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

Visualizing Evoked data

Compare evoked responses for different conditions

mne.viz.plot_evoked_topo#

Examples using mne.viz.plot_evoked_topo#

Examples using `mne.viz.plot_evoked_topo`#