ExitCodes main_(int, const char**)
{
//-------------------------------------------------------------
// parsing parameters
//-------------------------------------------------------------
String in(getStringOption_("in"));
String out(getStringOption_("out"));
String pair_in(getStringOption_("pair_in"));
String feature_out(getStringOption_("feature_out"));
double precursor_mass_tolerance(getDoubleOption_("precursor_mass_tolerance"));
double RT_tolerance(getDoubleOption_("RT_tolerance"));
double expansion_range(getDoubleOption_("expansion_range"));
Size max_isotope(getIntOption_("max_isotope"));
Int debug(getIntOption_("debug"));
//-------------------------------------------------------------
// reading input
//-------------------------------------------------------------
PeakMap exp;
MzMLFile().load(in, exp);
exp.sortSpectra();
exp.updateRanges();
// read pair file
ifstream is(pair_in.c_str());
String line;
vector<SILAC_pair> pairs;
while (getline(is, line))
{
line.trim();
if (line.empty() || line[0] == '#')
{
continue;
}
vector<String> split;
line.split(' ', split);
if (split.size() != 4)
{
cerr << "missformated line ('" << line << "') should be (space separated) 'm/z-light m/z-heavy charge rt'" << endl;
}
SILAC_pair p;
p.mz_light = split[0].toDouble();
p.mz_heavy = split[1].toDouble();
p.charge = split[2].toInt();
p.rt = split[3].toDouble();
pairs.push_back(p);
}
is.close();
//-------------------------------------------------------------
// calculations
//-------------------------------------------------------------
ConsensusMap results_map;
results_map.getFileDescriptions()[0].label = "light";
results_map.getFileDescriptions()[0].filename = in;
results_map.getFileDescriptions()[1].label = "heavy";
results_map.getFileDescriptions()[1].filename = in;
FeatureFinderAlgorithmIsotopeWavelet iso_ff;
Param ff_param(iso_ff.getParameters());
ff_param.setValue("max_charge", 3);
ff_param.setValue("intensity_threshold", -1.0);
iso_ff.setParameters(ff_param);
FeatureFinder ff;
ff.setLogType(ProgressLogger::NONE);
vector<SILACQuantitation> quantlets;
FeatureMap all_features;
for (PeakMap::ConstIterator it = exp.begin(); it != exp.end(); ++it)
{
if (it->size() == 0 || it->getMSLevel() != 1 || !it->getInstrumentSettings().getZoomScan())
{
continue;
}
PeakSpectrum new_spec = *it;
// get spacing from data
double min_spacing(numeric_limits<double>::max());
double last_mz(0);
for (PeakSpectrum::ConstIterator pit = new_spec.begin(); pit != new_spec.end(); ++pit)
{
if (pit->getMZ() - last_mz < min_spacing)
{
min_spacing = pit->getMZ() - last_mz;
}
last_mz = pit->getMZ();
}
writeDebug_("Min-spacing=" + String(min_spacing), 1);
// split the spectrum into two subspectra, by using different hypothesis of
// the SILAC pairs
Size idx = 0;
for (vector<SILAC_pair>::const_iterator pit = pairs.begin(); pit != pairs.end(); ++pit, ++idx)
{
// in RT window?
