RooMCStudy is a helper class to facilitate Monte Carlo studies such as 'goodness-of-fit' studies, that involve fitting a PDF to multiple toy Monte Carlo sets.

These may be generated from either same PDF or from a different PDF with similar parameters.

Given a fit and a generator PDF (they might be identical), RooMCStudy can produce toyMC samples and/or fit these. It accumulates the post-fit parameters of each iteration in a dataset. These can be retrieved using fitParams() or fitParDataSet(). This dataset additionally contains the variables

NLL: The value of the negative log-likelihood for each run.
ngen: The number of events generated for each run.

Additional plotting routines simplify the task of plotting the distribution of the minimized likelihood, the fitted parameter values, fitted error and pull distribution.

RooMCStudy provides the option to insert add-in modules that modify the generate-and-fit cycle and allow to perform extra steps in the cycle. Output of these modules can be stored alongside the fit results in the aggregate results dataset. These study modules should derive from the class RooAbsMCStudyModule.

Check the RooFit tutorials

rf801_mcstudy.C
rf802_mcstudy_addons.C
rf803_mcstudy_addons2.C
rf804_mcstudy_constr.C for usage examples.

Definition at line 32 of file RooMCStudy.h.

Public Member Functions
	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 (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.

virtual	~RooMCStudy ()

Bool_t	addFitResult (const RooFitResult &fr)
	Utility function to add fit result from external fit to this RooMCStudy and process its results through the standard RooMCStudy statistics gathering tools.

void	addModule (RooAbsMCStudyModule &module)
	Insert given RooMCStudy add-on module to the processing chain of this MCStudy object.

Bool_t	fit (Int_t nSamples, const char *asciiFilePat)
	Fit 'nSamples' datasets, which are read from ASCII files.

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

const RooArgSet *	fitParams (Int_t sampleNum) const
	Return an argset with the fit parameters for the given sample number.

const RooDataSet &	fitParDataSet ()
	Return a RooDataSet containing the post-fit parameters of each toy cycle.

const RooFitResult *	fitResult (Int_t sampleNum) const
	Return the RooFitResult of the fit with the given run number.

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

Bool_t	generate (Int_t nSamples, Int_t nEvtPerSample=0, Bool_t keepGenData=kFALSE, const char *asciiFilePat=0)
	Generate 'nSamples' samples of 'nEvtPerSample' events.

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.

const RooDataSet *	genParDataSet () const
	Return dataset with generator parameters for each toy.

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())
	Plot the distribution of the fit errors for the specified parameter on a newly created frame.

RooPlot *	plotError (const RooRealVar &param, Double_t lo, Double_t hi, Int_t nbins=100)
	Create a RooPlot of the distribution of the fitted errors of the given parameter.

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.

RooPlot *	plotNLL (Double_t lo, Double_t hi, Int_t nBins=100)
	Create a RooPlot of the -log(L) distribution in the range lo-hi with 'nBins' bins.

RooPlot *	plotParam (const char *paramName, 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.

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())
	Plot the distribution of the fitted value of the given parameter on a newly created frame.

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.

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())
	Plot the distribution of pull values for the specified parameter on a newly created frame.

RooPlot *	plotPull (const RooRealVar &param, Double_t lo=-3.0, Double_t hi=3.0, Int_t nbins=25, Bool_t fitGauss=kFALSE)
	Create a RooPlot of the pull distribution for the given parameter.

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

	TNamed (const TNamed &named)
	TNamed copy ctor.

	TNamed (const TString &name, const TString &title)

virtual	~TNamed ()
	TNamed destructor.

virtual void	Clear (Option_t *option="")
	Set name and title to empty strings ("").

virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility.

virtual Int_t	Compare (const TObject *obj) const
	Compare two TNamed objects.

virtual void	Copy (TObject &named) const
	Copy this to obj.

virtual void	FillBuffer (char *&buffer)
	Encode TNamed into output buffer.

virtual const char *	GetName () const
	Returns name of object.

virtual const char *	GetTitle () const
	Returns title of object.

virtual ULong_t	Hash () const
	Return hash value for this object.

virtual Bool_t	IsSortable () const

virtual void	ls (Option_t *option="") const
	List TNamed name and title.

