braindecode.preprocessing.EqualizeChannels#

class braindecode.preprocessing.EqualizeChannels(copy=True, verbose=None)[source]#

Braindecode preprocessor wrapper for equalize_channels().

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:
instanceslist

A list of MNE-Python objects to equalize the channels for. Objects can be of type Raw, Epochs, Evoked, Spectrum, AverageTFR, Forward, Covariance, CrossSpectralDensity or Info.

Changed in version 1.11: Added support for mne.time_frequency.Spectrum objects.

copybool

When dropping and/or re-ordering channels, an object will be copied when this parameter is set to True. When set to False (the default) the dropping and re-ordering of channels happens in-place.

Added in version 0.20.0.

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:
equalized_instanceslist

A list of MNE-Python objects that have the same channels defined in the same order.

See also

mne.channels.unify_bad_channels
mne.channels.rename_channels
mne.channels.combine_channels

Methods

fn(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, Spectrum, AverageTFR, Forward, Covariance, CrossSpectralDensity or Info.

    Changed in version 1.11: Added support for mne.time_frequency.Spectrum objects.

  • copy (bool) –

    When dropping and/or re-ordering channels, an object will be copied when this parameter is set to True. When set to False (the default) the dropping and re-ordering of channels happens in-place.

    Added 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 and mne.verbose() for details. Should only be passed as a keyword argument.

Returns:

equalized_instances – A list of MNE-Python objects that have the same channels defined in the same order.

Return type:

list

See also

mne.channels.unify_bad_channels, mne.channels.rename_channels, mne.channels.combine_channels