if (fabs(it->getRT() - pit->rt) >= RT_tolerance)
{
continue;
}
// now excise the two ranges for the pair, complete isotope distributions of both, light and heavy
PeakSpectrum light_spec, heavy_spec;
light_spec.setRT(it->getRT());
heavy_spec.setRT(it->getRT());
for (PeakSpectrum::ConstIterator sit = it->begin(); sit != it->end(); ++sit)
{
double mz(sit->getMZ());
if (mz - (pit->mz_light - precursor_mass_tolerance) > 0 &&
(pit->mz_light + (double)max_isotope * Constants::NEUTRON_MASS_U / (double)pit->charge + precursor_mass_tolerance) - mz > 0)
{
light_spec.push_back(*sit);
}
if (mz - (pit->mz_heavy - precursor_mass_tolerance) > 0 &&
(pit->mz_heavy + (double)max_isotope * Constants::NEUTRON_MASS_U / (double)pit->charge + precursor_mass_tolerance) - mz > 0)
{
heavy_spec.push_back(*sit);
}
}
// expand light spectrum
Peak1D p;
p.setIntensity(0);
if (light_spec.size() > 0)
{
double lower_border = light_spec.begin()->getMZ() - expansion_range;
for (double pos = light_spec.begin()->getMZ(); pos > lower_border; pos -= min_spacing)
{
p.setMZ(pos);
light_spec.insert(light_spec.begin(), p);
}
double upper_border = light_spec.begin()->getMZ() - expansion_range;
for (double pos = light_spec.rbegin()->getMZ(); pos < upper_border; pos += min_spacing)
{
p.setMZ(pos);
light_spec.push_back(p);
}
}
if (heavy_spec.size() > 0)
{
// expand heavy spectrum
double lower_border = heavy_spec.begin()->getMZ() - expansion_range;
for (double pos = heavy_spec.begin()->getMZ(); pos > lower_border; pos -= min_spacing)
{
p.setMZ(pos);
heavy_spec.insert(heavy_spec.begin(), p);
}
double upper_border = heavy_spec.begin()->getMZ() - expansion_range;
for (double pos = heavy_spec.rbegin()->getMZ(); pos < upper_border; pos += min_spacing)
{
p.setMZ(pos);
heavy_spec.push_back(p);
}
}
// create experiments for feature finding
PeakMap new_exp_light, new_exp_heavy;
new_exp_light.addSpectrum(light_spec);
new_exp_heavy.addSpectrum(heavy_spec);
if (debug > 9)
{
MzMLFile().store(String(it->getRT()) + "_debugging_light.mzML", new_exp_light);
MzMLFile().store(String(it->getRT()) + "_debugging_heavy.mzML", new_exp_heavy);
}
writeDebug_("Spectrum-id: " + it->getNativeID() + " @ " + String(it->getRT()) + "s", 1);
new_exp_light.updateRanges();
new_exp_heavy.updateRanges();
FeatureMap feature_map_light, feature_map_heavy, seeds;
if (light_spec.size() > 0)
{
ff.run("isotope_wavelet", new_exp_light, feature_map_light, ff_param, seeds);
}
writeDebug_("#light_features=" + String(feature_map_light.size()), 1);
if (heavy_spec.size() > 0)
{
ff.run("isotope_wavelet", new_exp_heavy, feature_map_heavy, ff_param, seeds);
}
writeDebug_("#heavy_features=" + String(feature_map_heavy.size()), 1);
// search if feature maps to m/z value of pair
vector<MatchedFeature> light, heavy;
for (FeatureMap::const_iterator fit = feature_map_light.begin(); fit != feature_map_light.end(); ++fit)
{
all_features.push_back(*fit);
light.push_back(MatchedFeature(*fit, idx));
}
for (FeatureMap::const_iterator fit = feature_map_heavy.begin(); fit != feature_map_heavy.end(); ++fit)
{
all_features.push_back(*fit);
heavy.push_back(MatchedFeature(*fit, idx));
}
if (!heavy.empty() && !light.empty())
{
writeDebug_("Finding best feature pair out of " + String(light.size()) + " light and " + String(heavy.size()) + " heavy matching features.", 1);
// now find "good" matches, means the pair with the smallest m/z deviation
Feature best_light, best_heavy;
double best_deviation(numeric_limits<double>::max());
Size best_idx(pairs.size());
