mne.viz.plot_topo_image_epochs(epochs, layout=None, sigma=0.0, vmin=None, vmax=None, colorbar=True, order=None, cmap='RdBu_r', layout_scale=0.95, title=None, scalings=None, border='none', fig_facecolor='k', fig_background=None, font_color='w', show=True)

Plot Event Related Potential / Fields image on topographies


epochs : instance of Epochs

The epochs.

layout: instance of Layout

System specific sensor positions.

sigma : float

The standard deviation of the Gaussian smoothing to apply along the epoch axis to apply in the image. If 0., no smoothing is applied.

vmin : float

The min value in the image. The unit is uV for EEG channels, fT for magnetometers and fT/cm for gradiometers.

vmax : float

The max value in the image. The unit is uV for EEG channels, fT for magnetometers and fT/cm for gradiometers.

colorbar : bool

Display or not a colorbar.

order : None | array of int | callable

If not None, order is used to reorder the epochs on the y-axis of the image. If it’s an array of int it should be of length the number of good epochs. If it’s a callable the arguments passed are the times vector and the data as 2d array (data.shape[1] == len(times)).

cmap : instance of matplotlib.pyplot.colormap

Colors to be mapped to the values.

layout_scale: float

scaling factor for adjusting the relative size of the layout on the canvas.

title : str

Title of the figure.

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).

border : str

matplotlib borders style to be used for each sensor plot.

fig_facecolor : str | obj

The figure face color. Defaults to black.

fig_background : None | array

A background image for the figure. This must be a valid input to matplotlib.pyplot.imshow. Defaults to None.

font_color : str | obj

The color of tick labels in the colorbar. Defaults to white.

show : bool

Show figure if True.


fig : instance of matplotlib figure

Figure distributing one image per channel across sensor topography.