data_tot, tt, triggers, ch_rec_list = dm.get_raw(n_triggers=params.classifier.n_classes) vv = np.zeros((data_tot.shape[0], 128)) for ii in range(data_tot.shape[0]): vv[ii,:] = data_tot[ii,0].mean(axis=0)
