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.

PyROOT

Some member functions of RooMCStudy that take a RooCmdArg as argument also support keyword arguments. So far, this applies to constructor RooMCStudy(), RooMCStudy::plotParamOn, RooMCStudy::plotParam, RooMCStudy::plotNLL, RooMCStudy::plotError and RooMCStudy::plotPull. For example, the following code is equivalent in PyROOT:

# Directly passing a RooCmdArg:
frame3 = mcstudy.plotPull(mean, ROOT.RooFit.Bins(40), ROOT.RooFit.FitGauss(True))
 
# With keyword arguments:
frame3 = mcstudy.plotPull(mean, Bins=40, FitGauss=True)

Definition at line 32 of file RooMCStudy.h.

Public Member Functions
	RooMCStudy (const RooAbsPdf &model, const RooArgSet &observables, const RooCmdArg &arg1={}, const RooCmdArg &arg2={}, const RooCmdArg &arg3={}, const RooCmdArg &arg4={}, const RooCmdArg &arg5={}, const RooCmdArg &arg6={}, const RooCmdArg &arg7={}, const RooCmdArg &arg8={})
	Construct Monte Carlo Study Manager.

	~RooMCStudy () override

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

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

bool	generateAndFit (Int_t nSamples, Int_t nEvtPerSample=0, bool keepGenData=false, const char *asciiFilePat=nullptr)
	Generate and fit 'nSamples' samples of 'nEvtPerSample' events.

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

TClass *	IsA () const override

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.

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

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.

RooPlot *	plotNLL (double lo, double 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={}, 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.

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.

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 fitted values of a parameter.

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.

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

void	Streamer (TBuffer &) override
	Stream an object of class TObject.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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.

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

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

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

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

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

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

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

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

TClass *	IsA () const override

Bool_t	IsSortable () const override

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

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

void	Print (Option_t *option="") const override
	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.

void	Streamer (TBuffer &) override
	Stream an object of class TObject.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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 with: `gROOT->SetSelectedPad(c1)`.

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=nullptr)
	Execute method on this object with the given parameter string, e.g.

virtual void	Execute (TMethod method, TObjArray params, Int_t *error=nullptr)
	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)

Bool_t	IsDestructed () const
	IsDestructed.

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 (the base implementation is no-op).

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, void vp)
	Only called by placement new when throwing an exception.

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

void	operator delete[] (void ptr, void vp)
	Only called by placement new[] when throwing an exception.

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.

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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=nullptr, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory.

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

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TNamed
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Static Public Member Functions inherited from TObject
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

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

RooFit::OwningPtr< RooFitResult >	doFit (RooAbsData *genSample)
	Internal function. Performs actual fit according to specifications.

bool	fitSample (RooAbsData *genSample)
	Internal method.

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

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

RooFit::OwningPtr< RooFitResult >	refit (RooAbsData *genSample=nullptr)
	Redo fit on 'current' toy sample, or if genSample is not nullptr 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	run (bool generate, bool fit, Int_t nSamples, Int_t nEvtPerSample, bool 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
	List of generate + prototype dependents.

bool	_binGenData

bool	_canAddFitResults
	Allow adding of external fit results?

std::unique_ptr< RooAbsGenContext >	_constrGenContext
	Generator context for constraints p.d.f.

std::unique_ptr< RooAbsPdf >	_constrPdf
	Constraints p.d.f.

RooArgSet	_dependents
	List of dependents.

bool	_extendedGen

RooArgSet	_fitInitParams
	List of initial values of fit parameters.

RooAbsPdf *	_fitModel
	Fit model.

RooLinkedList	_fitOptList

RooArgSet	_fitParams
	List of actual fit parameters.

std::unique_ptr< RooDataSet >	_fitParData

TList	_fitResList

std::unique_ptr< RooAbsGenContext >	_genContext
	Generator context.

TList	_genDataList

RooArgSet	_genInitParams
	List of original generator parameters.

RooAbsPdf *	_genModel
	Generator model.

RooArgSet	_genParams
	List of actual generator parameters.

std::unique_ptr< RooDataSet >	_genParData

const RooDataSet *	_genProtoData
	Generator prototype data set.

RooAbsData *	_genSample
	Currently generated sample.

std::list< RooAbsMCStudyModule * >	_modList
	List of additional study modules ;.

double	_nExpGen

std::unique_ptr< RooRealVar >	_ngenVar

std::unique_ptr< RooRealVar >	_nllVar

bool	_perExptGenParams = false
	Do generation parameter change per event?

RooArgSet	_projDeps
	List of projected dependents in fit.

bool	_randProto

bool	_silence
	Silent running mode?

bool	_verboseGen
	Verbose generation?

