mne.viz.plot_evoked_image(evoked, picks=None, exclude='bads', unit=True, show=True, clim=None, xlim='tight', proj=False, units=None, scalings=None, titles=None, axes=None, cmap='RdBu_r')

Plot evoked data as images


evoked : instance of Evoked

The evoked data

picks : array-like of int | None

The indices of channels to plot. If None show all.

exclude : list of str | ‘bads’

Channels names to exclude from being shown. If ‘bads’, the bad channels are excluded.

unit : bool

Scale plot with channel (SI) unit.

show : bool

Show figure if True.

clim : dict | None

clim for plots. e.g. clim = dict(eeg=[-200e-6, 200e6]) Valid keys are eeg, mag, grad, misc. If None, the clim parameter for each channel equals the pyplot default.

xlim : ‘tight’ | tuple | None

xlim for plots.

proj : bool | ‘interactive’

If true SSP projections are applied before display. If ‘interactive’, a check box for reversible selection of SSP projection vectors will be shown.

units : dict | None

The units of the channel types used for axes lables. If None, defaults to dict(eeg=’uV’, grad=’fT/cm’, mag=’fT’).

scalings : dict | None

The scalings of the channel types to be applied for plotting. If None,` defaults to dict(eeg=1e6, grad=1e13, mag=1e15).

titles : dict | None

The titles associated with the channels. If None, defaults to dict(eeg=’EEG’, grad=’Gradiometers’, mag=’Magnetometers’).

axes : instance of Axis | list | None

The axes to plot to. If list, the list must be a list of Axes of the same length as the number of channel types. If instance of Axes, there must be only one channel type plotted.

cmap : matplotlib colormap