125 pc.defineObject(
"fitModel",
"FitModel",0,0) ;
126 pc.defineObject(
"condObs",
"ProjectedDependents",0,0) ;
127 pc.defineObject(
"protoData",
"PrototypeData",0,0) ;
128 pc.defineSet(
"cPars",
"Constrain",0,0) ;
129 pc.defineSet(
"extCons",
"ExternalConstraints",0,0) ;
130 pc.defineInt(
"silence",
"Silence",0,0) ;
131 pc.defineInt(
"randProtoData",
"PrototypeData",0,0) ;
132 pc.defineInt(
"verboseGen",
"Verbose",0,0) ;
133 pc.defineInt(
"extendedGen",
"Extended",0,0) ;
134 pc.defineInt(
"binGenData",
"Binned",0,0) ;
135 pc.defineInt(
"dummy",
"FitOptArgs",0,0) ;
138 pc.process(cmdList) ;
141 throw std::string(
"RooMCStudy::RooMCStudy() Error in parsing arguments passed to contructor") ;
146 if (
pc.hasProcessed(
"FitOptArgs")) {
166 cPars->
add(*cParsTmp) ;
183 allConstraints.
add(*constraints) ;
189 if (allConstraints.
getSize()>0) {
190 _constrPdf =
new RooProdPdf(
"mcs_constr_prod",
"RooMCStudy constraints product",allConstraints) ;
193 consPars.
add(*cPars) ;
197 consPars.
add(*cparams) ;
205 coutI(
Generation) <<
"RooMCStudy::RooMCStudy: INFO have pdf with constraints, will generate parameters from constraint pdf for each experiment" << endl ;
224 if (
pc.getObject(
"condObs",0)) {
234 oocoutW(
_fitModel,
Generation) <<
"RooMCStudy::RooMCStudy: WARNING Using generator option 'e' (Poisson distribution of #events) together " << endl
235 <<
" with a prototype dataset implies incomplete sampling or oversampling of proto data." << endl
236 <<
" Use option \"r\" to randomize prototype dataset order and thus to randomize" << endl
237 <<
" the set of over/undersampled prototype events for each generation cycle." << endl ;
293 list<RooAbsMCStudyModule*>::iterator iter ;
295 Bool_t ok = (*iter)->doInitializeInstance(*
this) ;
297 oocoutE(
_fitModel,
Generation) <<
"RooMCStudy::ctor: removing study module " << (*iter)->GetName() <<
" from analysis chain because initialization failed" << endl ;
359 list<RooAbsMCStudyModule*>::iterator iter ;
361 (*iter)->initializeRun(nSamples) ;
364 Int_t prescale = nSamples>100 ?
Int_t(nSamples/100) : 1 ;
368 if (nSamples%prescale==0) {
380 Int_t nEvt(nEvtPerSample) ;
398 list<RooAbsMCStudyModule*>::iterator iter2 ;
400 (*iter2)->processBeforeGen(nSamples) ;
424 oocoutI(
_fitModel,
Generation) <<
"RooMCStudy: (Re)randomizing event order in prototype dataset (Nevt=" << nEvt <<
")" << endl ;
430 coutP(
Generation) <<
"RooMCStudy: now generating " << nEvt <<
" events" << endl ;
443 }
else if (asciiFilePat) {
446 char asciiFile[1024] ;
447 snprintf(asciiFile,1024,asciiFilePat,nSamples) ;
455 existingData =
kTRUE ;
466 list<RooAbsMCStudyModule*>::iterator iter3 ;
468 (*iter3)->processBetweenGenAndFit(nSamples) ;
475 (*iter3)->processAfterFit(nSamples) ;
479 if (doGenerate && asciiFilePat && *asciiFilePat) {
480 char asciiFile[1024] ;
481 snprintf(asciiFile,1024,asciiFilePat,nSamples) ;
484 unbinnedData->
write(asciiFile) ;
486 coutE(
InputArguments) <<
"RooMCStudy::run(" <<
GetName() <<
") ERROR: ASCII writing of binned datasets is not supported" << endl ;
501 RooDataSet* auxData = (*iter)->finalizeRun() ;
552 return run(
kTRUE,
kTRUE,nSamples,nEvtPerSample,keepGenData,asciiFilePat) ;
572 return run(
kTRUE,
kFALSE,nSamples,nEvtPerSample,keepGenData,asciiFilePat) ;
650 fitOptList.