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 = (1ULL << ( 0 )) , kOverwrite = (1ULL << ( 1 )) , kWriteDelete = (1ULL << ( 2 )) }

enum	EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }

enum	EStatusBits { kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) , kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 )) }

Protected Types inherited from TObject
enum	{ kOnlyPrepStep = (1ULL << ( 3 )) }

#include <RooMCStudy.h>

Inheritance diagram for RooMCStudy:

[legend]

Constructor & Destructor Documentation

◆ RooMCStudy() [1/2]

RooMCStudy::RooMCStudy	(	const RooAbsPdf &	model,
		const RooArgSet &	observables,
		const RooCmdArg &	arg1 = `{}`,
		const RooCmdArg &	arg2 = `{}`,
		const RooCmdArg &	arg3 = `{}`,
		const RooCmdArg &	arg4 = `{}`,
		const RooCmdArg &	arg5 = `{}`,
		const RooCmdArg &	arg6 = `{}`,
		const RooCmdArg &	arg7 = `{}`,
		const RooCmdArg &	arg8 = `{}`
	)

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]	arg1,arg2,arg3,arg4,arg5,arg6,arg7,arg8	Optional arguments according to 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 flag)	Bin the dataset before fitting it. Speeds up fitting of large data samples
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 flag)	Activate informational messages in event generation phase
Extended(bool 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 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 109 of file RooMCStudy.cxx.

◆ ~RooMCStudy()

RooMCStudy::~RooMCStudy ( )

override

Definition at line 294 of file RooMCStudy.cxx.

◆ RooMCStudy() [2/2]

RooMCStudy::RooMCStudy ( const RooMCStudy & )

private

Member Function Documentation

◆ addFitResult()

bool 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 704 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 306 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 738 of file RooMCStudy.cxx.

◆ Class()

static TClass * RooMCStudy::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * RooMCStudy::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t RooMCStudy::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 152 of file RooMCStudy.h.

◆ DeclFileName()

static const char * RooMCStudy::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 152 of file RooMCStudy.h.

◆ doFit()

RooFit::OwningPtr< RooFitResult > RooMCStudy::doFit ( RooAbsData * genSample )

protected

Internal function. Performs actual fit according to specifications.

Definition at line 599 of file RooMCStudy.cxx.

◆ fit() [1/2]

bool 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 553 of file RooMCStudy.cxx.

◆ fit() [2/2]

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

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

Definition at line 568 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 successful fits, thus the maximum sampleNum can be less that the number of generated samples and if so, the indices will be out of synch with genData() and fitResult()

Definition at line 823 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 803 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 841 of file RooMCStudy.cxx.

◆ fitSample()

bool 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 659 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 866 of file RooMCStudy.cxx.

◆ generate()

bool RooMCStudy::generate	(	Int_t	nSamples,
		Int_t	nEvtPerSample = `0`,
		bool	keepGenData = `false`,
		const char *	asciiFilePat = `nullptr`
	)

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 536 of file RooMCStudy.cxx.

◆ generateAndFit()

bool RooMCStudy::generateAndFit	(	Int_t	nSamples,
		Int_t	nEvtPerSample = `0`,
		bool	keepGenData = `false`,
		const char *	asciiFilePat = `nullptr`
	)

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 514 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 60 of file RooMCStudy.h.

◆ IsA()

TClass * RooMCStudy::IsA ( ) const

inlineoverridevirtual

Returns: TClass describing current object

Reimplemented from TObject.

Definition at line 152 of file RooMCStudy.h.

◆ makeFrameAndPlotCmd()

RooPlot * RooMCStudy::makeFrameAndPlotCmd	(	const RooRealVar &	param,
		RooLinkedList &	cmdList,
		bool	symRange = `false`
	)		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 1152 of file RooMCStudy.cxx.

◆ plotError() [1/2]

RooMCStudy::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.

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.

PyROOT

The RooMCStudy::plotError() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 996 of file RooMCStudy.cxx.

◆ plotError() [2/2]

RooPlot * RooMCStudy::plotError	(	const RooRealVar &	param,
		double	lo,
		double	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 1222 of file RooMCStudy.cxx.

◆ plotNLL() [1/2]

RooMCStudy::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.

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

PyROOT

The RooMCStudy::plotNLL() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 972 of file RooMCStudy.cxx.

◆ plotNLL() [2/2]

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

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

Definition at line 1208 of file RooMCStudy.cxx.

◆ plotParam() [1/2]

RooMCStudy::plotParam	(	const char *	paramName,
		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.

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

PyROOT

The RooMCStudy::plotParam() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 916 of file RooMCStudy.cxx.

◆ plotParam() [2/2]

RooMCStudy::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.

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

PyROOT

The RooMCStudy::plotParam() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

PyROOT

The RooMCStudy::plotParam() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 938 of file RooMCStudy.cxx.

