This documentation is for development version 0.18.dev0.


mne.make_ad_hoc_cov(info, std=None, verbose=None)[source]

Create an ad hoc noise covariance.

info : instance of Info

Measurement info.

std : dict of float | None

Standard_deviation of the diagonal elements. If dict, keys should be grad for gradiometers, mag for magnetometers and eeg for EEG channels. If None, default values will be used (see Notes).

verbose : bool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

cov : instance of Covariance

The ad hoc diagonal noise covariance for the M/EEG data channels.


The default noise values are 5 fT/cm, 20 fT, and 0.2 uV for gradiometers, magnetometers, and EEG channels respectively.

New in version 0.9.0.

Examples using mne.make_ad_hoc_cov