Add(&save) ;
652 fitOptList.
Add(&condo) ;
654 fitOptList.
Add(&plevel) ;
676 fr =
doFit(genSample) ;
704 fr =
doFit(genSample) ;
726 if (userSaveRequest) {
784 const auto par =
static_cast<RooRealVar*
>(*it);
789 TString name(par->GetName()), title(par->GetTitle()) ;
790 name.Append(
"pull") ;
793 if (!par->hasError(
false)) {
794 coutW(
Generation) <<
"Fit parameter '" << par->GetName() <<
"' does not have an error."
795 " A pull distribution cannot be generated. This might be caused by the parameter being constant or"
796 " because the fits were not run." << std::endl;
818 coutW(
Generation) <<
"The fit parameter '" << par->GetName() <<
"' is not in the model that was used to generate toy data. "
819 "The parameter '" << genParOrig->GetName() <<
"'=" << genParOrig->getVal() <<
" was found at the same position in the generator model."
820 " It will be used to compute pulls."
821 "\nIf this is not desired, the parameters of the generator model need to be renamed or reordered." << std::endl;
826 std::unique_ptr<RooAbsReal> genPar(
static_cast<RooAbsReal*
>(genParOrig->Clone(
"truth")));
831 coutE(
Generation) <<
"Cannot generate pull distribution for the fit parameter '" << par->GetName() <<
"'."
832 "\nNo similar parameter was found in the set of parameters that were used to generate toy data." << std::endl;
900 << sampleNum <<
", did you use the 'r; fit option?" << endl ;
973 return plotParam(*param,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8) ;
1053 RooPlot* frame =
plotParam(*evar_rrv,arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8) ;
1097 name.Append(
"pull") ; title.
Append(
" Pull") ;
1107 pc.defineInt(
"fitGauss",
"FitGauss",0,0) ;
1108 pc.allowUndefined() ;
1109 pc.process(cmdList) ;
1110 Bool_t fitGauss=
pc.getInt(
"fitGauss") ;
1113 pc.stripCmdList(cmdList,
"FitGauss") ;
1117 coutF(
Plotting) <<
"No pull distribution for the parameter '" << param.
GetName() <<
"'. Check logs for errors." << std::endl;
1123 RooRealVar pullMean(
"pullMean",
"Mean of pull",0,-10,10) ;
1124 RooRealVar pullSigma(
"pullSigma",
"Width of pull",1,0.1,5) ;
1126 "exp(-0.5*(@0-@1)*(@0-@1)/(@2*@2))",
1129 pullGauss.
plotOn(frame) ;
1147 pc.defineInt(
"nbins",
"Bins",0,0) ;
1148 pc.defineDouble(
"xlo",
"Range",0,0) ;
1149 pc.defineDouble(
"xhi",
"Range",1,0) ;
1150 pc.defineInt(
"dummy",
"FrameArgs",0,0) ;
1151 pc.defineMutex(
"Bins",
"FrameArgs") ;
1152 pc.defineMutex(
"Range",
"FrameArgs") ;
1155 pc.allowUndefined() ;
1156 pc.process(cmdList) ;
1162 Int_t nbins =
pc.getInt(
"nbins") ;
1167 if (
pc.hasProcessed(
"FrameArgs")) {
1178 if (
pc.hasProcessed(
"Bins")) frameCmdList.
Add(&bins) ;
1179 if (
pc.hasProcessed(
"Range")) {
1180 frameCmdList.
Add(&range) ;
1182 frameCmdList.
Add(&autor) ;
1184 frame = param.
frame(frameCmdList) ;
1188 pc.stripCmdList(cmdList,
"FrameArgs,Bins,Range") ;
1252 name.Append(
"pull") ; title.
Append(
" Pull") ;
1260 coutF(
Plotting) <<
"No pull distribution for the parameter '" << param.
GetName() <<
"'. Check logs for errors." << std::endl;
1265 RooRealVar pullMean(
"pullMean",
"Mean of pull",0,lo,
hi) ;
1266 RooRealVar pullSigma(
"pullSigma",
"Width of pull",1,0,5) ;
1268 "exp(-0.5*(@0-@1)*(@0-@1)/(@2*@2))",
1271 pullGauss.
plotOn(frame) ;
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t index
char * Form(const char *fmt,...)
Formats a string in a circular formatting buffer.
RooAbsArg is the common abstract base class for objects that represent a value and a "shape" in RooFi...