for (vector<MatchedFeature>::const_iterator fit1 = light.begin(); fit1 != light.end(); ++fit1)
{
for (vector<MatchedFeature>::const_iterator fit2 = heavy.begin(); fit2 != heavy.end(); ++fit2)
{
if (fit1->idx != fit2->idx || fit1->f.getCharge() != fit2->f.getCharge() ||
fabs(fit1->f.getMZ() - pairs[fit1->idx].mz_light) > precursor_mass_tolerance ||
fabs(fit2->f.getMZ() - pairs[fit2->idx].mz_heavy) > precursor_mass_tolerance)
{
continue;
}
double deviation(0);
deviation = fabs((fit1->f.getMZ() - pairs[fit1->idx].mz_light) - (fit2->f.getMZ() - pairs[fit2->idx].mz_heavy));
if (deviation < best_deviation && deviation < precursor_mass_tolerance)
{
best_light = fit1->f;
best_heavy = fit2->f;
best_idx = fit1->idx;
}
}
}
if (best_idx == pairs.size())
{
continue;
}
writeDebug_("Ratio: " + String(best_heavy.getIntensity() / best_light.getIntensity()), 1);
ConsensusFeature SILAC_feature;
SILAC_feature.setMZ((best_light.getMZ() + best_heavy.getMZ()) / 2.0);
SILAC_feature.setRT((best_light.getRT() + best_heavy.getRT()) / 2.0);
SILAC_feature.insert(0, best_light);
SILAC_feature.insert(1, best_heavy);
results_map.push_back(SILAC_feature);
quantlets.push_back(SILACQuantitation(best_light.getIntensity(), best_heavy.getIntensity(), best_idx));
}
}
}
// now calculate the final quantitation values from the quantlets
Map<Size, vector<SILACQuantitation> > idx_to_quantlet;
for (vector<SILACQuantitation>::const_iterator it = quantlets.begin(); it != quantlets.end(); ++it)
{
idx_to_quantlet[it->idx].push_back(*it);
}
for (Map<Size, vector<SILACQuantitation> >::ConstIterator it1 = idx_to_quantlet.begin(); it1 != idx_to_quantlet.end(); ++it1)
{
SILAC_pair silac_pair = pairs[it1->first];
// simply add up all intensities and calculate the final ratio
double light_sum(0), heavy_sum(0);
vector<double> light_ints, heavy_ints, ratios;
for (vector<SILACQuantitation>::const_iterator it2 = it1->second.begin(); it2 != it1->second.end(); ++it2)
{
light_sum += it2->light_intensity;
light_ints.push_back(it2->light_intensity);
heavy_sum += it2->heavy_intensity;
heavy_ints.push_back(it2->heavy_intensity);
ratios.push_back(it2->heavy_intensity / it2->light_intensity * (it2->heavy_intensity + it2->light_intensity));
}
double absdev_ratios = Math::absdev(ratios.begin(), ratios.begin() + (ratios.size()) / (heavy_sum + light_sum));
cout << "Ratio: " << silac_pair.mz_light << " <-> " << silac_pair.mz_heavy << " @ " << silac_pair.rt << " s, ratio(h/l) " << heavy_sum / light_sum << " +/- " << absdev_ratios << " (#scans for quantation: " << String(it1->second.size()) << " )" << endl;
}
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
if (feature_out != "")
{
FeatureXMLFile().store(feature_out, all_features);
}
writeDebug_("Writing output", 1);
ConsensusXMLFile().store(out, results_map);
return EXECUTION_OK;
}
ExitCodes main_(int, const char**)
{
// parsing parameters
String in(getStringOption_("in"));
String feature_in(getStringOption_("feature_in"));
String out(getStringOption_("out"));
double precursor_mass_tolerance(getDoubleOption_("precursor_mass_tolerance"));
// reading input
FileHandler fh;
FileTypes::Type in_type = fh.getType(in);
PeakMap exp;
fh.loadExperiment(in, exp, in_type, log_type_, false, false);
exp.sortSpectra();
FeatureMap feature_map;
if (feature_in != "")
{
FeatureXMLFile().load(feature_in, feature_map);
}
// calculations
FeatureFinderAlgorithmIsotopeWavelet iso_ff;
Param ff_param(iso_ff.getParameters());
