How to use the pyopenms.ConsensusXMLFile 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:

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)
        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)

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:

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)

    out_map.setUniqueIds()
    addDataProcessing(out_map, params, pms.ProcessingAction.FEATURE_GROUPING)

    pms.ConsensusXMLFile().store(out_file, out_map)

    sizes = []
    for feat in out_map:
        sizes.append(feat.size())

    c = Counter(sizes)
    print "Number of consensus features:"
    for size, count in c.most_common():
        print "   of size %2d : %6d" % (size, count)
    print "        total : %6d" % out_map.size()