RooArgSet * getObservables(const RooArgSet &set, Bool_t valueOnly=kTRUE) const
Given a set of possible observables, return the observables that this PDF depends on.
RooArgSet * getParameters(const RooAbsData *data, bool stripDisconnected=true) const
Create a list of leaf nodes in the arg tree starting with ourself as top node that don't match any of...
virtual Bool_t add(const RooAbsArg &var, Bool_t silent=kFALSE)
Add the specified argument to list.
Int_t getSize() const
Return the number of elements in the collection.
const_iterator end() const
void assign(const RooAbsCollection &other) const
Sets the value, cache and constant attribute of any argument in our set that also appears in the othe...
Storage_t::size_type size() const
const_iterator begin() const
void setAttribAll(const Text_t *name, Bool_t value=kTRUE)
Set given attribute in each element of the collection by calling each elements setAttribute() functio...
TIterator * createIterator(Bool_t dir=kIterForward) const
TIterator-style iteration over contained elements.
RooAbsArg * find(const char *name) const
Find object with given name in list.
RooAbsData is the common abstract base class for binned and unbinned datasets.
virtual Bool_t changeObservableName(const char *from, const char *to)
virtual Double_t sumEntries() const =0
Return effective number of entries in dataset, i.e., sum all weights.
void RecursiveRemove(TObject *obj) override
If one of the TObject we have a referenced to is deleted, remove the reference.
virtual Int_t numEntries() const
Return number of entries in dataset, i.e., count unweighted entries.
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
virtual void attach(const RooArgSet ¶ms)
Interface to attach given parameters to object in this context.
virtual RooDataSet * generate(Double_t nEvents=0, Bool_t skipInit=kFALSE, Bool_t extendedMode=kFALSE)
Generate the specified number of events with nEvents>0 and and return a dataset containing the genera...
virtual void setProtoDataOrder(Int_t *lut)
Set the traversal order of prototype data to that in the lookup tables passed as argument.
RooAbsMCStudyModule is a base class for add-on modules to RooMCStudy that can perform additional calc...
Bool_t doInitializeInstance(RooMCStudy &)
Initializer method called upon attachement to given RooMCStudy object.
virtual RooAbsGenContext * genContext(const RooArgSet &vars, const RooDataSet *prototype=0, const RooArgSet *auxProto=0, Bool_t verbose=kFALSE) const
Interface function to create a generator context from a p.d.f.
virtual RooDataHist * generateBinned(const RooArgSet &whatVars, Double_t nEvents, const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none()) const
As RooAbsPdf::generateBinned(const RooArgSet&, const RooCmdArg&,const RooCmdArg&, const RooCmdArg&,...
virtual RooFitResult * fitTo(RooAbsData &data, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Fit PDF to given dataset.
virtual RooPlot * paramOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Add a box with parameter values (and errors) to the specified frame.
virtual RooArgSet * getAllConstraints(const RooArgSet &observables, RooArgSet &constrainedParams, Bool_t stripDisconnected=kTRUE) const
This helper function finds and collects all constraints terms of all component p.d....
Int_t * randomizeProtoOrder(Int_t nProto, Int_t nGen, Bool_t resample=kFALSE) const
Return lookup table with randomized order for nProto prototype events.
virtual Double_t expectedEvents(const RooArgSet *nset) const
Return expected number of events to be used in calculation of extended likelihood.
RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none(), const RooCmdArg &arg9=RooCmdArg::none(), const RooCmdArg &arg10=RooCmdArg::none()) const override
Helper calling plotOn(RooPlot*, RooLinkedList&) const.
RooPlot * frame(const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
Create a new RooPlot on the heap with a drawing frame initialized for this object,...
RooAbsReal is the common abstract base class for objects that represent a real value and implements f...
RooAbsArg * createFundamental(const char *newname=0) const override
Create a RooRealVar fundamental object with our properties.
RooArgList is a container object that can hold multiple RooAbsArg objects.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
RooArgSet * snapshot(bool deepCopy=true) const
Use RooAbsCollection::snapshot(), but return as RooArgSet.
RooCmdArg is a named container for two doubles, two integers two object points and three string point...
RooLinkedList const & subArgs() const
Return list of sub-arguments in this RooCmdArg.
TObject * Clone(const char *newName=0) const override
Make a clone of an object using the Streamer facility.
