mne.compute_proj_epochs#

mne.compute_proj_epochs(epochs, n_grad=2, n_mag=2, n_eeg=2, n_jobs=None, desc_prefix=None, meg='separate', verbose=None)[source]#

Compute SSP (signal-space projection) vectors on epoched 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:

epochsinstance of Epochs: The epochs containing the artifact.
n_gradint | float between 0 and 1: Number of vectors for gradiometers. Either an integer or a float between 0 and 1 to select the number of vectors to explain the cumulative variance greater than n_grad.
n_magint | float between 0 and 1: Number of vectors for magnetometers. Either an integer or a float between 0 and 1 to select the number of vectors to explain the cumulative variance greater than n_mag.
n_eegint | float between 0 and 1: Number of vectors for EEG channels. Either an integer or a float between 0 and 1 to select the number of vectors to explain the cumulative variance greater than n_eeg.
n_jobsint | None: The number of jobs to run in parallel. If -1, it is set to the number of CPU cores. Requires the joblib package. None (default) is a marker for ‘unset’ that will be interpreted as n_jobs=1 (sequential execution) unless the call is performed under a joblib.parallel_config context manager that sets another value for n_jobs. Number of jobs to use to compute covariance.
desc_prefixstr | None: The description prefix to use. If None, one will be created based on the event_id, tmin, and tmax.
megstr: 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 v0.18.
verbosebool | 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.

Returns: