'Filter data.
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 after filtering'

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

    if (not isinstance(epochs_data, np.ndarray)):
        raise ValueError(('epochs_data    should    be    of    type    ndarray    (got    %s).' % type(epochs_data)))
    epochs_data = np.atleast_3d(epochs_data)
    return filter_data(epochs_data, self.info['sfreq'], self.l_freq, self.h_freq, self.picks, self.filter_length, self.l_trans_bandwidth, self.h_trans_bandwidth, method=self.method, iir_params=self.iir_params, n_jobs=self.n_jobs, copy=False, verbose=False)
