RooAbsPdf is the abstract interface for all probability density functions The class provides hybrid analytical/numerical normalization for its implementations, error tracing and a MC generator interface.

A minimal implementation of a PDF class derived from RooAbsPdf should overload the evaluate() function. This functions should return PDFs value.

Normalization/Integration

Although the normalization of a PDF is an integral part of a probability density function, normalization is treated separately in RooAbsPdf. The reason is that a RooAbsPdf object is more than a PDF: it can be a building block for a more complex, composite PDF if any of its variables are functions instead of variables. In such cases the normalization of the composite may not be simply the integral over the dependents of the top level PDF as these are functions with potentially non-trivial Jacobian terms themselves. Therefore

–> No explicit attempt should be made to normalize the functions output in evaluate().**

In addition, RooAbsPdf objects do not have a static concept of what variables are parameters and what variables are dependents (which need to be integrated over for a correct PDF normalization). Instead the choice of normalization is always specified each time a normalized values is requested from the PDF via the getVal() method.

RooAbsPdf manages the entire normalization logic of each PDF with help of a RooRealIntegral object, which coordinates the integration of a given choice of normalization. By default, RooRealIntegral will perform a fully numeric integration of all dependents. However, PDFs can advertise one or more (partial) analytical integrals of their function, and these will be used by RooRealIntegral, if it determines that this is safe (i.e. no hidden Jacobian terms, multiplication with other PDFs that have one or more dependents in commen etc)

To implement analytical integrals, two functions must be implemented. First,

Int_t getAnalyticalIntegral(const RooArgSet& integSet, RooArgSet& anaIntSet)

advertises the analytical integrals that are supported. 'integSet' is the set of dependents for which integration is requested. The function should copy the subset of dependents it can analytically integrate to anaIntSet and return a unique identification code for this integration configuration. If no integration can be performed, zero should be returned. Second,

Double_t analyticalIntegral(Int_t code)

Implements the actual analytical integral(s) advertised by getAnalyticalIntegral. This functions will only be called with codes returned by getAnalyticalIntegral, except code zero.

The integration range for real each dependent to be integrated can be obtained from the dependents' proxy functions min() and max(). Never call these proxy functions for any proxy not known to be a dependent via the integration code. Doing so may be ill-defined, e.g. in case the proxy holds a function, and will trigger an assert. Integrated category dependents should always be summed over all of their states.

Direct generation of observables

Any PDF dependent can be generated with the accept/reject method, but for certain PDFs more efficient methods may be implemented. To implement direct generation of one or more observables, two functions need to be implemented, similar to those for analytical integrals:

Int_t getGenerator(const RooArgSet& generateVars, RooArgSet& directVars) and void generateEvent(Int_t code)

The first function advertises observables that can be generated, similar to the way analytical integrals are advertised. The second function implements the generator for the advertised observables

The generated dependent values should be store in the proxy objects. For this the assignment operator can be used (i.e. xProxy = 3.0 ). Never call assign to any proxy not known to be a dependent via the generation code. Doing so may be ill-defined, e.g. in case the proxy holds a function, and will trigger an assert

Definition at line 41 of file RooAbsPdf.h.

Classes
class	CacheElem
	Normalization set with for above integral. More...

class	GenSpec

Public Types
enum	ExtendMode { CanNotBeExtended, CanBeExtended, MustBeExtended }

Public Types inherited from RooAbsReal
enum	ScaleType { Raw, Relative, NumEvent, RelativeExpected }

enum	ErrorLoggingMode { PrintErrors, CollectErrors, CountErrors, Ignore }

typedef std::map< const RooAbsArg *, std::pair < std::string, std::list < EvalError > > >::const_iterator	EvalErrorIter

Public Types inherited from RooAbsArg
enum	ConstOpCode { Activate =0, DeActivate =1, ConfigChange =2, ValueChange =3 }

enum	CacheMode { Always =0, NotAdvised =1, Never =2 }

enum	OperMode { Auto =0, AClean =1, ADirty =2 }

Public Types inherited from TObject
enum	EStatusBits { kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13) }

enum	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }

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

Public Types inherited from RooPrintable
enum	ContentsOption { kName =1, kClassName =2, kValue =4, kArgs =8, kExtras =16, kAddress =32, kTitle =64, kCollectionHeader =128 }

enum	StyleOption { kInline =1, kSingleLine =2, kStandard =3, kVerbose =4, kTreeStructure =5 }

Public Member Functions
	RooAbsPdf ()
	Default constructor. More...