ff_param.setValue("max_charge", getIntOption_("max_charge"));
ff_param.setValue("intensity_threshold", getDoubleOption_("intensity_threshold"));
iso_ff.setParameters(ff_param);
FeatureFinder ff;
ff.setLogType(ProgressLogger::NONE);
PeakMap exp2 = exp;
exp2.clear(false);
for (PeakMap::ConstIterator it = exp.begin(); it != exp.end(); ++it)
{
if (it->size() != 0)
{
exp2.addSpectrum(*it);
}
}
exp = exp2;
exp.updateRanges();
// TODO check MS2 and MS1 counts
ProgressLogger progresslogger;
progresslogger.setLogType(log_type_);
progresslogger.startProgress(0, exp.size(), "Correcting precursor masses");
for (PeakMap::Iterator it = exp.begin(); it != exp.end(); ++it)
{
progresslogger.setProgress(exp.end() - it);
if (it->getMSLevel() != 2)
{
continue;
}
// find first MS1 scan of the MS/MS scan
PeakMap::Iterator ms1_it = it;
while (ms1_it != exp.begin() && ms1_it->getMSLevel() != 1)
{
--ms1_it;
}
if (ms1_it == exp.begin() && ms1_it->getMSLevel() != 1)
{
writeLog_("Did not find a MS1 scan to the MS/MS scan at RT=" + String(it->getRT()));
continue;
}
if (ms1_it->size() == 0)
{
writeDebug_("No peaks in scan at RT=" + String(ms1_it->getRT()) + String(", skipping"), 1);
continue;
}
PeakMap::Iterator ms2_it = ms1_it;
++ms2_it;
while (ms2_it != exp.end() && ms2_it->getMSLevel() == 2)
{
// first: error checks
if (ms2_it->getPrecursors().empty())
{
writeDebug_("Warning: found no precursors of spectrum RT=" + String(ms2_it->getRT()) + ", skipping it.", 1);
++ms2_it;
continue;
}
else if (ms2_it->getPrecursors().size() > 1)
{
writeLog_("Warning: found more than one precursor of spectrum RT=" + String(ms2_it->getRT()) + ", using first one.");
}
Precursor prec = *ms2_it->getPrecursors().begin();
double prec_pos = prec.getMZ();
PeakMap new_exp;
// now excise small region from the MS1 spec for the feature finder (isotope pattern must be covered...)
PeakSpectrum zoom_spec;
for (PeakSpectrum::ConstIterator pit = ms1_it->begin(); pit != ms1_it->end(); ++pit)
{
if (pit->getMZ() > prec_pos - 3 && pit->getMZ() < prec_pos + 3)
{
zoom_spec.push_back(*pit);
}
}
new_exp.addSpectrum(zoom_spec);
new_exp.updateRanges();
FeatureMap features, seeds;
ff.run("isotope_wavelet", new_exp, features, ff_param, seeds);
if (features.empty())
{
writeDebug_("No features found for scan RT=" + String(ms1_it->getRT()), 1);
++ms2_it;
continue;
}
double max_int(numeric_limits<double>::min());
double min_dist(numeric_limits<double>::max());
Size max_int_feat_idx(0);
for (Size i = 0; i != features.size(); ++i)
{
if (fabs(features[i].getMZ() - prec_pos) < precursor_mass_tolerance &&
features[i].getIntensity() > max_int)
{
max_int_feat_idx = i;
max_int = features[i].getIntensity();
min_dist = fabs(features[i].getMZ() - prec_pos);
}
}
writeDebug_(" max_int=" + String(max_int) + " mz=" + String(features[max_int_feat_idx].getMZ()) + " charge=" + String(features[max_int_feat_idx].getCharge()), 5);
if (min_dist < precursor_mass_tolerance)
{
prec.setMZ(features[max_int_feat_idx].getMZ());
prec.setCharge(features[max_int_feat_idx].getCharge());
vector<Precursor> precs;
precs.push_back(prec);
ms2_it->setPrecursors(precs);
writeDebug_("Correcting precursor mass of spectrum RT=" + String(ms2_it->getRT()) + " from " + String(prec_pos) + " to " + String(prec.getMZ()) + " (z=" + String(prec.getCharge()) + ")", 1);
}
++ms2_it;
}
it = --ms2_it;
}
progresslogger.endProgress();
// writing output
fh.storeExperiment(out, exp, log_type_);
return EXECUTION_OK;
}
ExitCodes main_(int, const char **)
{
//input and output file names ..
