'Standardize data across channels.
Parameters
epochs_data : array, shape (n_epochs, n_channels, n_times)
The data.
y : None | array, shape (n_epochs,)
The label for each epoch.
If None not used. Defaults to None.
Returns
X : array, shape (n_epochs, n_channels, n_times)
The data concatenated over channels.
Notes
This function makes a copy of the data before the operations and the
memory usage may be large with big data.'

def transform(self, epochs_data, y=None):

    return _sklearn_reshape_apply(self._scaler.transform, True, epochs_data, y)
