void | calcPulls() |
RooFitResult* | doFit(RooAbsData* genSample) |
Bool_t | fitSample(RooAbsData* genSample) |
RooPlot* | makeFrameAndPlotCmd(const RooRealVar& param, RooLinkedList& cmdList, Bool_t symRange = kFALSE) const |
RooFitResult* | refit(RooAbsData* genSample = 0) |
void | resetFitParams() |
Bool_t | run(Bool_t generate, Bool_t fit, Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char* asciiFilePat) |
RooMCStudy(const RooMCStudy&) |
RooArgSet | _allDependents | List of generate + prototype dependents |
Bool_t | _binGenData | Bin data between generating and fitting |
Bool_t | _canAddFitResults | Allow adding of external fit results? |
RooArgSet | _dependents | List of dependents |
Bool_t | _extendedGen | Add poisson term to number of events to generate? |
RooArgSet* | _fitInitParams | List of initial values of fit parameters |
RooAbsPdf* | _fitModel | Fit model |
RooLinkedList | _fitOptList | Fit option command list |
TString | _fitOptions | Fit options string |
RooDataSet* | _fitParData | Data set of fit parameters of each sample |
RooArgSet* | _fitParams | List of actual fit parameters |
TList | _fitResList | List of RooFitResult fit output objects |
RooAbsGenContext* | _genContext | Generator context |
TList | _genDataList | List of generated data sample |
RooArgSet* | _genInitParams | List of originalgenerator parameters |
RooAbsPdf* | _genModel | Generator model |
RooArgSet* | _genParams | List of actual generator parameters |
const RooDataSet* | _genProtoData | Generator prototype data set |
RooDataSet* | _genSample | Currently generated sample |
list<RooAbsMCStudyModule*> | _modList | List of additional study modules ; |
Double_t | _nExpGen | Number of expected events to generate in extended mode |
RooRealVar* | _nllVar | |
RooArgSet | _projDeps | List of projected dependents in fit |
Bool_t | _randProto | Randomize order of prototype data access |
Bool_t | _verboseGen | Verbose generation? |
Construct Monte Carlo Study Manager. This class automates generating data from a given PDF, fitting the PDF to that data and accumulating the fit statistics. The constructor accepts the following arguments model -- The PDF to be studied observables -- The variables of the PDF to be considered the observables FitModel(const RooAbsPdf&) -- The PDF for fitting, if it is different from the PDF for generating ConditionalObservables (const RooArgSet& set) -- The set of observables that the PDF should _not_ be normalized over Binned(Bool_t flag) -- Bin the dataset before fitting it. Speeds up fitting of large data samples FitOptions(const char*) -- Classic fit options, provided for backward compatibility FitOptions(....) -- Options to be used for fitting. All named arguments inside FitOptions() are passed to RooAbsPdf::fitTo(); Verbose(Bool_t flag) -- Activate informational messages in event generation phase Extended(Bool_t flag) -- Determine number of events for each sample anew from a Poisson distribution ProtoData(const RooDataSet&, Bool_t randOrder) -- Prototype data for the event generation. If the randOrder flag is set, the order of the dataset will be re-randomized for each generation cycle to protect against systematic biases if the number of generated events does not exactly match the number of events in the prototype dataset at the cost of reduced precision with mu equal to the specified number of events Stuff all arguments in a list
Constructor with a generator and fit model. Both models may point to the same object. The 'dependents' set of variables is generated in the generator phase. The optional prototype dataset is passed to the generator Available generator options v - Verbose e - Extended: use Poisson distribution for Nevts generated Available fit options See RooAbsPdf::fitTo()
Run engine. Generate and/or fit, according to flags, 'nSamples' samples of 'nEvtPerSample' events. If keepGenData is set, all generated data sets will be kept in memory and can be accessed later via genData(). When generating, data sets will be written out in ascii form if the pattern string is supplied The pattern, which is a template for sprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number. When fitting only, data sets may optionally be read from ascii files, using the same file pattern.