String in = getStringOption_("in");
String out = getStringOption_("out");
//prevent loading of fragment spectra
PeakFileOptions options;
options.setMSLevels(vector<Int>(1, 1));
//reading input data
MzMLFile f;
f.getOptions() = options;
f.setLogType(log_type_);
PeakMap exp;
f.load(in, exp);
exp.updateRanges();
//no seeds supported
FeatureMap<> seeds;
//setup of FeatureFinder
FeatureFinder ff;
ff.setLogType(log_type_);
// A map for the resulting features
FeatureMap<> features;
// get parameters specific for the feature finder
Param feafi_param = getParam_().copy("algorithm:", true);
writeDebug_("Parameters passed to FeatureFinder", feafi_param, 3);
// Apply the feature finder
ff.run(FeatureFinderAlgorithmIsotopeWavelet<Peak1D, Feature>::getProductName(), exp, features, feafi_param, seeds);
features.applyMemberFunction(&UniqueIdInterface::setUniqueId);
// DEBUG
if (debug_level_ > 10)
{
FeatureMap<>::Iterator it;
for (it = features.begin(); it != features.end(); ++it)
{
if (!it->isMetaEmpty())
{
vector<String> keys;
it->getKeys(keys);
LOG_INFO << "Feature " << it->getUniqueId() << endl;
for (Size i = 0; i < keys.size(); i++)
{
LOG_INFO << " " << keys[i] << " = " << it->getMetaValue(keys[i]) << endl;
}
}
}
}
//-------------------------------------------------------------
// writing files
//-------------------------------------------------------------
//annotate output with data processing info
addDataProcessing_(features, getProcessingInfo_(DataProcessing::QUANTITATION));
// write features to user specified output file
FeatureXMLFile map_file;
map_file.store(out, features);
return EXECUTION_OK;
}
ExitCodes main_(int, const char**)
{
//input file names
String in = getStringOption_("in");
String out = getStringOption_("out");
String out_mzq = getStringOption_("out_mzq");
//prevent loading of fragment spectra
PeakFileOptions options;
options.setMSLevels(vector<Int>(1, 1));
//reading input data
MzMLFile f;
f.getOptions() = options;
f.setLogType(log_type_);
PeakMap exp;
f.load(in, exp);
exp.updateRanges();
if (exp.getSpectra().empty())
{
throw OpenMS::Exception::FileEmpty(__FILE__, __LINE__, __FUNCTION__, "Error: No MS1 spectra in input file.");
}
// determine type of spectral data (profile or centroided)
SpectrumSettings::SpectrumType spectrum_type = exp[0].getType();
if (spectrum_type == SpectrumSettings::RAWDATA)
{
if (!getFlag_("force"))
{
throw OpenMS::Exception::IllegalArgument(__FILE__, __LINE__, __FUNCTION__, "Error: Profile data provided but centroided spectra expected. To enforce processing of the data set the -force flag.");
}
}
//load seeds
FeatureMap seeds;
if (getStringOption_("seeds") != "")
{
FeatureXMLFile().load(getStringOption_("seeds"), seeds);
}
//setup of FeatureFinder
FeatureFinder ff;
ff.setLogType(log_type_);
// A map for the resulting features
FeatureMap features;
// get parameters specific for the feature finder
Param feafi_param = getParam_().copy("algorithm:", true);
writeDebug_("Parameters passed to FeatureFinder", feafi_param, 3);
// Apply the feature finder
ff.run(FeatureFinderAlgorithmPicked::getProductName(), exp, features, feafi_param, seeds);
features.applyMemberFunction(&UniqueIdInterface::setUniqueId);
// DEBUG
if (debug_level_ > 10)
{
FeatureMap::Iterator it;
for (it = features.begin(); it != features.end(); ++it)
{
if (!it->isMetaEmpty())
{
vector<String> keys;
it->getKeys(keys);
LOG_INFO << "Feature " << it->getUniqueId() << endl;
for (Size i = 0; i < keys.size(); i++)
{
LOG_INFO << " " << keys[i] << " = " << it->getMetaValue(keys[i]) << endl;
}
}
}
}
//-------------------------------------------------------------
// writing files
//-------------------------------------------------------------
//annotate output with data processing info
addDataProcessing_(features, getProcessingInfo_(DataProcessing::QUANTITATION));
// write features to user specified output file
FeatureXMLFile map_file;
// Remove detailed convex hull information and subordinate features
// (unless requested otherwise) to reduce file size of feature files
// unless debugging is turned on.
