Plot Covariance data.
Covariance
The covariance matrix.
mne.Info
The mne.Info
object with information about the sensors and methods of measurement.
list
of str
| str
List of channels to exclude. If empty do not exclude any channel. If ‘bads’, exclude info[‘bads’].
Show colorbar or not.
Apply projections or not.
Plot also singular values of the noise covariance for each sensor type. We show square roots ie. standard deviations.
Show figure if True.
str
| int
| None
Control verbosity of the logging output. If None
, use the default
verbosity level. See the logging documentation and
mne.verbose()
for details. Should only be passed as a keyword
argument.
matplotlib.figure.Figure
The covariance plot.
matplotlib.figure.Figure
| None
The SVD spectra plot of the covariance.
See also
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.
mne.viz.plot_cov
#Source localization with MNE, dSPM, sLORETA, and eLORETA
Compute evoked ERS source power using DICS, LCMV beamformer, and dSPM
Compute source power estimate by projecting the covariance with MNE