	RooAbsPdf (const char name, const char title=0)
	Constructor with name and title only. More...

	RooAbsPdf (const char name, const char title, Double_t minVal, Double_t maxVal)
	Constructor with name, title, and plot range. More...

virtual	~RooAbsPdf ()
	Destructor. More...

RooDataSet *	generate (const RooArgSet &whatVars, Int_t nEvents, const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none())
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

RooDataSet *	generate (const RooArgSet &whatVars, 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())
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

RooDataSet *	generate (const RooArgSet &whatVars, Double_t nEvents=0, Bool_t verbose=kFALSE, Bool_t autoBinned=kTRUE, const char *binnedTag="", Bool_t expectedData=kFALSE, Bool_t extended=kFALSE) const
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

RooDataSet *	generate (const RooArgSet &whatVars, const RooDataSet &prototype, Int_t nEvents=0, Bool_t verbose=kFALSE, Bool_t randProtoOrder=kFALSE, Bool_t resampleProto=kFALSE) const
	Generate a new dataset with values of the whatVars variables sampled from our distribution. More...

GenSpec *	prepareMultiGen (const RooArgSet &whatVars, 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())
	Prepare GenSpec configuration object for efficient generation of multiple datasets from idetical specification This method does not perform any generation. More...

RooDataSet *	generate (GenSpec &) const
	Generate data according to a pre-configured specification created by RooAbsPdf::prepareMultiGen(). More...

virtual RooDataHist *	generateBinned (const RooArgSet &whatVars, Double_t nEvents, const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none())
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

virtual RooDataHist *	generateBinned (const RooArgSet &whatVars, 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())
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

virtual RooDataHist *	generateBinned (const RooArgSet &whatVars, Double_t nEvents, Bool_t expectedData=kFALSE, Bool_t extended=kFALSE) const
	Generate a new dataset containing the specified variables with events sampled from our distribution. More...

virtual RooDataSet *	generateSimGlobal (const RooArgSet &whatVars, Int_t nEvents)
	Special generator interface for generation of 'global observables' – for RooStats tools. More...

virtual RooPlot *	plotOn (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(), const RooCmdArg &arg9=RooCmdArg::none(), const RooCmdArg &arg10=RooCmdArg::none()) const
	Plot (project) PDF on specified frame. More...

virtual RooPlot *	plotOn (RooPlot *frame, RooLinkedList &cmdList) const
	Plot (project) PDF on specified frame. More...

virtual RooPlot *	paramOn (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())
	Add a box with parameter values (and errors) to the specified frame. More...

virtual RooPlot *	paramOn (RooPlot frame, const RooAbsData data, const char label="", Int_t sigDigits=2, Option_t options="NELU", Double_t xmin=0.50, Double_t xmax=0.99, Double_t ymax=0.95)
	OBSOLETE FUNCTION PROVIDED FOR BACKWARD COMPATIBILITY. More...

virtual Int_t	getGenerator (const RooArgSet &directVars, RooArgSet &generateVars, Bool_t staticInitOK=kTRUE) const
	Load generatedVars with the subset of directVars that we can generate events for, and return a code that specifies the generator algorithm we will use. More...

virtual void	initGenerator (Int_t code)
	Interface for one-time initialization to setup the generator for the specified code. More...

virtual void	generateEvent (Int_t code)
	Interface for generation of anan event using the algorithm corresponding to the specified code. More...

virtual Bool_t	isDirectGenSafe (const RooAbsArg &arg) const
	Check if given observable can be safely generated using the pdfs internal generator mechanism (if that existsP). More...

const RooNumGenConfig *	getGeneratorConfig () const
	Return the numeric MC generator configuration used for this object. More...

