| Parameters: |
- noise_cov : Covariance
The noise covariance.
- info : dict
The measurement info.
- picks : str | list | slice | None
Channels to include. Slices and lists of integers will be
interpreted as channel indices. In lists, channel type strings
(e.g., ['meg', 'eeg']) will pick channels of those
types, channel name strings (e.g., ['MEG0111', 'MEG2623']
will pick the given channels. Can also be the string values
“all” to pick all channels, or “data” to pick data channels.
None (default) will pick good data channels(excluding reference MEG channels).
- rank : None | int | dict
Specified rank of the noise covariance matrix. If None, the rank is
detected automatically. If int, the rank is specified for the MEG
channels. A dictionary with entries ‘eeg’ and/or ‘meg’ can be used
to specify the rank for each modality.
- scalings : dict | None
The rescaling method to be applied. See documentation of
prepare_noise_cov for details.
- return_rank : bool
If True, return the rank used to compute the whitener.
- verbose : bool, str, int, or None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
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