void RunGAMESSDialog::saveGAMESSInput()
{
QString filename = QFileDialog::getSaveFileName(MainControl::getInstance(0)->getWorkingDir().c_str());
if (filename == "")
return;
outfile_.open(filename.latin1(), std::ios::out);
setParameters_();
outfile_.write(*(MainControl::getInstance(0)->getSelectedSystem()));
outfile_.close();
}
void RunGAMESSDialog::accept()
{
String filename;
File::createTemporaryFilename(filename);
outfile_.open(filename+".inp", std::ios::out);
setParameters_();
outfile_.write(*(MainControl::getInstance(0)->getSelectedSystem()));
outfile_.close();
String GAMESSCommand = GAMESSPath->text().latin1();
GAMESSCommand += " " + filename;
Log.info() << (String)tr("Executing GAMESS") << std::endl;
system(GAMESSCommand.c_str());
Log.info() << (String)tr("Done! ") << std::endl;
File::remove(filename+".inp");
DatasetControl::getInstance(0)->addGAMESSData();
}
void QTClusterFinder::run_(const vector<MapType> & input_maps,
ConsensusMap & result_map)
{
num_maps_ = input_maps.size();
if (num_maps_ < 2)
{
throw Exception::IllegalArgument(__FILE__, __LINE__, __PRETTY_FUNCTION__,
"At least two input maps required");
}
// set up the distance functor (and set other parameters):
DoubleReal max_intensity = input_maps[0].getMaxInt();
DoubleReal max_mz = input_maps[0].getMax()[1];
for (Size map_index = 1; map_index < num_maps_; ++map_index)
{
max_intensity = max(max_intensity, input_maps[map_index].getMaxInt());
max_mz = max(max_mz, input_maps[map_index].getMax()[0]);
}
setParameters_(max_intensity, max_mz);
// create the hash grid and fill it with features:
//cout << "Hashing..." << endl;
list<GridFeature> grid_features;
Grid grid(Grid::ClusterCenter(max_diff_rt_, max_diff_mz_));
for (Size map_index = 0; map_index < num_maps_; ++map_index)
{
for (Size feature_index = 0; feature_index < input_maps[map_index].size();
++feature_index)
{
grid_features.push_back(
GridFeature(input_maps[map_index][feature_index], map_index,
feature_index));
GridFeature & gfeature = grid_features.back();
// sort peptide hits once now, instead of multiple times later:
BaseFeature & feature = const_cast<BaseFeature &>(
grid_features.back().getFeature());
for (vector<PeptideIdentification>::iterator pep_it =
feature.getPeptideIdentifications().begin(); pep_it !=
feature.getPeptideIdentifications().end(); ++pep_it)
{
pep_it->sort();
}
grid.insert(std::make_pair(Grid::ClusterCenter(gfeature.getRT(), gfeature.getMZ()), &gfeature));
}
}
// compute QT clustering:
//cout << "Clustering..." << endl;
list<QTCluster> clustering;
computeClustering_(grid, clustering);
// number of clusters == number of data points:
Size size = clustering.size();
// Create a temporary map where we store which GridFeatures are next to which Clusters
OpenMSBoost::unordered_map<GridFeature *, std::vector< QTCluster * > > element_mapping;
for (list<QTCluster>::iterator it = clustering.begin(); it != clustering.end(); ++it)
{
OpenMSBoost::unordered_map<Size, GridFeature *> elements;
typedef std::multimap<DoubleReal, GridFeature *> InnerNeighborMap;
typedef OpenMSBoost::unordered_map<Size, InnerNeighborMap > NeighborMap;
NeighborMap neigh = it->getNeighbors();
for (NeighborMap::iterator n_it = neigh.begin(); n_it != neigh.end(); ++n_it)
{
for (InnerNeighborMap::iterator i_it = n_it->second.begin(); i_it != n_it->second.end(); ++i_it)
{
element_mapping[i_it->second].push_back( &(*it) );
}
}
}
ProgressLogger logger;
logger.setLogType(ProgressLogger::CMD);
logger.startProgress(0, size, "linking features");
Size progress = 0;
result_map.clear(false);
while (!clustering.empty())
{
// cout << "Clusters: " << clustering.size() << endl;
ConsensusFeature consensus_feature;
makeConsensusFeature_(clustering, consensus_feature, element_mapping);
if (!clustering.empty())
{
result_map.push_back(consensus_feature);
}
logger.setProgress(progress++);
}
logger.endProgress();
}