Class RooCmdConfig is a configurable parser for RooCmdArg named arguments.
The RooDataHist is a container class to hold N-dimensional binned data.
RooDataSet is a container class to hold unbinned data.
const RooArgSet * get(Int_t index) const override
Return RooArgSet with coordinates of event 'index'.
virtual RooAbsArg * addColumn(RooAbsArg &var, Bool_t adjustRange=kTRUE)
Add a column with the values of the given (function) argument to this dataset.
Bool_t write(const char *filename) const
Write the contents of this dataset to an ASCII file with the specified name.
static RooDataSet * read(const char *filename, const RooArgList &variables, const char *opts="", const char *commonPath="", const char *indexCatName=0)
Read data from a text file and create a dataset from it.
Bool_t merge(RooDataSet *data1, RooDataSet *data2=0, RooDataSet *data3=0, RooDataSet *data4=0, RooDataSet *data5=0, RooDataSet *data6=0)
void add(const RooArgSet &row, Double_t weight=1.0, Double_t weightError=0) override
Add one ore more rows of data.
RooErrorVar is an auxilary class that represents the error of a RooRealVar as a seperate object.
RooFitResult is a container class to hold the input and output of a PDF fit to a dataset.
Double_t minNll() const
Return minimized -log(L) value.
const RooArgList & floatParsFinal() const
Return list of floating parameters after fit.
Int_t status() const
Return MINUIT status code.
RooGenericPdf is a concrete implementation of a probability density function, which takes a RooArgLis...
RooLinkedList is an collection class for internal use, storing a collection of RooAbsArg pointers in ...
TObject * At(int index) const
Return object stored in sequential position given by index.
void RecursiveRemove(TObject *obj) override
If one of the TObject we have a referenced to is deleted, remove the reference.
void Delete(Option_t *o=0) override
Remove all elements in collection and delete all elements NB: Collection does not own elements,...
virtual void Add(TObject *arg)
TObject * FindObject(const char *name) const override
Return pointer to obejct with given name.
RooMCStudy is a helper class to facilitate Monte Carlo studies such as 'goodness-of-fit' studies,...
RooAbsData * _genSample
Currently generated sample.
RooArgSet _projDeps
List of projected dependents in fit.
RooPlot * plotNLL(const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Plot the distribution of the -log(L) values on a newly created frame.
const RooArgSet * fitParams(Int_t sampleNum) const
Return an argset with the fit parameters for the given sample number.
void calcPulls()
Calculate the pulls for all fit parameters in the fit results data set, and add them to that dataset.
Bool_t addFitResult(const RooFitResult &fr)
Utility function to add fit result from external fit to this RooMCStudy and process its results throu...
Bool_t run(Bool_t generate, Bool_t fit, Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char *asciiFilePat)
Run engine method.
Bool_t _silence
Silent running mode?
RooArgSet _dependents
List of dependents.
RooMCStudy(const RooAbsPdf &model, const RooArgSet &observables, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Construct Monte Carlo Study Manager.
std::list< RooAbsMCStudyModule * > _modList
List of additional study modules ;.
RooAbsGenContext * _constrGenContext
Generator context for constraints p.d.f.
RooFitResult * refit(RooAbsData *genSample=0)
Redo fit on 'current' toy sample, or if genSample is not NULL do fit on given sample instead.
Bool_t fitSample(RooAbsData *genSample)
Internal method.
const RooDataSet * _genProtoData
Generator prototype data set.
const RooFitResult * fitResult(Int_t sampleNum) const
Return the RooFitResult of the fit with the given run number.
Bool_t _perExptGenParams
Do generation parameter change per event?
RooPlot * plotError(const RooRealVar ¶m, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Plot the distribution of the fit errors for the specified parameter on a newly created frame.
RooAbsGenContext * _genContext
Generator context.
RooAbsPdf * _constrPdf
Constraints p.d.f.
RooArgSet * _fitInitParams
List of initial values of fit parameters.
Bool_t _canAddFitResults
Allow adding of external fit results?
RooPlot * makeFrameAndPlotCmd(const RooRealVar ¶m, RooLinkedList &cmdList, Bool_t symRange=kFALSE) const
Internal function.
RooAbsData * genData(Int_t sampleNum) const
Return the given generated dataset.
RooArgSet * _genInitParams
List of original generator parameters.
void RecursiveRemove(TObject *obj) override
If one of the TObject we have a referenced to is deleted, remove the reference.
