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.
The Evoked obtained by averaging the artifact.
Number of vectors for gradiometers.
Number of vectors for magnetometers.
Number of vectors for EEG channels.
The description prefix to use. If None, one will be created based on tmin and tmax.
New in version 0.17.
Can be ‘separate’ (default) or ‘combined’ to compute projectors
for magnetometers and gradiometers separately or jointly.
n_mag == n_grad is required and the number of
projectors computed for MEG will be
New in version 0.18.
List of projection vectors.