TNamed &	operator= (const TNamed &rhs)
	TNamed assignment operator.

virtual void	Print (Option_t *option="") const
	Print TNamed name and title.

virtual void	SetName (const char *name)
	Set the name of the TNamed.

virtual void	SetNameTitle (const char name, const char title)
	Set all the TNamed parameters (name and title).

virtual void	SetTitle (const char *title="")
	Set the title of the TNamed.

virtual Int_t	Sizeof () const
	Return size of the TNamed part of the TObject.

Public Member Functions inherited from TObject
	TObject ()
	TObject constructor.

	TObject (const TObject &object)
	TObject copy ctor.

virtual	~TObject ()
	TObject destructor.

void	AbstractMethod (const char *method) const
	Use this method to implement an "abstract" method that you don't want to leave purely abstract.

virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad.

virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action.

ULong_t	CheckedHash ()
	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.

virtual const char *	ClassName () const
	Returns name of class to which the object belongs.

virtual void	Delete (Option_t *option="")
	Delete this object.

virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object.

virtual void	Draw (Option_t *option="")
	Default Draw method for all objects.

virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs.

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current selected pad for instance with: `gROOT->SetSelectedPad(gPad)`.

virtual void	Dump () const
	Dump contents of object on stdout.

virtual void	Error (const char method, const char msgfmt,...) const
	Issue error message.

virtual void	Execute (const char method, const char params, Int_t *error=0)
	Execute method on this object with the given parameter string, e.g.

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=0)
	Execute method on this object with parameters stored in the TObjArray.

virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py).

virtual void	Fatal (const char method, const char msgfmt,...) const
	Issue fatal error message.

virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes.

virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes.

virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object.

virtual const char *	GetIconName () const
	Returns mime type name of object.

virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py).

virtual Option_t *	GetOption () const

virtual UInt_t	GetUniqueID () const
	Return the unique object id.

virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out.

Bool_t	HasInconsistentHash () const
	Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.

virtual void	Info (const char method, const char msgfmt,...) const
	Issue info message.

virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname".

virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl.

virtual void	Inspect () const
	Dump contents of this object in a graphics canvas.

void	InvertBit (UInt_t f)

virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory).

virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).

R__ALWAYS_INLINE Bool_t	IsOnHeap () const

R__ALWAYS_INLINE Bool_t	IsZombie () const

void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary).

virtual Bool_t	Notify ()
	This method must be overridden to handle object notification.

void	Obsolete (const char method, const char asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete.

void	operator delete (void *ptr)
	Operator delete.

void	operator delete[] (void *ptr)
	Operator delete [].

void *	operator new (size_t sz)

void *	operator new (size_t sz, void *vp)

void *	operator new[] (size_t sz)

void *	operator new[] (size_t sz, void *vp)

TObject &	operator= (const TObject &rhs)
	TObject assignment operator.

virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself.

virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list.

virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory.

void	ResetBit (UInt_t f)

virtual void	SaveAs (const char filename="", Option_t option="") const
	Save this object in the file specified by filename.

virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out".

void	SetBit (UInt_t f)

void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f.

virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object.

virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id.

virtual void	SysError (const char method, const char msgfmt,...) const
	Issue system error message.

R__ALWAYS_INLINE Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked.

virtual void	Warning (const char method, const char msgfmt,...) const
	Issue warning message.

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory.

virtual Int_t	Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory.

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

RooFitResult *	doFit (RooAbsData *genSample)
	Internal function. Performs actual fit according to specifications.

Bool_t	fitSample (RooAbsData *genSample)
	Internal method.

RooPlot *	makeFrameAndPlotCmd (const RooRealVar &param, RooLinkedList &cmdList, Bool_t symRange=kFALSE) const
	Internal function.

virtual void	RecursiveRemove (TObject *obj)
	If one of the TObject we have a referenced to is deleted, remove the reference.

