How to use the pyopenms.ConsensusMap function in pyopenms

def id_mapper(in_file, id_file, out_file, params, use_centroid_rt,
        use_centroid_mz, use_subelements ):

    in_type = pms.FileHandler.getType(in_file)

    protein_ids = []
    peptide_ids = []

    pms.IdXMLFile().load(id_file, protein_ids, peptide_ids)

    mapper = pms.IDMapper()
    mapper.setParameters(params)

    if in_type == pms.Type.CONSENSUSXML:
        file_ = pms.ConsensusXMLFile()
        map_ = pms.ConsensusMap()
        file_.load(in_file, map_)
        mapper.annotate(map_, peptide_ids, protein_ids, use_subelements)
        addDataProcessing(map_, params, pms.ProcessingAction.IDENTIFICATION_MAPPING)
        file_.store(out_file, map_)

    elif in_type == pms.Type.FEATUREXML:
        file_ = pms.FeatureXMLFile()
        map_ = pms.FeatureMap()
        file_.load(in_file, map_)
        mapper.annotate(map_, peptide_ids, protein_ids, use_centroid_rt,
                use_centroid_mz)
        addDataProcessing(map_, params, pms.ProcessingAction.IDENTIFICATION_MAPPING)
        file_.store(out_file, map_)

    elif in_type == pms.Type.MZQ:
        file_ = pms.MzQuantMLFile()

def id_mapper(in_file, id_file, out_file, params, use_centroid_rt,
        use_centroid_mz, use_subelements ):

    in_type = pms.FileHandler.getType(in_file)

    protein_ids = []
    peptide_ids = []

    pms.IdXMLFile().load(id_file, protein_ids, peptide_ids)

    mapper = pms.IDMapper()
    mapper.setParameters(params)

    if in_type == pms.Type.CONSENSUSXML:
        file_ = pms.ConsensusXMLFile()
        map_ = pms.ConsensusMap()
        file_.load(in_file, map_)
        mapper.annotate(map_, peptide_ids, protein_ids, use_subelements)
        addDataProcessing(map_, params, pms.ProcessingAction.IDENTIFICATION_MAPPING)
        file_.store(out_file, map_)

    elif in_type == pms.Type.FEATUREXML:
        file_ = pms.FeatureXMLFile()
        map_ = pms.FeatureMap()
        file_.load(in_file, map_)
        mapper.annotate(map_, peptide_ids, protein_ids, use_centroid_rt,
                use_centroid_mz)
        addDataProcessing(map_, params, pms.ProcessingAction.IDENTIFICATION_MAPPING)
        file_.store(out_file, map_)

    elif in_type == pms.Type.MZQ:
        file_ = pms.MzQuantMLFile()

def link(in_files, out_file, keep_subelements, params):

    in_types = set(pms.FileHandler.getType(in_) for in_ in in_files)

    if in_types == set((pms.Type.CONSENSUSXML,)):
        link_features = False
    elif in_types == set((pms.Type.FEATUREXML,)):
        link_features = True
    else:
        raise Exception("different kinds of input files")

    algorithm_parameters = params.copy("algorithm:", True)
    algorithm = pms.FeatureGroupingAlgorithmQT()
    algorithm.setParameters(algorithm_parameters)

    out_map = pms.ConsensusMap()
    fds = out_map.getColumnHeaders()
    if link_features:
        f = pms.FeatureXMLFile()
        maps = []
        for i, in_file in enumerate(in_files):
            map_ = pms.FeatureMap()
            f.load(in_file, map_)

            # set filedescriptions
            fd = fds.get(i, pms.ColumnHeader())
            fd.filename = in_file
            fd.size = map_.size()
            fd.unique_id = map_.getUniqueId()
            fds[i] = fd
            maps.append(map_)
        out_map.setColumnHeaders(fds)

f.load(in_file, map_)

            # set filedescriptions
            fd = fds.get(i, pms.ColumnHeader())
            fd.filename = in_file
            fd.size = map_.size()
            fd.unique_id = map_.getUniqueId()
            fds[i] = fd
            maps.append(map_)
        out_map.setColumnHeaders(fds)
        algorithm.group(maps, out_map)
    else:
        f = pms.ConsensusXMLFile()
        maps = []
        for i, in_file in enumerate(in_files):
            map_ = pms.ConsensusMap()
            f.load(in_file, map_)
            maps.append(map_)
        algorithm.group(maps, out_map)

        if not keep_subelements:
            for i in range(len(in_files)):
                # set filedescriptions
                fd = fds.get(i, pms.ColumnHeader())
                fd.filename = in_files[i]
                fd.size = maps[i].size()
                fd.unique_id = maps[i].getUniqueId()
                fds[i] = fd
            out_map.setColumnHeaders(fds)
        else:
            algorithm.transferSubelements(maps, out_map)

def main(options):

    # make sure that the ids are "correct" for the testcase
    date_time = pyopenms.DateTime();
    if options.test:
        date_time.set("1999-12-31 23:59:59");
        pyopenms.UniqueIdGenerator().setSeed(date_time);
    else:
        date_time = pyopenms.DateTime.now();

    exp = pyopenms.MSExperiment()
    out_map = pyopenms.ConsensusMap()
    pyopenms.FileHandler().loadExperiment(options.infile, exp)
    exp.updateRanges()

    # 
    # 1. filter MS1 level (only keep MS1)
    # 
    tmp = copy.copy(exp)
    tmp.clear(False); 
    for spectrum in exp:
        if spectrum.getMSLevel() == 1:
            tmp.push_back(spectrum)
    exp = tmp
    exp.sortSpectra(True)

    # 
    # 2. set parameters