def calculate_performance(molecules, ensemble, sort_order, options):
    """
    determine the virtual screening performance of the input ensemble, and return the results in an
    ensemble storage object.
    :param molecules:
    :param ensemble:
    :param sort_order: string. either 'asc' (for binding energy estimates)  or 'dsc' (for similarity scores)
    :param options: instance of s
    :return:
    """
    es = EnsembleStorage()
    es.set_prop('ensemble', ensemble)

    # calculate the appropriate score structure type
    score_structure = classification.make_score_structure(molecules, ensemble)

    # determine auc value
    auc_structure = classification.make_auc_structure(score_structure)
    auc = classification.calculate_auc(auc_structure, sort_order, 'no stats')
    es.set_prop('auc', auc)

    # calculate enrichment factors
    for fpf in classification.make_fpfList(options, score_structure):
        fpf = float(fpf)
        ef_structure = classification.make_ef_structure(score_structure, fpf, sort_order)
        if ef_structure:
            ef = classification.calculate_ef(ef_structure, fpf)
            es.set_prop(ef[0], ef[1], 'ef')
    return es
determine the virtual screening performance of the input ensemble, and return the results in an
    ensemble storage object.
    :param molecules:
    :param ensemble:
    :param sort_order: string. either 'asc' (for binding energy estimates)  or 'dsc' (for similarity scores)
    :param options: instance of s
    :return: