sfreq = d['sfreq'] ch_names = layout.names print ch_names types = ['mag'] * len(ch_names) info = create_info(ch_names, sfreq, types) events = np.vstack(zip([125 for _ in xrange(len(labels))], [0 for _ in xrange(len(labels))], labels)) print events.shape #help(EpochsArray) ea = EpochsArray(data, info, events, tmin=d['tmin']) from mne.evoked import EvokedArray evoked = EvokedArray(data[labels==1].mean(axis=0), info, tmin=d['tmin']) print evoked print info times = np.arange(0.05, 0.15, 0.01) print len(info['ch_names']) evoked.plot_topomap(0.15, ch_type='mag', layout=layout, size=10, colorbar=False) #evoked.plot_topomap(times, ch_type='mag', layout=layout, size=10, colorbar=False) evoked = EvokedArray(data[labels==0].mean(axis=0), info, tmin=d['tmin']) evoked.plot_topomap(0.15, ch_type='mag', layout=layout, size=10, colorbar=False) #evoked.plot_topomap(times, ch_type='mag', layout=layout, size=10, colorbar=False) evoked = EvokedArray(data[labels==1].mean(axis=0) - data[labels==0].mean(axis=0), info, tmin=d['tmin']) evoked.plot_topomap(0.25, ch_type='mag', layout=layout, size=10, colorbar=False) # TODO use the EpochsArray
