mne.grand_average#

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

Make grand average of a list of Evoked or AverageTFR data.

For mne.Evoked data, the function interpolates bad channels based on the 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 mne.time_frequency.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

A grand average evoked should not be used for source localization.

Parameters:
all_instlist of Evoked or AverageTFR

The evoked datasets.

interpolate_badsbool

If True, bad MEG and EEG channels are interpolated. Ignored for AverageTFR.

drop_badsbool

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_averageEvoked | AverageTFR

The grand average data. Same type as input.

Notes

New in v0.11.0.

Examples using mne.grand_average#

EEG analysis - Event-Related Potentials (ERPs)

EEG analysis - Event-Related Potentials (ERPs)