mne.grand_average¶

mne.grand_average(all_inst, interpolate_bads=True, drop_bads=True)[source]¶

Make grand average of a list evoked or AverageTFR data.

For evoked data, the function interpolates bad channels based on interpolate_bads parameter. If interpolate_bads is True, the grand average file will contain good channels and the bad channels interpolated from the good MEG/EEG channels. For AverageTFR data, the function takes the subset of channels not marked as bad in any of the instances.

The grand_average.nave attribute will be equal to the number of evoked datasets used to calculate the grand average.

Note: Grand average evoked should not be used for source localization.

Parameters:

all_inst : list of Evoked or AverageTFR data The evoked datasets. interpolate_bads : bool If True, bad MEG and EEG channels are interpolated. Ignored for AverageTFR. drop_bads : bool If True, drop all bad channels marked as bad in any data set. If neither interpolate_bads nor drop_bads is True, in the output file, every channel marked as bad in at least one of the input files will be marked as bad, but no interpolation or dropping will be performed.

Returns:

grand_average : Evoked | AverageTFR The grand average data. Same type as input.

Notes

New in version 0.11.0.

Examples using mne.grand_average¶

EEG processing and Event Related Potentials (ERPs)