RooNumGenConfig *	specialGeneratorConfig () const
	Returns the specialized integrator configuration for this RooAbsReal. More...

RooNumGenConfig *	specialGeneratorConfig (Bool_t createOnTheFly)
	Returns the specialized integrator configuration for this RooAbsReal. More...

void	setGeneratorConfig ()
	Remove the specialized numeric MC generator configuration associated with this object. More...

void	setGeneratorConfig (const RooNumGenConfig &config)
	Set the given configuration as default numeric MC generator configuration for this object. More...

virtual RooFitResult *	fitTo (RooAbsData &data, 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())
	Fit PDF to given dataset. More...

virtual RooFitResult *	fitTo (RooAbsData &data, const RooLinkedList &cmdList)
	Fit PDF to given dataset. More...

virtual RooAbsReal *	createNLL (RooAbsData &data, const RooLinkedList &cmdList)
	Construct representation of -log(L) of PDFwith given dataset. More...

virtual RooAbsReal *	createNLL (RooAbsData &data, 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 representation of -log(L) of PDFwith given dataset. More...

virtual RooFitResult *	chi2FitTo (RooDataHist &data, const RooLinkedList &cmdList)
	Internal back-end function to steer chi2 fits. More...

virtual RooAbsReal *	createChi2 (RooDataHist &data, 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())
	Create a chi-2 from a histogram and this function. More...

virtual RooAbsReal *	createChi2 (RooDataSet &data, const RooLinkedList &cmdList)
	Internal back-end function to create a chi^2 from a p.d.f. and a dataset. More...

virtual RooArgSet *	getConstraints (const RooArgSet &, RooArgSet &, Bool_t) const

virtual RooArgSet *	getAllConstraints (const RooArgSet &observables, RooArgSet &constrainedParams, Bool_t stripDisconnected=kTRUE) const
	This helper function finds and collects all constraints terms of all coponent p.d.f.s and returns a RooArgSet with all those terms. More...

virtual RooAbsPdf *	createProjection (const RooArgSet &iset)
	Return a p.d.f that represent a projection of this p.d.f integrated over given observables. More...

RooAbsReal *	createCdf (const RooArgSet &iset, const RooArgSet &nset=RooArgSet())
	Create a cumulative distribution function of this p.d.f in terms of the observables listed in iset. More...

RooAbsReal *	createCdf (const RooArgSet &iset, 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())
	Create an object that represents the integral of the function over one or more observables listed in iset The actual integration calculation is only performed when the return object is evaluated. More...

RooAbsReal *	createScanCdf (const RooArgSet &iset, const RooArgSet &nset, Int_t numScanBins, Int_t intOrder)

virtual Bool_t	traceEvalHook (Double_t value) const
	WVE 08/21/01 Probably obsolete now. More...

virtual Double_t	getValV (const RooArgSet *set=0) const
	Return current value, normalizated by integrating over the observables in 'nset'. More...

virtual Double_t	getLogVal (const RooArgSet *set=0) const
	Return the log of the current value with given normalization An error message is printed if the argument of the log is negative. More...

Double_t	getNorm (const RooArgSet &nset) const

virtual Double_t	getNorm (const RooArgSet *set=0) const
	Return the integral of this PDF over all observables listed in 'nset'. More...

virtual void	resetErrorCounters (Int_t resetValue=10)
	Reset error counter to given value, limiting the number of future error messages for this pdf to 'resetValue'. More...

void	setTraceCounter (Int_t value, Bool_t allNodes=kFALSE)
	Reset trace counter to given value, limiting the number of future trace messages for this pdf to 'value'. More...

Bool_t	traceEvalPdf (Double_t value) const
	Check that passed value is positive and not 'not-a-number'. More...