RooFitResult *	refit (RooAbsData *genSample=0)
	Redo fit on 'current' toy sample, or if genSample is not NULL do fit on given sample instead.

void	resetFitParams ()
	Reset all fit parameters to the initial model parameters at the time of the RooMCStudy constructor.

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

Protected Member Functions inherited from TObject
virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected).

void	MakeZombie ()

Protected Attributes
RooArgSet	_allDependents

Bool_t	_binGenData

Bool_t	_canAddFitResults

RooAbsGenContext *	_constrGenContext

RooAbsPdf *	_constrPdf

RooArgSet	_dependents

Bool_t	_extendedGen

RooArgSet *	_fitInitParams

RooAbsPdf *	_fitModel

TString	_fitOptions

RooLinkedList	_fitOptList

RooArgSet *	_fitParams

RooDataSet *	_fitParData

TList	_fitResList

RooAbsGenContext *	_genContext

TList	_genDataList

RooArgSet *	_genInitParams

RooAbsPdf *	_genModel

RooArgSet *	_genParams

RooDataSet *	_genParData

const RooDataSet *	_genProtoData

RooAbsData *	_genSample

std::list< RooAbsMCStudyModule * >	_modList

Double_t	_nExpGen

RooRealVar *	_ngenVar

RooRealVar *	_nllVar

Bool_t	_perExptGenParams

RooArgSet	_projDeps

Bool_t	_randProto

Bool_t	_silence

Bool_t	_verboseGen

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

Private Member Functions
	RooMCStudy (const RooMCStudy &)

Friends
class	RooAbsMCStudyModule

Additional Inherited Members
Public Types inherited from TObject
enum	{ kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 , kBitMask = 0x00ffffff }

enum	{ kSingleKey = BIT(0) , kOverwrite = BIT(1) , kWriteDelete = BIT(2) }

enum	EDeprecatedStatusBits { kObjInCanvas = BIT(3) }

enum	EStatusBits { kCanDelete = BIT(0) , kMustCleanup = BIT(3) , kIsReferenced = BIT(4) , kHasUUID = BIT(5) , kCannotPick = BIT(6) , kNoContextMenu = BIT(8) , kInvalidObject = BIT(13) }

Static Public Member Functions inherited from TObject
static Long_t	GetDtorOnly ()
	Return destructor only flag.

static Bool_t	GetObjectStat ()
	Get status of object stat flag.

static void	SetDtorOnly (void *obj)
	Set destructor only flag.

static void	SetObjectStat (Bool_t stat)
	Turn on/off tracking of objects in the TObjectTable.

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = BIT(3) }

#include <RooMCStudy.h>

Inheritance diagram for RooMCStudy:

[legend]

Constructor & Destructor Documentation

◆ RooMCStudy() [1/3]

RooMCStudy::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.

This class automates generating data from a given PDF, fitting the PDF to data and accumulating the fit statistics.

Parameters

[in]	model	The PDF to be studied
[in]	observables	The variables of the PDF to be considered observables
[in]	argX	Arguments from the table below

Optional arguments
Silence()	Suppress all RooFit messages during running below PROGRESS level
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(). `Save()` is especially interesting to be able to retrieve fit results of each run using fitResult().
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
Constrain(const RooArgSet& pars)	Apply internal constraints on given parameters in fit and sample constrained parameter values from constraint p.d.f for each toy.
ExternalConstraints(const RooArgSet& )	Apply internal constraints on given parameters in fit and sample constrained parameter values from constraint p.d.f for each toy.
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

Definition at line 113 of file RooMCStudy.cxx.

◆ RooMCStudy() [2/3]

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()`
	)

Deprecated:: PLEASE USE CONSTRUCTOR WITH NAMED ARGUMENTS. RETAINED FOR BACKWARD COMPATIBILY.

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()

Definition at line 330 of file RooMCStudy.cxx.

