17 #include <boost/foreach.hpp>
88 <<
" Failed to find File = " << inputFileName <<
" !!\n";
90 return std::unique_ptr<TFile>{
new TFile(inputFileName.
fullPath().data()) };
96 const T*
object =
dynamic_cast<T*
>(inputFile.Get(objectName.data()));
98 throw cms::Exception(
"RecoTauDiscriminantCutMultiplexer::loadObjectFromFile")
99 <<
" Failed to load Object = " << objectName.data() <<
" from file = " << inputFile.GetName() <<
" !!\n";
101 std::unique_ptr<const T>
copy{
static_cast<T*
>(
object->Clone()) };
109 std::cout <<
"<loadTGraphFromDB>:" << std::endl;
110 std::cout <<
" graphName = " << graphName << std::endl;
114 return std::unique_ptr<const TGraph>{
new TGraph(*graphPayload.
product()) };
120 std::cout <<
"<loadTFormulaFromDB>:" << std::endl;
121 std::cout <<
" formulaName = " << formulaName << std::endl;
126 if ( formulaPayload->formulas().size() == 1 && formulaPayload->limits().size() == 1 ) {
127 return std::unique_ptr<TFormula> {
new TFormula(newName, formulaPayload->formulas().at(0).data()) };
129 throw cms::Exception(
"RecoTauDiscriminantCutMultiplexer::loadTFormulaFromDB")
130 <<
"Failed to load TFormula = " << formulaName <<
" from Database !!\n";
132 return std::unique_ptr<TFormula>{};
139 mvaOutput_normalization_(),
140 isInitialized_(
false)
154 if(cfg.
exists(
"inputFileName")){
156 }
else throw cms::Exception(
"MVA input not defined") <<
"Requested to load tau MVA input from ROOT file but no file provided in cfg file";
159 if ( cfg.
exists(
"mvaOutput_normalization") ) {
164 typedef std::vector<edm::ParameterSet> VPSet;
166 for ( VPSet::const_iterator mappingEntry = mapping.begin();
167 mappingEntry != mapping.end(); ++mappingEntry ) {
168 unsigned category = mappingEntry->getParameter<uint32_t>(
"category");
170 if ( mappingEntry->existsAs<
double>(
"cut") ) {
171 cut->cutValue_ = mappingEntry->getParameter<
double>(
"cut");
173 }
else if ( mappingEntry->existsAs<
std::string>(
"cut") ) {
180 <<
" Undefined Configuration Parameter 'cut' !!\n";
185 verbosity_ = ( cfg.
exists(
"verbosity") ) ?
210 for ( DiscriminantCutMap::iterator
cut =
cuts_.begin();
218 cut->second->cutFunction_ = loadObjectFromFile<TGraph>(*
inputFile,
cut->second->cutName_);
221 cut->second->cutFunction_ = loadTGraphFromDB(es,
cut->second->cutName_,
verbosity_);
236 std::cout <<
"<RecoTauDiscriminantCutMultiplexer::discriminate>:" << std::endl;
240 double disc_result = (*toMultiplexHandle_)[
tau];
242 std::cout <<
"disc_result = " << disc_result << std::endl;
249 std::cout <<
"disc_result (normalized) = " << disc_result << std::endl;
252 double key_result = (*keyHandle_)[
tau];
253 DiscriminantCutMap::const_iterator cutIter =
cuts_.find(TMath::Nint(key_result));
257 if ( cutIter ==
cuts_.end() ) {
261 bool passesCuts =
false;
263 passesCuts = (disc_result > cutIter->second->cutValue_);
265 std::cout <<
"cutValue (fixed) = " << cutIter->second->cutValue_ <<
" --> passesCuts = " << passesCuts << std::endl;
268 double cutVariable = (*cutIter->second->cutVariable_)(*tau);
269 double xMin, xMax, dummy;
270 cutIter->second->cutFunction_->GetPoint(0, xMin, dummy);
271 cutIter->second->cutFunction_->GetPoint(cutIter->second->cutFunction_->GetN() - 1, xMax, dummy);
273 if ( cutVariable < (xMin + epsilon) ) cutVariable = xMin + epsilon;
274 else if ( cutVariable > (xMax - epsilon) ) cutVariable = xMax - epsilon;
275 double cutValue = cutIter->second->cutFunction_->Eval(cutVariable);
276 passesCuts = (disc_result > cutValue);
278 std::cout <<
"cutValue (@" << cutVariable <<
") = " << cutValue <<
" --> passesCuts = " << passesCuts << std::endl;
T getParameter(std::string const &) const
std::unique_ptr< const TFormula > mvaOutput_normalization_
std::string mvaOutputNormalizationName_
bool getByToken(EDGetToken token, Handle< PROD > &result) const
edm::Handle< reco::PFTauDiscriminator > keyHandle_
#define DEFINE_FWK_MODULE(type)
void beginEvent(const edm::Event &event, const edm::EventSetup &eventSetup) override
bool exists(std::string const ¶meterName) const
checks if a parameter exists
edm::Handle< reco::PFTauDiscriminator > toMultiplexHandle_
std::unique_ptr< StringObjectFunction< reco::PFTau > > cutVariable_
~RecoTauDiscriminantCutMultiplexer()
double discriminate(const reco::PFTauRef &) const override
edm::EDGetTokenT< reco::PFTauDiscriminator > toMultiplex_token
edm::FileInPath inputFileName_
edm::EDGetTokenT< reco::PFTauDiscriminator > key_token
How EventSelector::AcceptEvent() decides whether to accept an event for output otherwise it is excluding the probing of A single or multiple positive and the trigger will pass if any such matching triggers are PASS or EXCEPTION[A criterion thatmatches no triggers at all is detected and causes a throw.] A single negative with an expectation of appropriate bit checking in the decision and the trigger will pass if any such matching triggers are FAIL or EXCEPTION A wildcarded negative criterion that matches more than one trigger in the trigger but the state exists so we define the behavior If all triggers are the negative crieriion will lead to accepting the event(this again matches the behavior of"!*"before the partial wildcard feature was incorporated).The per-event"cost"of each negative criterion with multiple relevant triggers is about the same as!*was in the past
std::unique_ptr< const TGraph > cutFunction_
LocationCode location() const
Where was the file found?
T const * product() const
edm::InputTag toMultiplex_
RecoTauDiscriminantCutMultiplexer(const edm::ParameterSet &pset)
volatile std::atomic< bool > shutdown_flag false
std::string fullPath() const
std::map< int, std::unique_ptr< DiscriminantCutEntry > > DiscriminantCutMap
double prediscriminantFailValue_