◆ plotParamOn()

RooMCStudy::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 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

PyROOT

The RooMCStudy::plotParamOn() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 894 of file RooMCStudy.cxx.

◆ plotPull() [1/2]

RooMCStudy::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.

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 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.

If you want to have more control over the Gaussian fit to the pull distribution, you can also do it after the call to plotPull():

RooPlot *frame = mcstudy->plotPull(myVariable, RooFit::Bins(40), RooFit::FitGauss(false));
RooRealVar pullMean("pullMean","Mean of pull",0,-10,10) ;
RooRealVar pullSigma("pullSigma","Width of pull",1,0.1,5) ;
pullMean.setPlotLabel("pull #mu");     // optional (to get nicer plot labels if you want)
pullSigma.setPlotLabel("pull #sigma"); // optional
RooGaussian pullGauss("pullGauss","Gaussian of pull", *frame->getPlotVar(), pullMean, pullSigma);
pullGauss.fitTo(const_cast<RooDataSet&>(mcstudy->fitParDataSet()),
                RooFit::Minos(0), RooFit::PrintLevel(-1)) ;
pullGauss.plotOn(frame) ;
pullGauss.paramOn(frame, RooFit::Layout(0.65, 0.9, 0.9)); // optionally specify label position (xmin, xmax, ymax)

PyROOT

The RooMCStudy::plotError() function is pythonized with the command argument pythonization. The keywords must correspond to the CmdArg of the function.

Definition at line 1097 of file RooMCStudy.cxx.

◆ plotPull() [2/2]

RooPlot * RooMCStudy::plotPull	(	const RooRealVar &	param,
		double	lo = `-3.0`,
		double	hi = `3.0`,
		Int_t	nbins = `25`,
		bool	fitGauss = `false`
	)

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 1251 of file RooMCStudy.cxx.

◆ RecursiveRemove()

void RooMCStudy::RecursiveRemove ( TObject * obj )

overrideprotectedvirtual

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

Reimplemented from TObject.

Definition at line 1284 of file RooMCStudy.cxx.

◆ refit()

RooFit::OwningPtr< RooFitResult > RooMCStudy::refit ( RooAbsData * genSample = nullptr )

protected

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

Definition at line 632 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 589 of file RooMCStudy.cxx.

◆ run()

bool RooMCStudy::run	(	bool	doGenerate,
		bool	DoFit,
		Int_t	nSamples,
		Int_t	nEvtPerSample,
		bool	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 327 of file RooMCStudy.cxx.

◆ Streamer()

void RooMCStudy::Streamer ( TBuffer & R__b )

overridevirtual

Stream an object of class TObject.

Reimplemented from TObject.

◆ StreamerNVirtual()

void RooMCStudy::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 152 of file RooMCStudy.h.

Friends And Related Symbol Documentation

◆ RooAbsMCStudyModule

friend class RooAbsMCStudyModule

friend

Definition at line 97 of file RooMCStudy.h.

Member Data Documentation

◆ _allDependents

RooArgSet RooMCStudy::_allDependents

protected

List of generate + prototype dependents.

Definition at line 119 of file RooMCStudy.h.

◆ _binGenData

bool RooMCStudy::_binGenData

protected

Definition at line 132 of file RooMCStudy.h.

◆ _canAddFitResults

bool RooMCStudy::_canAddFitResults

protected

Allow adding of external fit results?

Definition at line 136 of file RooMCStudy.h.

◆ _constrGenContext

std::unique_ptr<RooAbsGenContext> RooMCStudy::_constrGenContext

protected

Generator context for constraints p.d.f.

Definition at line 116 of file RooMCStudy.h.

◆ _constrPdf

std::unique_ptr<RooAbsPdf> RooMCStudy::_constrPdf

protected

Constraints p.d.f.

Definition at line 115 of file RooMCStudy.h.

◆ _dependents

RooArgSet RooMCStudy::_dependents

protected

List of dependents.

Definition at line 118 of file RooMCStudy.h.

◆ _extendedGen

bool RooMCStudy::_extendedGen

protected

Definition at line 131 of file RooMCStudy.h.

◆ _fitInitParams

RooArgSet RooMCStudy::_fitInitParams

protected

List of initial values of fit parameters.

Definition at line 121 of file RooMCStudy.h.

◆ _fitModel

RooAbsPdf* RooMCStudy::_fitModel

protected

Fit model.

Definition at line 120 of file RooMCStudy.h.

◆ _fitOptList

RooLinkedList RooMCStudy::_fitOptList

protected

Definition at line 130 of file RooMCStudy.h.

◆ _fitParams

RooArgSet RooMCStudy::_fitParams

protected

List of actual fit parameters.

Definition at line 122 of file RooMCStudy.h.