◆ ~RooMCStudy()

RooMCStudy::~RooMCStudy ( )

virtual

Definition at line 422 of file RooMCStudy.cxx.

◆ RooMCStudy() [3/3]

RooMCStudy::RooMCStudy ( const RooMCStudy & )

private

Member Function Documentation

◆ addFitResult()

Bool_t RooMCStudy::addFitResult ( const RooFitResult & fr )

Utility function to add fit result from external fit to this RooMCStudy and process its results through the standard RooMCStudy statistics gathering tools.

This function allows users to run the toy MC generation and/or fitting in a distributed way and to collect and analyze the results in a RooMCStudy as if they were run locally.

This method is only functional if this RooMCStudy object is cleanm, i.e. it was not used to generate and/or fit any samples.

Definition at line 880 of file RooMCStudy.cxx.

◆ addModule()

void RooMCStudy::addModule ( RooAbsMCStudyModule & module )

Insert given RooMCStudy add-on module to the processing chain of this MCStudy object.

Definition at line 445 of file RooMCStudy.cxx.

◆ calcPulls()

void RooMCStudy::calcPulls ( )

protected

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

Definition at line 914 of file RooMCStudy.cxx.

◆ doFit()

RooFitResult * RooMCStudy::doFit ( RooAbsData * genSample )

protected

Internal function. Performs actual fit according to specifications.

Definition at line 748 of file RooMCStudy.cxx.

◆ fit() [1/2]

Bool_t RooMCStudy::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 snprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number.

Definition at line 699 of file RooMCStudy.cxx.

◆ fit() [2/2]

Bool_t RooMCStudy::fit	(	Int_t	nSamples,
		TList &	dataSetList
	)

Fit 'nSamples' datasets, as supplied in 'dataSetList'.

Definition at line 714 of file RooMCStudy.cxx.

◆ fitParams()

const RooArgSet * RooMCStudy::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()

Definition at line 1001 of file RooMCStudy.cxx.

◆ fitParDataSet()

const RooDataSet & RooMCStudy::fitParDataSet ( )

Return a RooDataSet containing the post-fit parameters of each toy cycle.

This dataset also contains any additional output that was generated by study modules that were added to this RooMCStudy. By default, the two following variables are added (apart from fit parameters):

NLL: The value of the negative log-likelihood for each run.
ngen: Number of events generated for each run.

Definition at line 981 of file RooMCStudy.cxx.

◆ fitResult()

const RooFitResult * RooMCStudy::fitResult ( Int_t sampleNum ) const

Return the RooFitResult of the fit with the given run number.

Note: Fit results are not saved by default. This requires passing FitOptions(Save(), ...) to the constructor.

Definition at line 1019 of file RooMCStudy.cxx.

◆ fitSample()

Bool_t RooMCStudy::fitSample ( RooAbsData * genSample )

protected

Internal method.

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().

Definition at line 826 of file RooMCStudy.cxx.

◆ genData()

RooAbsData * RooMCStudy::genData ( Int_t sampleNum ) const

Return the given generated dataset.

This method will only return datasets if during the run cycle it was indicated that generator data should be saved.

Definition at line 1044 of file RooMCStudy.cxx.

◆ generate()

Bool_t RooMCStudy::generate	(	Int_t	nSamples,
		Int_t	nEvtPerSample = `0`,
		Bool_t	keepGenData = `kFALSE`,
		const char *	asciiFilePat = `0`
	)

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 snprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number.

Definition at line 682 of file RooMCStudy.cxx.

◆ generateAndFit()

Bool_t RooMCStudy::generateAndFit	(	Int_t	nSamples,
		Int_t	nEvtPerSample = `0`,
		Bool_t	keepGenData = `kFALSE`,
		const char *	asciiFilePat = `0`
	)

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 in ascii form if the pattern string is supplied. The pattern, which is a template for snprintf, should look something like "data/toymc_%04d.dat" and should contain one integer field that encodes the sample serial number.

Definition at line 660 of file RooMCStudy.cxx.