RooAbsPdf * _genModel
Generator model.
const RooDataSet & fitParDataSet()
Return a RooDataSet containing the post-fit parameters of each toy cycle.
RooPlot * plotParamOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Plot the distribution of fitted values of a parameter.
RooLinkedList _fitOptList
Bool_t generate(Int_t nSamples, Int_t nEvtPerSample=0, Bool_t keepGenData=kFALSE, const char *asciiFilePat=0)
Generate 'nSamples' samples of 'nEvtPerSample' events.
RooArgSet _allDependents
List of generate + prototype dependents.
RooArgSet * _fitParams
List of actual fit parameters.
void resetFitParams()
Reset all fit parameters to the initial model parameters at the time of the RooMCStudy constructor.
RooArgSet * _genParams
List of actual generator parameters.
Bool_t _verboseGen
Verbose generation?
RooAbsPdf * _fitModel
Fit model.
Bool_t generateAndFit(Int_t nSamples, Int_t nEvtPerSample=0, Bool_t keepGenData=kFALSE, const char *asciiFilePat=0)
Generate and fit 'nSamples' samples of 'nEvtPerSample' events.
Bool_t fit(Int_t nSamples, const char *asciiFilePat)
Fit 'nSamples' datasets, which are read from ASCII files.
RooPlot * plotParam(const RooRealVar ¶m, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Plot the distribution of the fitted value of the given parameter on a newly created frame.
void addModule(RooAbsMCStudyModule &module)
Insert given RooMCStudy add-on module to the processing chain of this MCStudy object.
RooFitResult * doFit(RooAbsData *genSample)
Internal function. Performs actual fit according to specifications.
RooPlot * plotPull(const RooRealVar ¶m, const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Plot the distribution of pull values for the specified parameter on a newly created frame.
static RooMsgService & instance()
Return reference to singleton instance.
void setGlobalKillBelow(RooFit::MsgLevel level)
RooFit::MsgLevel globalKillBelow() const
A RooPlot is a plot frame and a container for graphics objects within that frame.
RooProdPdf is an efficient implementation of a product of PDFs of the form.
RooPullVar represents the pull of a measurement w.r.t.
static TRandom * randomGenerator()
Return a pointer to a singleton random-number generator implementation.
RooRealVar represents a variable that can be changed from the outside.
void setVal(Double_t value) override
Set value of variable to 'value'.
void setBins(Int_t nBins, const char *name=0)
Create a uniform binning under name 'name' for this variable.
RooErrorVar * errorVar() const
Return a RooAbsRealLValue representing the error associated with this variable.
virtual Int_t GetSize() const
Return the capacity of the collection, i.e.
Iterator abstract base class.
virtual TObject * Next()=0
void RecursiveRemove(TObject *obj) override
Remove object from this collection and recursively remove the object from all other objects (and coll...
void Add(TObject *obj) override
TIterator * MakeIterator(Bool_t dir=kIterForward) const override
Return a list iterator.
void Delete(Option_t *option="") override
Remove all objects from the list AND delete all heap based objects.
TObject * At(Int_t idx) const override
Returns the object at position idx. Returns 0 if idx is out of range.
The TNamed class is the base class for all named ROOT classes.
const char * GetName() const override
Returns name of object.
const char * GetTitle() const override
Returns title of object.
Mother of all ROOT objects.
virtual Int_t Poisson(Double_t mean)
Generates a random integer N according to a Poisson law.
const char * Data() const
TString & Append(const char *cs)
RooCmdArg AutoSymRange(const RooAbsData &data, Double_t marginFactor=0.1)
RooCmdArg AutoRange(const RooAbsData &data, Double_t marginFactor=0.1)
RooCmdArg Bins(Int_t nbin)
RooCmdArg Constrain(const RooArgSet ¶ms)
RooCmdArg ExternalConstraints(const RooArgSet &constraintPdfs)
RooCmdArg Save(Bool_t flag=kTRUE)
RooCmdArg PrintLevel(Int_t code)
RooCmdArg ConditionalObservables(Args_t &&... argsOrArgSet)
Create a RooCmdArg to declare conditional observables.
RooCmdArg Minos(Bool_t flag=kTRUE)
RooCmdArg Range(const char *rangeName, Bool_t adjustNorm=kTRUE)
MsgLevel
Verbosity level for RooMsgService::StreamConfig in RooMsgService.
static constexpr double pc