◆ _fitParData

std::unique_ptr<RooDataSet> RooMCStudy::_fitParData

protected

Definition at line 129 of file RooMCStudy.h.

◆ _fitResList

TList RooMCStudy::_fitResList

protected

Definition at line 127 of file RooMCStudy.h.

◆ _genContext

std::unique_ptr<RooAbsGenContext> RooMCStudy::_genContext

protected

Generator context.

Definition at line 109 of file RooMCStudy.h.

◆ _genDataList

TList RooMCStudy::_genDataList

protected

Definition at line 126 of file RooMCStudy.h.

◆ _genInitParams

RooArgSet RooMCStudy::_genInitParams

protected

List of original generator parameters.

Definition at line 110 of file RooMCStudy.h.

◆ _genModel

RooAbsPdf* RooMCStudy::_genModel

protected

Generator model.

Definition at line 108 of file RooMCStudy.h.

◆ _genParams

RooArgSet RooMCStudy::_genParams

protected

List of actual generator parameters.

Definition at line 111 of file RooMCStudy.h.

◆ _genParData

std::unique_ptr<RooDataSet> RooMCStudy::_genParData

protected

Definition at line 128 of file RooMCStudy.h.

◆ _genProtoData

const RooDataSet* RooMCStudy::_genProtoData

protected

Generator prototype data set.

Definition at line 112 of file RooMCStudy.h.

◆ _genSample

RooAbsData* RooMCStudy::_genSample

protected

Currently generated sample.

Definition at line 107 of file RooMCStudy.h.

◆ _modList

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

protected

List of additional study modules ;.

Definition at line 141 of file RooMCStudy.h.

◆ _nExpGen

double RooMCStudy::_nExpGen

protected

Definition at line 133 of file RooMCStudy.h.

◆ _ngenVar

std::unique_ptr<RooRealVar> RooMCStudy::_ngenVar

protected

Definition at line 124 of file RooMCStudy.h.

◆ _nllVar

std::unique_ptr<RooRealVar> RooMCStudy::_nllVar

protected

Definition at line 123 of file RooMCStudy.h.

◆ _perExptGenParams

bool RooMCStudy::_perExptGenParams = false

protected

Do generation parameter change per event?

Definition at line 138 of file RooMCStudy.h.

◆ _projDeps

RooArgSet RooMCStudy::_projDeps

protected

List of projected dependents in fit.

Definition at line 113 of file RooMCStudy.h.

◆ _randProto

bool RooMCStudy::_randProto

protected

Definition at line 134 of file RooMCStudy.h.

◆ _silence

bool RooMCStudy::_silence

protected

Silent running mode?

Definition at line 139 of file RooMCStudy.h.

◆ _verboseGen

bool RooMCStudy::_verboseGen

protected

Verbose generation?

Definition at line 137 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
/home/sftnight/build/workspace/root-makedoc-v630/rootspi/rdoc/v630_TMP/pyzdoc/_roofit.pyzdoc

PyROOT

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Private Member Functions

Friends

Additional Inherited Members

Constructor & Destructor Documentation

◆ RooMCStudy() [1/2]

◆ ~RooMCStudy()

◆ RooMCStudy() [2/2]

Member Function Documentation

◆ addFitResult()

◆ addModule()

◆ calcPulls()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ DeclFileName()

◆ doFit()

◆ fit() [1/2]

◆ fit() [2/2]

◆ fitParams()

◆ fitParDataSet()

◆ fitResult()

◆ fitSample()

◆ genData()

◆ generate()

◆ generateAndFit()

◆ genParDataSet()

◆ IsA()

◆ makeFrameAndPlotCmd()

◆ plotError() [1/2]

PyROOT

◆ plotError() [2/2]

◆ plotNLL() [1/2]

PyROOT

◆ plotNLL() [2/2]

◆ plotParam() [1/2]

PyROOT

◆ plotParam() [2/2]

PyROOT

PyROOT

◆ plotParamOn()

PyROOT

◆ plotPull() [1/2]

PyROOT

◆ plotPull() [2/2]

◆ RecursiveRemove()

◆ refit()

◆ resetFitParams()

◆ run()

◆ Streamer()

◆ StreamerNVirtual()

Friends And Related Symbol Documentation

◆ RooAbsMCStudyModule

Member Data Documentation

◆ _allDependents

◆ _binGenData

◆ _canAddFitResults

◆ _constrGenContext

◆ _constrPdf

◆ _dependents

◆ _extendedGen

◆ _fitInitParams

◆ _fitModel

◆ _fitOptList

◆ _fitParams

◆ _fitParData

◆ _fitResList

◆ _genContext

◆ _genDataList

◆ _genInitParams

◆ _genModel

◆ _genParams

◆ _genParData

◆ _genProtoData

◆ _genSample

◆ _modList