◆ genParDataSet()

const RooDataSet * RooMCStudy::genParDataSet ( ) const

inline

Return dataset with generator parameters for each toy.

When constraints are used these may generally not be the same as the fitted parameters.

Definition at line 64 of file RooMCStudy.h.

◆ makeFrameAndPlotCmd()

RooPlot * RooMCStudy::makeFrameAndPlotCmd	(	const RooRealVar &	param,
		RooLinkedList &	cmdList,
		Bool_t	symRange = `kFALSE`
	)		const

protected

Internal function.

Construct RooPlot from given parameter and modify the list of named arguments 'cmdList' to only contain the plot arguments that should be forwarded to RooAbsData::plotOn()

Definition at line 1276 of file RooMCStudy.cxx.

◆ plotError() [1/2]

RooPlot * RooMCStudy::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()`
	)

Plot the distribution of the fit errors for the specified parameter on a newly created frame.

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 there for list of allowed arguments

If no frame specifications are given, the AutoRange() feature will be used to set a default range. Any other named argument is passed to the RooAbsData::plotOn() call. See that function for allowed options.

Definition at line 1174 of file RooMCStudy.cxx.

◆ plotError() [2/2]

RooPlot * RooMCStudy::plotError	(	const RooRealVar &	param,
		Double_t	lo,
		Double_t	hi,
		Int_t	nbins = `100`
	)

Create a RooPlot of the distribution of the fitted errors of the given parameter.

The frame is created with a range [lo,hi] and plotted data will be binned in 'nbins' bins

Definition at line 1346 of file RooMCStudy.cxx.

◆ plotNLL() [1/2]

RooPlot * RooMCStudy::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.

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 there 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

Definition at line 1150 of file RooMCStudy.cxx.

◆ plotNLL() [2/2]

RooPlot * RooMCStudy::plotNLL	(	Double_t	lo,
		Double_t	hi,
		Int_t	nBins = `100`
	)

Create a RooPlot of the -log(L) distribution in the range lo-hi with 'nBins' bins.

Definition at line 1332 of file RooMCStudy.cxx.

◆ plotParam() [1/2]

RooPlot * RooMCStudy::plotParam	(	const char *	paramName,
		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.

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 there 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

Definition at line 1094 of file RooMCStudy.cxx.

◆ plotParam() [2/2]

RooPlot * RooMCStudy::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()`
	)

Plot the distribution of the fitted value of the given parameter on a newly created frame.

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 there 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

Definition at line 1116 of file RooMCStudy.cxx.

◆ plotParamOn()

RooPlot * RooMCStudy::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.

The parameter shown is the one from which the RooPlot was created, e.g.

RooPlot* frame = param.frame(100,-10,10) ; mcstudy.paramOn(frame,LineStyle(kDashed)) ;

Any named arguments passed to plotParamOn() are forwarded to the underlying plotOn() call

Definition at line 1072 of file RooMCStudy.cxx.

◆ plotPull() [1/2]

RooPlot * RooMCStudy::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()`
	)

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.

If the parameters of the models for generation and fit differ, simple heuristics are used to find the corresponding parameters:

Parameters have the same name: They will be used to compute pulls.
Parameters have different names: The position of the fit parameter in the set of fit parameters will be computed. The parameter at the same position in the set of generator parameters will be used.

Further options:

Arguments	Effect
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 there 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 a default range. Any other named argument is passed to the RooAbsData::plotOn(). See that function for allowed options.

Definition at line 1217 of file RooMCStudy.cxx.

◆ plotPull() [2/2]

RooPlot * RooMCStudy::plotPull	(	const RooRealVar &	param,
		Double_t	lo = `-3.0`,
		Double_t	hi = `3.0`,
		Int_t	nbins = `25`,
		Bool_t	fitGauss = `kFALSE`
	)

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 ML fit of the distribution to a Gaussian p.d.f is performed. The fit result is overlaid on the returned RooPlot and a box with the fitted mean and sigma is added.