Double_t	analyticalIntegralWN (Int_t code, const RooArgSet normSet, const char rangeName=0) const
	Analytical integral with normalization (see RooAbsReal::analyticalIntegralWN() for further information) More...

virtual Bool_t	selfNormalized () const

virtual ExtendMode	extendMode () const

Bool_t	canBeExtended () const

Bool_t	mustBeExtended () const

virtual Double_t	expectedEvents (const RooArgSet *nset) const
	Return expected number of events from this p.d.f for use in extended likelihood calculations. More...

virtual Double_t	expectedEvents (const RooArgSet &nset) const

virtual void	printValue (std::ostream &os) const
	Print value of p.d.f, also print normalization integral that was last used, if any. More...

virtual void	printMultiline (std::ostream &os, Int_t contents, Bool_t verbose=kFALSE, TString indent="") const
	Print multi line detailed information of this RooAbsPdf. More...

virtual Double_t	extendedTerm (Double_t observedEvents, const RooArgSet *nset=0) const
	Returned the extended likelihood term (Nexpect - Nobserved*log(NExpected) of this PDF for the given number of observed events. More...

void	setNormRange (const char *rangeName)

const char *	normRange () const

void	setNormRangeOverride (const char *rangeName)

const RooAbsReal *	getNormIntegral (const RooArgSet &nset) const

virtual const RooAbsReal *	getNormObj (const RooArgSet set, const RooArgSet iset, const TNamed *rangeName=0) const
	Return pointer to RooAbsReal object that implements calculation of integral over observables iset in range rangeName, optionally taking the integrand normalized over observables nset. More...

virtual RooAbsGenContext *	binnedGenContext (const RooArgSet &vars, Bool_t verbose=kFALSE) const
	Return a binned generator context. More...

virtual RooAbsGenContext *	genContext (const RooArgSet &vars, const RooDataSet prototype=0, const RooArgSet auxProto=0, Bool_t verbose=kFALSE) const
	Interface function to create a generator context from a p.d.f. More...

virtual RooAbsGenContext *	autoGenContext (const RooArgSet &vars, const RooDataSet prototype=0, const RooArgSet auxProto=0, Bool_t verbose=kFALSE, Bool_t autoBinned=kTRUE, const char *binnedTag="") const

Public Member Functions inherited from RooAbsReal
	RooAbsReal ()
	coverity[UNINIT_CTOR] Default constructor More...

	RooAbsReal (const char name, const char title, const char *unit="")
	Constructor with unit label. More...

	RooAbsReal (const char name, const char title, Double_t minVal, Double_t maxVal, const char *unit="")
	Constructor with plot range and unit label. More...

	RooAbsReal (const RooAbsReal &other, const char *name=0)
	coverity[UNINIT_CTOR] Copy constructor More...

virtual	~RooAbsReal ()
	Destructor. More...

Double_t	getVal (const RooArgSet *set=0) const

Double_t	getVal (const RooArgSet &set) const

Double_t	getPropagatedError (const RooFitResult &fr)
	Calculate error on self by propagated errors on parameters with correlations as given by fit result The linearly propagated error is calculated as follows T error(x) = F_a(x) * Corr(a,a') F_a'(x) More...

Bool_t	operator== (Double_t value) const
	Equality operator comparing to a Double_t. More...

virtual Bool_t	operator== (const RooAbsArg &other)
	Equality operator when comparing to another RooAbsArg. More...

virtual Bool_t	isIdentical (const RooAbsArg &other, Bool_t assumeSameType=kFALSE)

const Text_t *	getUnit () const

void	setUnit (const char *unit)

TString	getTitle (Bool_t appendUnit=kFALSE) const
	Return this variable's title string. More...

RooAbsFunc *	bindVars (const RooArgSet &vars, const RooArgSet *nset=0, Bool_t clipInvalid=kFALSE) const
	Create an interface adaptor f(vars) that binds us to the specified variables (in arbitrary order). More...

