RooMCStudy

class RooMCStudy

    private:

                 RooMCStudy(const RooMCStudy&)

    protected:

          void calcPulls()
        Bool_t fitSample(RooAbsData* genSample)
      RooPlot* makeFrameAndPlotCmd(const RooRealVar& param, RooLinkedList& cmdList, Bool_t symRange = kFALSE) const
        Bool_t run(Bool_t generate, Bool_t fit, Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char* asciiFilePat)

    public:

                          RooMCStudy(const RooAbsPdf& model, const RooArgSet& observables, RooCmdArg arg1 = RooCmdArg::none, RooCmdArg arg2 = RooCmdArg::none, RooCmdArg arg3 = RooCmdArg::none, RooCmdArg arg4 = RooCmdArg::none, RooCmdArg arg5 = RooCmdArg::none, RooCmdArg arg6 = RooCmdArg::none, RooCmdArg arg7 = RooCmdArg::none, RooCmdArg arg8 = RooCmdArg::none)
                          RooMCStudy(const RooAbsPdf& genModel, const RooAbsPdf& fitModel, const RooArgSet& dependents, const char* genOptions = "", const char* fitOptions = "", const RooDataSet* genProtoData = 0, const RooArgSet& projDeps = RooArgSet())
                  virtual ~RooMCStudy()
                   Bool_t addFitResult(const RooFitResult& fr)
           static TClass* Class()
                   Bool_t fit(Int_t nSamples, const char* asciiFilePat)
                   Bool_t fit(Int_t nSamples, TList& dataSetList)
         const RooArgSet* fitParams(Int_t sampleNum) const
        const RooDataSet& fitParDataSet() const
      const RooFitResult* fitResult(Int_t sampleNum) const
        const RooDataSet* genData(Int_t sampleNum) const
                   Bool_t generate(Int_t nSamples, Int_t nEvtPerSample = 0, Bool_t keepGenData = kFALSE, const char* asciiFilePat = "0")
                   Bool_t generateAndFit(Int_t nSamples, Int_t nEvtPerSample = 0, Bool_t keepGenData = kFALSE, const char* asciiFilePat = "0")
          virtual TClass* IsA() const
                 RooPlot* plotError(const RooRealVar& param, 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)
                 RooPlot* plotError(const RooRealVar& param, Double_t lo, Double_t hi, Int_t nbins = 100)
                 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)
                 RooPlot* plotNLL(Double_t lo, Double_t hi, Int_t nBins = 100)
                 RooPlot* plotParam(const RooRealVar& param, 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)
                 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)
                 RooPlot* plotPull(const RooRealVar& param, 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)
                 RooPlot* plotPull(const RooRealVar& param, Double_t lo = -3.0, Double_t hi = 3.0, Int_t nbins = 25, Bool_t fitGauss = kFALSE)
             virtual void ShowMembers(TMemberInspector& insp, char* parent)
             virtual void Streamer(TBuffer& b)
                     void StreamerNVirtual(TBuffer& b)

Data Members

    protected:

             RooAbsPdf* _genModel          Generator model 
      RooAbsGenContext* _genContext        Generator context 
             RooArgSet* _genParams         List of fit parameters
      const RooDataSet* _genProtoData      Generator prototype data set
              RooArgSet _projDeps          List of projected dependents in fit
              RooArgSet _dependents        List of dependents 
              RooArgSet _allDependents     List of generate + prototype dependents
             RooAbsPdf* _fitModel          Fit model 
             RooArgSet* _fitInitParams     List of initial values of fit parameters
             RooArgSet* _fitParams         List of fit parameters
            RooRealVar* _nllVar            
                  TList _genDataList       List of generated data sample
                  TList _fitResList        List of RooFitResult fit output objects
            RooDataSet* _fitParData        Data set of fit parameters of each sample
                TString _fitOptions        Fit options string
          RooLinkedList _fitOptList        Fit option command list 
                 Bool_t _extendedGen       Add poisson term to number of events to generate?
                 Bool_t _binGenData        Bin data between generating and fitting
               Double_t _nExpGen           Number of expected events to generate in extended mode
                 Bool_t _randProto         Randomize order of prototype data access
                 Bool_t _canAddFitResults  Allow adding of external fit results?
                 Bool_t _verboseGen        Verbose generation?

Class Description

 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()

 Destructor

 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().

 Calculate the pulls for all fit parameters in
 the fit results data set, and add them to that dataset

 Return the fit parameter dataset

 Return an argset with the fit parameters for the given sample number
 NB: The fit parameters are only stored for successfull fits,
     thus the maximum sampleNum can be less that the number
     of generated samples and if so, the indeces will
     be out of synch with genData() and fitResult()

 Return the fit result object of the fit to given sample

 Return the given generated dataset

 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 -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.

Inline Functions

         RooMCStudy RooMCStudy(const RooAbsPdf& genModel, const RooAbsPdf& fitModel, const RooArgSet& dependents, const char* genOptions = "", const char* fitOptions = "", const RooDataSet* genProtoData = 0, const RooArgSet& projDeps = RooArgSet())
         RooMCStudy RooMCStudy(const RooMCStudy&)
            TClass* Class()
            TClass* IsA() const
               void ShowMembers(TMemberInspector& insp, char* parent)
               void Streamer(TBuffer& b)
               void StreamerNVirtual(TBuffer& b)