mne.channels.combine_channels

mne.channels.combine_channels(inst, groups, method='mean', keep_stim=False, drop_bad=False, verbose=None)

Combine channels based on specified channel grouping.

Parameters:

instinstance of Raw, Epochs, or Evoked

An MNE-Python object to combine the channels for. The object can be of type Raw, Epochs, or Evoked.

groupsdict

Specifies which channels are aggregated into a single channel, with aggregation method determined by the method parameter. One new pseudo-channel is made per dict entry; the dict values must be lists of picks (integer indices of ch_names). For example:

groups=dict(Left=[1, 2, 3, 4], Right=[5, 6, 7, 8])

Note that within a dict entry all channels must have the same type.

methodstr | callable()

Which method to use to combine channels. If a str, must be one of ‘mean’, ‘median’, or ‘std’ (standard deviation). If callable, the callable must accept one positional input (data of shape (n_channels, n_times), or (n_epochs, n_channels, n_times)) and return an array of shape (n_times,), or (n_epochs, n_times). For example with an instance of Raw or Evoked:

method = lambda data: np.mean(data, axis=0)

Another example with an instance of Epochs:

method = lambda data: np.median(data, axis=1)

Defaults to 'mean'.

keep_stimbool

If True, include stimulus channels in the resulting object. Defaults to False.

drop_badbool

If True, drop channels marked as bad before combining. Defaults to False.

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:

combined_instinstance of Raw, Epochs, or Evoked

An MNE-Python object of the same type as the input inst, containing one virtual channel for each group in groups (and, if keep_stim is True, also containing stimulus channels).

Examples using mne.channels.combine_channels

EEG analysis - Event-Related Potentials (ERPs)

EEG analysis - Event-Related Potentials (ERPs)