mne.viz.plot_cov

mne.viz.plot_cov(cov, info, exclude=(), colorbar=True, proj=False, show_svd=True, show=True, verbose=None)[source]

Plot Covariance data.

Parameters
covinstance of Covariance

The covariance matrix.

infodict

Measurement info.

excludelist of str | str

List of channels to exclude. If empty do not exclude any channel. If ‘bads’, exclude info[‘bads’].

colorbarbool

Show colorbar or not.

projbool

Apply projections or not.

show_svdbool

Plot also singular values of the noise covariance for each sensor type. We show square roots ie. standard deviations.

showbool

Show figure if True.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns
fig_covinstance of matplotlib.figure.Figure

The covariance plot.

fig_svdinstance of matplotlib.figure.Figure | None

The SVD spectra plot of the covariance.

See also

mne.compute_rank

Notes

For each channel type, the rank is estimated using mne.compute_rank().

Changed in version 0.19: Approximate ranks for each channel type are shown with red dashed lines.

Examples using mne.viz.plot_cov