RooAbsArg *	createFundamental (const char *newname=0) const
	Create a RooRealVar fundamental object with our properties. More...

virtual Int_t	getAnalyticalIntegralWN (RooArgSet &allVars, RooArgSet &analVars, const RooArgSet normSet, const char rangeName=0) const
	Variant of getAnalyticalIntegral that is also passed the normalization set that should be applied to the integrand of which the integral is request. More...

virtual Int_t	getAnalyticalIntegral (RooArgSet &allVars, RooArgSet &analVars, const char *rangeName=0) const
	Interface function getAnalyticalIntergral advertises the analytical integrals that are supported. More...

virtual Double_t	analyticalIntegral (Int_t code, const char *rangeName=0) const
	Implements the actual analytical integral(s) advertised by getAnalyticalIntegral. More...

virtual Bool_t	forceAnalyticalInt (const RooAbsArg &) const

virtual void	forceNumInt (Bool_t flag=kTRUE)

Bool_t	getForceNumInt () const

virtual RooFitResult *	chi2FitTo (RooDataHist &data, 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())
	Perform a chi^2 fit to given histogram By default the fit is executed through the MINUIT commands MIGRAD, HESSE in succession. More...

virtual RooAbsReal *	createChi2 (RooDataHist &data, const RooLinkedList &cmdList)
	Internal back-end function to create a chi2. More...

virtual RooFitResult *	chi2FitTo (RooDataSet &xydata, 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())
	Create a chi-2 from a series of x and y value stored in a dataset. More...

virtual RooFitResult *	chi2FitTo (RooDataSet &xydata, const RooLinkedList &cmdList)
	Internal back-end function to steer chi2 fits. More...

virtual RooAbsReal *	createChi2 (RooDataSet &data, 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())
	Create a chi-2 from a series of x and y value stored in a dataset. More...

virtual RooAbsReal *	createProfile (const RooArgSet &paramsOfInterest)
	Create a RooProfileLL object that eliminates all nuisance parameters in the present function. More...

RooAbsReal *	createIntegral (const RooArgSet &iset, 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()) const
	Create an object that represents the integral of the function over one or more observables listed in iset The actual integration calculation is only performed when the return object is evaluated. More...

RooAbsReal *	createIntegral (const RooArgSet &iset, const char *rangeName) const

RooAbsReal *	createIntegral (const RooArgSet &iset, const RooArgSet &nset, const char *rangeName=0) const

RooAbsReal *	createIntegral (const RooArgSet &iset, const RooArgSet &nset, const RooNumIntConfig &cfg, const char *rangeName=0) const

RooAbsReal *	createIntegral (const RooArgSet &iset, const RooNumIntConfig &cfg, const char *rangeName=0) const

virtual RooAbsReal *	createIntegral (const RooArgSet &iset, const RooArgSet nset=0, const RooNumIntConfig cfg=0, const char *rangeName=0) const
	Create an object that represents the integral of the function over one or more observables listed in iset The actual integration calculation is only performed when the return object is evaluated. More...

void	setParameterizeIntegral (const RooArgSet &paramVars)

RooAbsReal *	createRunningIntegral (const RooArgSet &iset, const RooArgSet &nset=RooArgSet())
	Create a running integral over this function, i.e. More...

RooAbsReal *	createRunningIntegral (const RooArgSet &iset, 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())
	Create an object that represents the running integral of the function over one or more observables listed in iset, i.e. More...

RooAbsReal *	createIntRI (const RooArgSet &iset, const RooArgSet &nset=RooArgSet())
	Utility function for createRunningIntegral that construct an object implementing the standard (analytical) integration technique for calculating the running integral. More...

RooAbsReal *	createScanRI (const RooArgSet &iset, const RooArgSet &nset, Int_t numScanBins, Int_t intOrder)
	Utility function for createRunningIntegral that construct an object implementing the numeric scanning technique for calculating the running integral. More...

virtual Int_t	getMaxVal (const RooArgSet &vars) const
	Advertise capability to determine maximum value of function for given set of observables. More...

virtual Double_t	maxVal (Int_t code) const
	Return maximum value for set of observables identified by code assigned in getMaxVal. More...

virtual Int_t	minTrialSamples (const RooArgSet &) const

void	setPlotLabel (const char *label)
	Set the label associated with this variable. More...

const char *	getPlotLabel () const
	Get the label associated with the variable. More...

virtual Double_t	defaultErrorLevel () const

const RooNumIntConfig *	getIntegratorConfig () const
	Return the numeric integration configuration used for this object. More...