If the parameters of the models for generation and fit differ, simple heuristics are used to find the corresponding parameters:

Parameters have the same name: They will be used to compute pulls.
Parameters have different names: The position of the fit parameter in the set of fit parameters will be computed. The parameter at the same position in the set of generator parameters will be used.

Definition at line 1376 of file RooMCStudy.cxx.

◆ RecursiveRemove()

void RooMCStudy::RecursiveRemove ( TObject * obj )

protectedvirtual

If one of the TObject we have a referenced to is deleted, remove the reference.

Reimplemented from TObject.

Definition at line 1416 of file RooMCStudy.cxx.

◆ refit()

RooFitResult * RooMCStudy::refit ( RooAbsData * genSample = 0 )

protected

Redo fit on 'current' toy sample, or if genSample is not NULL do fit on given sample instead.

Definition at line 799 of file RooMCStudy.cxx.

◆ resetFitParams()

void RooMCStudy::resetFitParams ( )

protected

Reset all fit parameters to the initial model parameters at the time of the RooMCStudy constructor.

Definition at line 738 of file RooMCStudy.cxx.

◆ run()

Bool_t RooMCStudy::run	(	Bool_t	doGenerate,
		Bool_t	DoFit,
		Int_t	nSamples,
		Int_t	nEvtPerSample,
		Bool_t	keepGenData,
		const char *	asciiFilePat
	)

protected

Run engine method.

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 snprintf, 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.

Definition at line 466 of file RooMCStudy.cxx.

Friends And Related Symbol Documentation

◆ RooAbsMCStudyModule

friend class RooAbsMCStudyModule

friend

Definition at line 101 of file RooMCStudy.h.

Member Data Documentation

◆ _allDependents

RooArgSet RooMCStudy::_allDependents

protected

Definition at line 123 of file RooMCStudy.h.

◆ _binGenData

Bool_t RooMCStudy::_binGenData

protected

Definition at line 137 of file RooMCStudy.h.

◆ _canAddFitResults

Bool_t RooMCStudy::_canAddFitResults

protected

Definition at line 141 of file RooMCStudy.h.

◆ _constrGenContext

RooAbsGenContext* RooMCStudy::_constrGenContext

protected

Definition at line 120 of file RooMCStudy.h.

◆ _constrPdf

RooAbsPdf* RooMCStudy::_constrPdf

protected

Definition at line 119 of file RooMCStudy.h.

◆ _dependents

RooArgSet RooMCStudy::_dependents

protected

Definition at line 122 of file RooMCStudy.h.

◆ _extendedGen

Bool_t RooMCStudy::_extendedGen

protected

Definition at line 136 of file RooMCStudy.h.

◆ _fitInitParams

RooArgSet* RooMCStudy::_fitInitParams

protected

Definition at line 125 of file RooMCStudy.h.

◆ _fitModel

RooAbsPdf* RooMCStudy::_fitModel

protected

Definition at line 124 of file RooMCStudy.h.

◆ _fitOptions

TString RooMCStudy::_fitOptions

protected

Definition at line 134 of file RooMCStudy.h.

◆ _fitOptList

RooLinkedList RooMCStudy::_fitOptList

protected

Definition at line 135 of file RooMCStudy.h.

◆ _fitParams

RooArgSet* RooMCStudy::_fitParams

protected

Definition at line 126 of file RooMCStudy.h.

◆ _fitParData

RooDataSet* RooMCStudy::_fitParData

protected

Definition at line 133 of file RooMCStudy.h.

◆ _fitResList

TList RooMCStudy::_fitResList

protected

Definition at line 131 of file RooMCStudy.h.

◆ _genContext

RooAbsGenContext* RooMCStudy::_genContext

protected

Definition at line 113 of file RooMCStudy.h.

◆ _genDataList

TList RooMCStudy::_genDataList

protected

Definition at line 130 of file RooMCStudy.h.

◆ _genInitParams

RooArgSet* RooMCStudy::_genInitParams

protected

Definition at line 114 of file RooMCStudy.h.

