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.
Evoked
The Evoked obtained by averaging the artifact.
int
Number of vectors for gradiometers.
int
Number of vectors for magnetometers.
int
Number of vectors for EEG channels.
str
| None
The description prefix to use. If None, one will be created based on tmin and tmax.
New in version 0.17.
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 be n_mag
.
New in version 0.18.
str
| int
| None
Control verbosity of the logging output. If None
, use the default
verbosity level. See the logging documentation and
mne.verbose()
for details. Should only be passed as a keyword
argument.
list
List of projection vectors.
See also
mne.compute_proj_evoked
#Background on projectors and projections
Brainstorm raw (median nerve) dataset