How to use the ms2pip.ms2pip_tools.calc_correlations function in ms2pip

all_preds["spec_id"] = pepids
            all_preds["charge"] = charges
            all_preds["ion"] = ions
            all_preds["ionnumber"] = ionnumbers
            all_preds["mz"] = np.concatenate(mz_bufs, axis=None)
            all_preds["target"] = np.concatenate(target_bufs, axis=None)
            all_preds["prediction"] = np.concatenate(prediction_bufs, axis=None)

            sys.stdout.write(
                "\nwriting file {}_pred_and_emp.csv...\n".format(output_filename)
            )
            all_preds.to_csv("{}_pred_and_emp.csv".format(output_filename), index=False)

            if compute_correlations:
                sys.stdout.write("computing correlations...\n")
                correlations = calc_correlations.calc_correlations(all_preds)
                correlations.to_csv(
                    "{}_correlations.csv".format(output_filename), index=True
                )
                sys.stdout.write("median correlations: \n")
                sys.stdout.write(
                    "{}\n".format(correlations.groupby("ion")["pearsonr"].median())
                )

            sys.stdout.write("done! \n")

    # Only get the predictions
    else:
        sys.stdout.write("scanning peptide file... ")

        titles = data.spec_id.tolist()
        split_titles = prepare_titles(titles, num_cpu)