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 theinterpolate_bads
parameter. Ifinterpolate_bads
is True, the grand average file will contain good channels and the bad channels interpolated from the good MEG/EEG channels. Formne.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_inst
list
ofEvoked
orAverageTFR
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.
- all_inst
- Returns:
- grand_average
Evoked
|AverageTFR
The grand average data. Same type as input.
- grand_average
Notes
New in version 0.11.0.
Examples using mne.grand_average
#
EEG analysis - Event-Related Potentials (ERPs)