Docs | All | Real | Category | PDF | DataSet | Plot | Container | Misc | Aux | User

RooFit Toolkit for Data Modeling
#include "RooMCStudy.hh"

RooMCStudy


class description - source file - inheritance tree (.pdf)

class RooMCStudy

Inheritance Chart:
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

 RooMCStudy is a help class to facilitate Monte Carlo studies
 such as 'goodness-of-fit' studies, that involve fitting a PDF
 to multiple toy Monte Carlo sets generated from the same PDF
 or another PDF.

 Given a fit PDF and a generator PDF, RooMCStudy can produce
 large numbers of toyMC samples and/or fit these samples
 and acculumate the final parameters of each fit in a dataset.

 Additional plotting routines simplify the task of plotting
 the distribution of the minimized likelihood, each parameters fitted value,
 fitted error and pull distribution.

RooMCStudy(const RooAbsPdf& genModel, const RooAbsPdf& fitModel, const RooArgSet& dependents, const char* genOptions, const char* fitOptions, const RooDataSet* genProtoData, const RooArgSet& projDeps) : _genModel((RooAbsPdf*)&genModel), _genProtoData(genProtoData), _projDeps(projDeps), _dependents(dependents), _allDependents(dependents), _fitModel((RooAbsPdf*)&fitModel), _fitOptions(fitOptions), _canAddFitResults(kTRUE)
 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()


~RooMCStudy()
 Destructor

Bool_t run(Bool_t generate, Bool_t fit, Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char* asciiFilePat)
 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.


Bool_t generateAndFit(Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char* asciiFilePat)
 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.


Bool_t generate(Int_t nSamples, Int_t nEvtPerSample, Bool_t keepGenData, const char* asciiFilePat)
 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.


Bool_t fit(Int_t nSamples, const char* asciiFilePat)
 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.


Bool_t fit(Int_t nSamples, TList& dataSetList)
 Fit 'nSamples' datasets, as supplied in 'dataSetList'


Bool_t fitSample(RooAbsData* genSample)
 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().


Bool_t addFitResult(const RooFitResult& fr)

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

const RooDataSet& fitParDataSet()
 Return the fit parameter dataset

const RooArgSet* fitParams(Int_t sampleNum) const
 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()

const RooFitResult* fitResult(Int_t sampleNum) const
 Return the fit result object of the fit to given sample

const RooDataSet* genData(Int_t sampleNum) const
 Return the given generated dataset

RooPlot* plotParamOn(RooPlot* frame, const RooCmdArg& arg1, const RooCmdArg& arg2, const RooCmdArg& arg3, const RooCmdArg& arg4, const RooCmdArg& arg5, const RooCmdArg& arg6, const RooCmdArg& arg7, const RooCmdArg& arg8)
 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

RooPlot* plotParam(const RooRealVar& param, const RooCmdArg& arg1, const RooCmdArg& arg2, const RooCmdArg& arg3, const RooCmdArg& arg4, const RooCmdArg& arg5, const RooCmdArg& arg6, const RooCmdArg& arg7, const RooCmdArg& arg8)
 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

RooPlot* plotNLL(const RooCmdArg& arg1, const RooCmdArg& arg2, const RooCmdArg& arg3, const RooCmdArg& arg4, const RooCmdArg& arg5, const RooCmdArg& arg6, const RooCmdArg& arg7, const RooCmdArg& arg8)
 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

RooPlot* plotError(const RooRealVar& param, const RooCmdArg& arg1, const RooCmdArg& arg2, const RooCmdArg& arg3, const RooCmdArg& arg4, const RooCmdArg& arg5, const RooCmdArg& arg6, const RooCmdArg& arg7, const RooCmdArg& arg8)
 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

RooPlot* plotPull(const RooRealVar& param, const RooCmdArg& arg1, const RooCmdArg& arg2, const RooCmdArg& arg3, const RooCmdArg& arg4, const RooCmdArg& arg5, const RooCmdArg& arg6, const RooCmdArg& arg7, const RooCmdArg& arg8)
 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

RooPlot* makeFrameAndPlotCmd(const RooRealVar& param, RooLinkedList& cmdList, Bool_t symRange) const

RooPlot* plotNLL(Double_t lo, Double_t hi, Int_t nBins)
 Create a RooPlot of the NLL distribution in the range lo-hi
 with 'nBins' bins

RooPlot* plotError(const RooRealVar& param, Double_t lo, Double_t hi, Int_t nbins)
 Create a RooPlot of the distribution of the fitted errors of the given parameter.
 The range lo-hi is plotted in nbins bins

RooPlot* plotPull(const RooRealVar& param, Double_t lo, Double_t hi, Int_t nbins, Bool_t fitGauss)
 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)
Last CVS Update: v 1.30 2005/06/20 15:44:54 wverkerke Top
Copyright © 2000-2005 University of California, Stanford University

Page maintained by Wouter Verkerke and David Kirkby

SourceForge.net Logo