if (debug_level_ < 5)
{
FeatureMap::Iterator it;
for (it = features.begin(); it != features.end(); ++it)
{
it->getConvexHull().expandToBoundingBox();
for (Size i = 0; i < it->getConvexHulls().size(); ++i)
{
it->getConvexHulls()[i].expandToBoundingBox();
}
it->getSubordinates().clear();
}
}
map_file.store(out, features);
if (!out_mzq.trim().empty())
{
MSQuantifications msq(features, exp.getExperimentalSettings(), exp[0].getDataProcessing());
msq.assignUIDs();
MzQuantMLFile file;
file.store(out_mzq, msq);
}
return EXECUTION_OK;
}
ExitCodes main_(int, const char**) override
{
ExitCodes ret = TOPPMapAlignerBase::checkParameters_();
if (ret != EXECUTION_OK) return ret;
MapAlignmentAlgorithmPoseClustering algorithm;
Param algo_params = getParam_().copy("algorithm:", true);
algorithm.setParameters(algo_params);
algorithm.setLogType(log_type_);
StringList in_files = getStringList_("in");
StringList out_files = getStringList_("out");
StringList out_trafos = getStringList_("trafo_out");
Size reference_index = getIntOption_("reference:index");
String reference_file = getStringOption_("reference:file");
FileTypes::Type in_type = FileHandler::getType(in_files[0]);
String file;
if (!reference_file.empty())
{
file = reference_file;
reference_index = in_files.size(); // points to invalid index
}
else if (reference_index > 0) // normal reference (index was checked before)
{
file = in_files[--reference_index]; // ref. index is 1-based in parameters, but should be 0-based here
}
else if (reference_index == 0) // no reference given
{
LOG_INFO << "Picking a reference (by size) ..." << std::flush;
// use map with highest number of features as reference:
Size max_count(0);
FeatureXMLFile f;
for (Size i = 0; i < in_files.size(); ++i)
{
Size s = 0;
if (in_type == FileTypes::FEATUREXML)
{
s = f.loadSize(in_files[i]);
}
else if (in_type == FileTypes::MZML) // this is expensive!
{
PeakMap exp;
MzMLFile().load(in_files[i], exp);
exp.updateRanges(1);
s = exp.getSize();
}
if (s > max_count)
{
max_count = s;
reference_index = i;
}
}
LOG_INFO << " done" << std::endl;
file = in_files[reference_index];
}
FeatureXMLFile f_fxml;
if (out_files.empty()) // no need to store featureXML, thus we can load only minimum required information
{
f_fxml.getOptions().setLoadConvexHull(false);
f_fxml.getOptions().setLoadSubordinates(false);
}
if (in_type == FileTypes::FEATUREXML)
{
FeatureMap map_ref;
FeatureXMLFile f_fxml_tmp; // for the reference, we never need CH or subordinates
f_fxml_tmp.getOptions().setLoadConvexHull(false);
f_fxml_tmp.getOptions().setLoadSubordinates(false);
f_fxml_tmp.load(file, map_ref);
algorithm.setReference(map_ref);
}
else if (in_type == FileTypes::MZML)
{
PeakMap map_ref;
MzMLFile().load(file, map_ref);
algorithm.setReference(map_ref);
}
ProgressLogger plog;
plog.setLogType(log_type_);
plog.startProgress(0, in_files.size(), "Aligning input maps");
Size progress(0); // thread-safe progress
// TODO: it should all work on featureXML files, since we might need them for output anyway. Converting to consensusXML is just wasting memory!
