mne.beamformer.
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)¶Linearly Constrained Minimum Variance (LCMV) beamformer.
Compute Linearly Constrained Minimum Variance (LCMV) beamformer on single trial data.
NOTE : This implementation has not been heavily tested so please report any issue or suggestions.
Parameters:  epochs : Epochs
forward : dict
noise_cov : Covariance
data_cov : Covariance
reg : float
label : Label
pick_ori : None  ‘normal’  ‘maxpower’
return_generator : bool
picks : arraylike of int
rank : None  int  dict
verbose : bool, str, int, or None


Returns:  stc: list  generator of (SourceEstimate  VolSourceEstimate) :

Notes
The original reference is: Van Veen et al. Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. Biomedical Engineering (1997) vol. 44 (9) pp. 867–880
The reference for finding the maxpower orientation is: Sekihara et al. Asymptotic SNR of scalar and vector minimumvariance beamformers for neuromagnetic source reconstruction. Biomedical Engineering (2004) vol. 51 (10) pp. 1726–34