mne.compute_proj_raw

mne.compute_proj_raw(raw, start=0, stop=None, duration=1, n_grad=2, n_mag=2, n_eeg=0, reject=None, flat=None, n_jobs=1, meg='separate', verbose=None)[source]

Compute SSP (signal-space projection) vectors on continuous 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
rawinstance of Raw

A raw object to use the data from.

startfloat

Time (in sec) to start computing SSP.

stopfloat

Time (in sec) to stop computing SSP. None will go to the end of the file.

durationfloat

Duration (in sec) to chunk data into for SSP If duration is None, data will not be chunked.

n_gradint

Number of vectors for gradiometers.

n_magint

Number of vectors for magnetometers.

n_eegint

Number of vectors for EEG channels.

rejectdict | None

Epoch rejection configuration (see Epochs).

flatdict | None

Epoch flat configuration (see Epochs).

n_jobsint

The number of jobs to run in parallel (default 1). Requires the joblib package. Number of jobs to use to compute covariance.

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 version 0.18.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

Returns
projs: list

List of projection vectors.