How to use the pyopenms.ProcessingAction function in pyopenms

options.label_identifiers)

    # 
    # 3. run
    # 
    analyzer.run_all(exp, out_map)

    # 
    # 4. set dataprocessing and output meta information
    # 
    out_map.sortByPosition()

    dp = out_map.getDataProcessing() 
    p = pyopenms.DataProcessing()
    p.setProcessingActions(set([ pyopenms.ProcessingAction().DATA_PROCESSING, 
                                  pyopenms.ProcessingAction().PEAK_PICKING,
                                  pyopenms.ProcessingAction().FILTERING,
                                  pyopenms.ProcessingAction().QUANTITATION]))
    p.setCompletionTime(date_time)

    sw = p.getSoftware()
    sw.setName("SILACAnalyzer")
    if options.test:
        sw.setVersion("version_string")
        p.setSoftware(sw)
        p.setMetaValue("parameter: mode", "test_mode")
    else:
        sw.setVersion("pyTOPP v1.10")
        p.setSoftware(sw)
    dp.append(p)
    out_map.setDataProcessing(dp)

chrom.setPrecursor(precursor)
                chrom.setNativeID(transition.getNativeID())
        if not mapped_already:
            notmapped += 1
            print "Did not find a mapping for chromatogram", chrom.getNativeID()
            if not allow_unmapped: raise Exception("No mapping")
        else:
            output.addChromatogram(chrom)

    if notmapped > 0:
        print "Could not find mapping for", notmapped, "chromatogram(s)"


    dp = pyopenms.DataProcessing()
    # dp.setProcessingActions(ProcessingAction:::FORMAT_CONVERSION)
    pa = pyopenms.ProcessingAction().FORMAT_CONVERSION
    dp.setProcessingActions(set([pa]))

    chromatograms = output.getChromatograms();
    for chrom in chromatograms:
        this_dp = chrom.getDataProcessing()
        this_dp.append(dp)
        chrom.setDataProcessing(this_dp)

    output.setChromatograms(chromatograms);
    return output

chrom.setPrecursor(precursor)
                chrom.setNativeID(transition.getNativeID())
        if not mapped_already:
            notmapped += 1
            print "Did not find a mapping for chromatogram", chrom.getNativeID()
            if not allow_unmapped: raise Exception("No mapping")
        else:
            output.addChromatogram(chrom)

    if notmapped > 0:
        print "Could not find mapping for", notmapped, "chromatogram(s)" 


    dp = pyopenms.DataProcessing()
    # dp.setProcessingActions(ProcessingAction:::FORMAT_CONVERSION)
    pa = pyopenms.ProcessingAction().FORMAT_CONVERSION
    dp.setProcessingActions(set([pa]))

    chromatograms = output.getChromatograms();
    for chrom in chromatograms:
        this_dp = chrom.getDataProcessing()
        this_dp.append(dp)
        chrom.setDataProcessing(this_dp)

    output.setChromatograms(chromatograms);
    return output

if options.is_swath:
            do_continue = pyopenms.OpenSwathHelper().checkSwathMapAndSelectTransitions(exp, targeted, transition_exp_used, options.min_upper_edge_dist)
        else:
            transition_exp_used = targeted

        if do_continue:
            # set up extractor and run
            tmp_out = pyopenms.MSExperiment();
            extractor = pyopenms.ChromatogramExtractor()
            extractor.extractChromatograms(exp, tmp_out, targeted, options.extraction_window, options.ppm, trafo, options.rt_extraction_window, options.extraction_function)
            # add all chromatograms to the output
            for chrom in tmp_out.getChromatograms():
                output.addChromatogram(chrom)

    dp = pyopenms.DataProcessing()
    pa = pyopenms.ProcessingAction().SMOOTHING
    dp.setProcessingActions(set([pa]))

    chromatograms = output.getChromatograms();
    for chrom in chromatograms:
        this_dp = chrom.getDataProcessing()
        this_dp.append(dp)
        chrom.setDataProcessing(this_dp)

    output.setChromatograms(chromatograms);

    pyopenms.MzMLFile().store(options.outfile, output);

# 
    # 3. run
    # 
    analyzer.run_all(exp, out_map)

    # 
    # 4. set dataprocessing and output meta information
    # 
    out_map.sortByPosition()

    dp = out_map.getDataProcessing() 
    p = pyopenms.DataProcessing()
    p.setProcessingActions(set([ pyopenms.ProcessingAction().DATA_PROCESSING, 
                                  pyopenms.ProcessingAction().PEAK_PICKING,
                                  pyopenms.ProcessingAction().FILTERING,
                                  pyopenms.ProcessingAction().QUANTITATION]))
    p.setCompletionTime(date_time)

    sw = p.getSoftware()
    sw.setName("SILACAnalyzer")
    if options.test:
        sw.setVersion("version_string")
        p.setSoftware(sw)
        p.setMetaValue("parameter: mode", "test_mode")
    else:
        sw.setVersion("pyTOPP v1.10")
        p.setSoftware(sw)
    dp.append(p)
    out_map.setDataProcessing(dp)

    # 
    # 5. write output

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()
        msq = pms.MSQuantifications()
        file_.load(in_file, msq)
        maps = msq.getConsensusMaps()
        for map_ in maps:
            mapper.annotate(map_, peptide_ids, protein_ids, use_subelements)
            addDataProcessing(map_, params, pms.ProcessingAction.IDENTIFICATION_MAPPING)
        msq.setConsensusMaps(maps)
        file_.store(out_file, msq)

    else:
        raise Exception("invalid input file format")