mne.read_cov¶

mne.read_cov(fname, verbose=None)[source]¶

Read a noise covariance from a FIF file.

Parameters:	fname : string The name of file containing the covariance matrix. It should end with -cov.fif or -cov.fif.gz. verbose : bool, str, int, or None (default None) If not None, override default verbose level (see `mne.verbose()` and Logging documentation for more).
Returns:	cov : Covariance The noise covariance matrix.

See also

write_cov, compute_covariance, compute_raw_covariance

Examples using `mne.read_cov`¶

../_images/sphx_glr_plot_mixed_source_space_connectivity_thumb.png

Compute mixed source space connectivity and visualize it using a circular graph

../_images/sphx_glr_plot_decoding_spatio_temporal_source_thumb.png

Decoding source space data

../_images/sphx_glr_plot_rap_music_thumb.png

Compute Rap-Music on evoked data

../_images/sphx_glr_plot_gamma_map_inverse_thumb.png

Compute a sparse inverse solution using the Gamma-Map empirical Bayesian method

../_images/sphx_glr_plot_mixed_norm_inverse_thumb.png

Compute sparse inverse solution with mixed norm: MxNE and irMxNE

../_images/sphx_glr_plot_time_frequency_mixed_norm_inverse_thumb.png

Compute MxNE with time-frequency sparse prior

../_images/sphx_glr_plot_mixed_source_space_inverse_thumb.png

Compute MNE inverse solution on evoked data in a mixed source space

../_images/sphx_glr_plot_custom_inverse_solver_thumb.png

Source localization with a custom inverse solver

../_images/sphx_glr_plot_read_noise_covariance_matrix_thumb.png

Reading/Writing a noise covariance matrix

../_images/sphx_glr_plot_simulate_evoked_data_thumb.png

Generate simulated evoked data

../_images/sphx_glr_plot_mne_solutions_thumb.png

Computing various MNE solutions

../_images/sphx_glr_plot_dipole_orientations_thumb.png

The role of dipole orientations in distributed source localization