mne.equalize_channels#
- mne.equalize_channels(instances, copy=True, verbose=None)[source]#
Equalize channel picks and ordering across multiple MNE-Python objects.
First, all channels that are not common to each object are dropped. Then, using the first object in the list as a template, the channels of each object are re-ordered to match the template. The end result is that all given objects define the same channels, in the same order.
- Parameters:
- instances
list
A list of MNE-Python objects to equalize the channels for. Objects can be of type Raw, Epochs, Evoked, AverageTFR, Forward, Covariance, CrossSpectralDensity or Info.
- copy
bool
When dropping and/or re-ordering channels, an object will be copied when this parameter is set to
True
. When set toFalse
(the default) the dropping and re-ordering of channels happens in-place.New in version 0.20.0.
- verbose
bool
|str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- instances
- Returns:
- equalized_instances
list
A list of MNE-Python objects that have the same channels defined in the same order.
- equalized_instances
Notes
This function operates inplace.