def METHOD_NAME(self, spectra_df, path_prefix):
    self.db_hits.to_csv(f'{path_prefix}_db_hits.csv')
    candidates = self.db_hits[lambda df: df.used_for_recal]
    if len(candidates) > 0:
        mz_bounds = np.array([candidates.mz.min(), candidates.mz.max()])
        mz_bound_moves = mz_bounds - self.model.predict(mz_bounds.reshape(-1, 1))
        save_recal_image(
            candidates,
            list(zip(mz_bounds, mz_bound_moves)),
            'MSIWarp recalibration',
            f'{path_prefix}_recal.png',
        )