mne.read_cov#
- mne.read_cov(fname, verbose=None)[source]#
Read a noise covariance from a FIF file.
- Parameters:
- fnamepath-like
The path-like of file containing the covariance matrix. It should end with
-cov.fif
or-cov.fif.gz
.- verbosebool |
str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- Returns:
- cov
Covariance
The noise covariance matrix.
- cov
See also
Examples using mne.read_cov
#
![](../_images/sphx_glr_35_dipole_orientations_thumb.png)
The role of dipole orientations in distributed source localization
![](../_images/sphx_glr_css_thumb.png)
Cortical Signal Suppression (CSS) for removal of cortical signals
![](../_images/sphx_glr_gamma_map_inverse_thumb.png)
Compute a sparse inverse solution using the Gamma-MAP empirical Bayesian method
![](../_images/sphx_glr_mixed_norm_inverse_thumb.png)
Compute sparse inverse solution with mixed norm: MxNE and irMxNE
![](../_images/sphx_glr_mixed_source_space_inverse_thumb.png)
Compute MNE inverse solution on evoked data with a mixed source space
![](../_images/sphx_glr_multi_dipole_model_thumb.png)
Computing source timecourses with an XFit-like multi-dipole model
![](../_images/sphx_glr_psf_ctf_vertices_thumb.png)
Plot point-spread functions (PSFs) and cross-talk functions (CTFs)
![](../_images/sphx_glr_resolution_metrics_thumb.png)
Compute spatial resolution metrics in source space
![](../_images/sphx_glr_resolution_metrics_eegmeg_thumb.png)
Compute spatial resolution metrics to compare MEG with EEG+MEG