mne.viz.plot_evoked_topo#

mne.viz.plot_evoked_topo(evoked, layout=None, layout_scale=0.945, color=None, border='none', ylim=None, scalings=None, title=None, proj=False, vline=[0.0], fig_background=None, merge_grads=False, legend=True, axes=None, background_color='w', noise_cov=None, exclude='bads', show=True)[source]#

Plot 2D topography of evoked responses.

Clicking on the plot of an individual sensor opens a new figure showing the evoked response for the selected sensor.

Parameters
evokedlist of Evoked | Evoked

The evoked response to plot.

layoutinstance of Layout | None

Layout instance specifying sensor positions (does not need to be specified for Neuromag data). If possible, the correct layout is inferred from the data.

layout_scalefloat

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

colorlist of color | color | None

Everything matplotlib accepts to specify colors. If not list-like, the color specified will be repeated. If None, colors are automatically drawn.

borderstr

Matplotlib borders style to be used for each sensor plot.

ylimdict | None

Y limits for plots (after scaling has been applied). The value determines the upper and lower subplot limits. e.g. ylim = dict(eeg=[-20, 20]). Valid keys are eeg, mag, grad, misc. If None, the ylim parameter for each channel type is determined by the minimum and maximum peak.

scalingsdict | None

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

titlestr

Title of the figure.

projbool | ‘interactive’

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

vlinelist of float | None

The values at which to show a vertical line.

fig_backgroundNone | ndarray

A background image for the figure. This must work with a call to plt.imshow. Defaults to None.

merge_gradsbool

Whether to use RMS value of gradiometer pairs. Only works for Neuromag data. Defaults to False.

legendbool | int | str | tuple

If True, create a legend based on evoked.comment. If False, disable the legend. Otherwise, the legend is created and the parameter value is passed as the location parameter to the matplotlib legend call. It can be an integer (e.g. 0 corresponds to upper right corner of the plot), a string (e.g. ‘upper right’), or a tuple (x, y coordinates of the lower left corner of the legend in the axes coordinate system). See matplotlib documentation for more details.

axesinstance of matplotlib Axes | None

Axes to plot into. If None, axes will be created.

background_colorcolor

Background color. Typically ‘k’ (black) or ‘w’ (white; default).

New in version 0.15.0.

noise_covinstance of Covariance | str | None

Noise covariance used to whiten the data while plotting. Whitened data channel names are shown in italic. Can be a string to load a covariance from disk.

New in version 0.16.0.

excludelist of str | ‘bads’

Channels names to exclude from the plot. If ‘bads’, the bad channels are excluded. By default, exclude is set to ‘bads’.

showbool

Show figure if True.

Returns
figinstance of matplotlib.figure.Figure

Images of evoked responses at sensor locations.

Examples using mne.viz.plot_evoked_topo#

Preprocessing functional near-infrared spectroscopy (fNIRS) data

Preprocessing functional near-infrared spectroscopy (fNIRS) data

Preprocessing functional near-infrared spectroscopy (fNIRS) data
Visualizing Evoked data

Visualizing Evoked data

Visualizing Evoked data
Compare evoked responses for different conditions

Compare evoked responses for different conditions

Compare evoked responses for different conditions