#ifdef _OPENMP
#pragma omp parallel for schedule(dynamic, 1)
#endif
for (int i = 0; i < static_cast<int>(in_files.size()); ++i)
{
TransformationDescription trafo;
if (in_type == FileTypes::FEATUREXML)
{
FeatureMap map;
// workaround for loading: use temporary FeatureXMLFile since it is not thread-safe
FeatureXMLFile f_fxml_tmp; // do not use OMP-firstprivate, since FeatureXMLFile has no copy c'tor
f_fxml_tmp.getOptions() = f_fxml.getOptions();
f_fxml_tmp.load(in_files[i], map);
if (i == static_cast<int>(reference_index)) trafo.fitModel("identity");
else algorithm.align(map, trafo);
if (out_files.size())
{
MapAlignmentTransformer::transformRetentionTimes(map, trafo);
// annotate output with data processing info
addDataProcessing_(map, getProcessingInfo_(DataProcessing::ALIGNMENT));
f_fxml_tmp.store(out_files[i], map);
}
}
else if (in_type == FileTypes::MZML)
{
PeakMap map;
MzMLFile().load(in_files[i], map);
if (i == static_cast<int>(reference_index)) trafo.fitModel("identity");
else algorithm.align(map, trafo);
if (out_files.size())
{
MapAlignmentTransformer::transformRetentionTimes(map, trafo);
// annotate output with data processing info
addDataProcessing_(map, getProcessingInfo_(DataProcessing::ALIGNMENT));
MzMLFile().store(out_files[i], map);
}
}
if (!out_trafos.empty())
{
TransformationXMLFile().store(out_trafos[i], trafo);
}
#ifdef _OPENMP
#pragma omp critical (MAPose_Progress)
#endif
{
plog.setProgress(++progress); // thread safe progress counter
}
}
plog.endProgress();
return EXECUTION_OK;
}
ExitCodes main_(int, const char **) override
{
//-------------------------------------------------------------
// parameter handling
//-------------------------------------------------------------
String in = getStringOption_("in");
String out = getStringOption_("out");
//-------------------------------------------------------------
// loading input
//-------------------------------------------------------------
PeakMap exp;
MzMLFile f;
f.load(in, exp);
//-------------------------------------------------------------
// calculations
//-------------------------------------------------------------
//determine maximum peak
exp.updateRanges();
double max = exp.getMaxInt() / 100.0;
for (PeakMap::Iterator it = exp.begin(); it != exp.end(); ++it)
{
if (it->getMSLevel() < 2)
{
for (PeakMap::SpectrumType::Iterator it2 = it->begin(); it2 != it->end(); ++it2)
{
it2->setIntensity(it2->getIntensity() / max);
}
}
}
/// @todo add chromatogram support for normalization, e.g. for MRM stuff (Andreas)
/*
vector<MSChromatogram > chroms = exp.getChromatograms();
double sum(0);
for (vector<MSChromatogram >::iterator it = chroms.begin(); it != chroms.end(); ++it)
{
for (MSChromatogram::Iterator it2 = it->begin(); it2 != it->end(); ++it2)
{
sum += it2->getIntensity();
}
}
for (vector<MSChromatogram >::iterator it = chroms.begin(); it != chroms.end(); ++it)
{
for (MSChromatogram::Iterator it2 = it->begin(); it2 != it->end(); ++it2)
{
it2->setIntensity(it2->getIntensity() / sum * 1000000.0);
}
}
exp.setChromatograms(chroms);
*/
//-------------------------------------------------------------
// writing output
//-------------------------------------------------------------
//annotate output with data processing info
addDataProcessing_(exp, getProcessingInfo_(DataProcessing::NORMALIZATION));
f.store(out, exp);
return EXECUTION_OK;
}