mne_connectivity.viz.plot_sensors_connectivity#

mne_connectivity.viz.plot_sensors_connectivity(info, con, picks=None, cbar_label='Connectivity', n_con=20, cmap='RdBu')[source]#

Visualize the sensor connectivity in 3D.

Parameters:

infodict | None: The measurement info.
conarray, shape (n_channels, n_channels) | Connectivity: The computed connectivity measure(s).
picksstr | array_like | slice | None: Channels to include. Slices and lists of integers will be interpreted as channel indices. In lists, channel type strings (e.g., ['meg', 'eeg']) will pick channels of those types, channel name strings (e.g., ['MEG0111', 'MEG2623'] will pick the given channels. Can also be the string values 'all' to pick all channels, or 'data' to pick data channels. None (default) will pick good data channels. Note that channels in info['bads'] will be included if their names or indices are explicitly provided. Indices of selected channels.
cbar_labelstr: Label for the colorbar.
n_conint: Number of strongest connections shown. By default 20.
cmapstr | instance of matplotlib.colors.Colormap: Colormap for coloring connections by strength. If str, must be a valid Matplotlib colormap (i.e. a valid key of matplotlib.colormaps). Default is "RdBu".

Returns:

Examples using `mne_connectivity.viz.plot_sensors_connectivity`#