mne.compute_proj_evoked#
- mne.compute_proj_evoked(evoked, n_grad=2, n_mag=2, n_eeg=2, desc_prefix=None, meg='separate', verbose=None)[source]#
Compute SSP (signal-space projection) vectors on evoked data.
This function aims to find those SSP vectors that will project out the
n
most prominent signals from the data for each specified sensor type. Consequently, if the provided input data contains high levels of noise, the produced SSP vectors can then be used to eliminate that noise from the data.- Parameters:
- evokedinstance of
Evoked
The Evoked obtained by averaging the artifact.
- n_grad
int
Number of vectors for gradiometers.
- n_mag
int
Number of vectors for magnetometers.
- n_eeg
int
Number of vectors for EEG channels.
- desc_prefix
str
|None
The description prefix to use. If None, one will be created based on tmin and tmax.
New in version 0.17.
- meg
str
Can be ‘separate’ (default) or ‘combined’ to compute projectors for magnetometers and gradiometers separately or jointly. If ‘combined’,
n_mag == n_grad
is required and the number of projectors computed for MEG will ben_mag
.New in version 0.18.
- verbose
bool
|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.
- evokedinstance of
- Returns:
- projs
list
List of projection vectors.
- projs
See also
Examples using mne.compute_proj_evoked
#
Background on projectors and projections
Brainstorm raw (median nerve) dataset