◆ _genModel

RooAbsPdf* RooMCStudy::_genModel

protected

Definition at line 112 of file RooMCStudy.h.

◆ _genParams

RooArgSet* RooMCStudy::_genParams

protected

Definition at line 115 of file RooMCStudy.h.

◆ _genParData

RooDataSet* RooMCStudy::_genParData

protected

Definition at line 132 of file RooMCStudy.h.

◆ _genProtoData

const RooDataSet* RooMCStudy::_genProtoData

protected

Definition at line 116 of file RooMCStudy.h.

◆ _genSample

RooAbsData* RooMCStudy::_genSample

protected

Definition at line 111 of file RooMCStudy.h.

◆ _modList

std::list<RooAbsMCStudyModule*> RooMCStudy::_modList

protected

Definition at line 146 of file RooMCStudy.h.

◆ _nExpGen

Double_t RooMCStudy::_nExpGen

protected

Definition at line 138 of file RooMCStudy.h.

◆ _ngenVar

RooRealVar* RooMCStudy::_ngenVar

protected

Definition at line 128 of file RooMCStudy.h.

◆ _nllVar

RooRealVar* RooMCStudy::_nllVar

protected

Definition at line 127 of file RooMCStudy.h.

◆ _perExptGenParams

Bool_t RooMCStudy::_perExptGenParams

protected

Definition at line 143 of file RooMCStudy.h.

◆ _projDeps

RooArgSet RooMCStudy::_projDeps

protected

Definition at line 117 of file RooMCStudy.h.

◆ _randProto

Bool_t RooMCStudy::_randProto

protected

Definition at line 139 of file RooMCStudy.h.

◆ _silence

Bool_t RooMCStudy::_silence

protected

Definition at line 144 of file RooMCStudy.h.

◆ _verboseGen

Bool_t RooMCStudy::_verboseGen

protected

Definition at line 142 of file RooMCStudy.h.

Libraries for RooMCStudy:

[legend]

The documentation for this class was generated from the following files:

roofit/roofitcore/inc/RooMCStudy.h
roofit/roofitcore/src/RooMCStudy.cxx

Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Friends

Additional Inherited Members

Constructor & Destructor Documentation

◆ RooMCStudy() [1/3]

◆ RooMCStudy() [2/3]

◆ ~RooMCStudy()

◆ RooMCStudy() [3/3]

Member Function Documentation

◆ addFitResult()

◆ addModule()

◆ calcPulls()

◆ doFit()

◆ fit() [1/2]

◆ fit() [2/2]

◆ fitParams()

◆ fitParDataSet()

◆ fitResult()

◆ fitSample()

◆ genData()

◆ generate()

◆ generateAndFit()

◆ genParDataSet()

◆ makeFrameAndPlotCmd()

◆ plotError() [1/2]

◆ plotError() [2/2]

◆ plotNLL() [1/2]

◆ plotNLL() [2/2]

◆ plotParam() [1/2]

◆ plotParam() [2/2]

◆ plotParamOn()

◆ plotPull() [1/2]

◆ plotPull() [2/2]

◆ RecursiveRemove()

◆ refit()

◆ resetFitParams()

◆ run()

Friends And Related Symbol Documentation

◆ RooAbsMCStudyModule

Member Data Documentation

◆ _allDependents

◆ _binGenData

◆ _canAddFitResults

◆ _constrGenContext

◆ _constrPdf

◆ _dependents

◆ _extendedGen

◆ _fitInitParams

◆ _fitModel

◆ _fitOptions

◆ _fitOptList

◆ _fitParams

◆ _fitParData

◆ _fitResList

◆ _genContext

◆ _genDataList

◆ _genInitParams

◆ _genModel

◆ _genParams

◆ _genParData

◆ _genProtoData

◆ _genSample

◆ _modList

◆ _nExpGen

◆ _ngenVar

◆ _nllVar

◆ _perExptGenParams

◆ _projDeps

◆ _randProto

◆ _silence

◆ _verboseGen