ) : stcs = [ s for s in stcs ] return stcs
linearly constrained minimum variance beamformer .