Generate and fit 'nSamples' samples of 'nEvtPerSample' events. If keepGenData is set, all generated data sets will be kept in memory and can be accessed later via genData(). Data sets will be written out is ascii form if the pattern string is supplied. The pattern, which is a template for sprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number.
Generate 'nSamples' samples of 'nEvtPerSample' events. If keepGenData is set, all generated data sets will be kept in memory and can be accessed later via genData(). Data sets will be written out in ascii form if the pattern string is supplied. The pattern, which is a template for sprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number.
Fit 'nSamples' datasets, which are read from ASCII files.
The ascii file pattern, which is a template for sprintf, should look something like "data/toymc_%04d.dat"
and should contain one integer field that encodes the sample serial number.
Fit 'nSamples' datasets, as supplied in 'dataSetList'
Fit given dataset with fit model. If fit converges (TMinuit status code zero) The fit results are appended to the fit results dataset If the fit option "r" is supplied, the RooFitResult objects will always be saved, regardless of the fit status. RooFitResults objects can be retrieved later via fitResult().
Plot the distribution of the fitted value of the given parameter on the specified frame Any specified named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Plot the distribution of the fitted value of the given parameter on a newly created frame. This function accepts the following optional arguments FrameRange(double lo, double hi) -- Set range of frame to given specification FrameBins(int bins) -- Set default number of bins of frame to given number Frame(...) -- Pass supplied named arguments to RooAbsRealLValue::frame() function. See frame() function for list of allowed arguments If no frame specifications are given, the AutoRange() feature will be used to set the range Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Plot the distribution of the fitted value of the given parameter on a newly created frame. This function accepts the following optional arguments FrameRange(double lo, double hi) -- Set range of frame to given specification FrameBins(int bins) -- Set default number of bins of frame to given number Frame(...) -- Pass supplied named arguments to RooAbsRealLValue::frame() function. See frame() function for list of allowed arguments If no frame specifications are given, the AutoRange() feature will be used to set the range Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Plot the distribution of the -log(l) values on a newly created frame. This function accepts the following optional arguments FrameRange(double lo, double hi) -- Set range of frame to given specification FrameBins(int bins) -- Set default number of bins of frame to given number Frame(...) -- Pass supplied named arguments to RooAbsRealLValue::frame() function. See frame() function for list of allowed arguments If no frame specifications are given, the AutoRange() feature will be used to set the range Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Plot the distribution of the fit errors for the specified parameter on a newly created frame. This function accepts the following optional arguments FrameRange(double lo, double hi) -- Set range of frame to given specification FrameBins(int bins) -- Set default number of bins of frame to given number Frame(...) -- Pass supplied named arguments to RooAbsRealLValue::frame() function. See frame() function for list of allowed arguments If no frame specifications are given, the AutoRange() feature will be used to set the range Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Plot the distribution of pull values for the specified parameter on a newly created frame. If asymmetric errors are calculated in the fit (by MINOS) those will be used in the pull calculation This function accepts the following optional arguments FrameRange(double lo, double hi) -- Set range of frame to given specification FrameBins(int bins) -- Set default number of bins of frame to given number Frame(...) -- Pass supplied named arguments to RooAbsRealLValue::frame() function. See frame() function for list of allowed arguments FitGauss(Bool_t flag) -- Add a gaussian fit to the frame If no frame specifications are given, the AutoSymRange() feature will be used to set the range Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options
Create a RooPlot of the NLL distribution in the range lo-hi with 'nBins' bins
Create a RooPlot of the distribution of the fitted errors of the given parameter. The range lo-hi is plotted in nbins bins
Create a RooPlot of the pull distribution for the given parameter. The range lo-hi is plotted in nbins. If fitGauss is set, an unbinned max. likelihood fit of the distribution to a Gaussian model is performed. The fit result is overlaid on the returned RooPlot and a box with the fitted mean and sigma is added.