RooNumIntConfig *	getIntegratorConfig ()
	Return the numeric integration configuration used for this object. More...

RooNumIntConfig *	specialIntegratorConfig () const
	Returns the specialized integrator configuration for this RooAbsReal. More...

RooNumIntConfig *	specialIntegratorConfig (Bool_t createOnTheFly)
	Returns the specialized integrator configuration for this RooAbsReal. More...

void	setIntegratorConfig ()
	Remove the specialized numeric integration configuration associated with this object. More...

void	setIntegratorConfig (const RooNumIntConfig &config)
	Set the given integrator configuration as default numeric integration configuration for this object. More...

virtual void	fixAddCoefNormalization (const RooArgSet &addNormSet=RooArgSet(), Bool_t force=kTRUE)
	Fix the interpretation of the coefficient of any RooAddPdf component in the expression tree headed by this object to the given set of observables. More...

virtual void	fixAddCoefRange (const char *rangeName=0, Bool_t force=kTRUE)
	Fix the interpretation of the coefficient of any RooAddPdf component in the expression tree headed by this object to the given set of observables. More...

virtual void	preferredObservableScanOrder (const RooArgSet &obs, RooArgSet &orderedObs) const
	Interface method for function objects to indicate their prefferred order of observables for scanning their values into a (multi-dimensional) histogram or RooDataSet. More...

virtual RooPlot *	plotSliceOn (RooPlot frame, const RooArgSet &sliceSet, Option_t drawOptions="L", Double_t scaleFactor=1.0, ScaleType stype=Relative, const RooAbsData *projData=0) const
	OBSOLETE – RETAINED FOR BACKWARD COMPATIBILITY. Use the plotOn(frame,Slice(...)) instead. More...

TH1 *	fillHistogram (TH1 hist, const RooArgList &plotVars, Double_t scaleFactor=1, const RooArgSet projectedVars=0, Bool_t scaling=kTRUE, const RooArgSet *condObs=0, Bool_t setError=kTRUE) const
	Fill the ROOT histogram 'hist' with values sampled from this function at the bin centers. More...

TH1 *	createHistogram (const char *varNameList, Int_t xbins=0, Int_t ybins=0, Int_t zbins=0) const
	Create and fill a ROOT histogram TH1,TH2 or TH3 with the values of this function for the variables with given names The number of bins can be controlled using the [xyz]bins parameters. More...

TH1 *	createHistogram (const char *name, const RooAbsRealLValue &xvar, RooLinkedList &argList) const
	Internal method implementing createHistogram. More...

TH1 *	createHistogram (const char *name, const RooAbsRealLValue &xvar, 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()) const
	Create and fill a ROOT histogram TH1,TH2 or TH3 with the values of this function. More...

RooDataHist *	fillDataHist (RooDataHist hist, const RooArgSet nset, Double_t scaleFactor, Bool_t correctForBinVolume=kFALSE, Bool_t showProgress=kFALSE) const
	Fill a RooDataHist with values sampled from this function at the bin centers. More...

virtual Bool_t	readFromStream (std::istream &is, Bool_t compact, Bool_t verbose=kFALSE)
	Read object contents from stream (dummy for now) More...

virtual void	writeToStream (std::ostream &os, Bool_t compact) const
	Write object contents to stream (dummy for now) More...

void	logEvalError (const char message, const char serverValueString=0) const
	Log evaluation error message. More...

virtual Bool_t	isBinnedDistribution (const RooArgSet &) const

virtual std::list< Double_t > *	binBoundaries (RooAbsRealLValue &, Double_t, Double_t) const

virtual std::list< Double_t > *	plotSamplingHint (RooAbsRealLValue &, Double_t, Double_t) const

RooGenFunction *	iGenFunction (RooRealVar &x, const RooArgSet &nset=RooArgSet())

RooMultiGenFunction *	iGenFunction (const RooArgSet &observables, const RooArgSet &nset=RooArgSet())

RooFunctor *	functor (const RooArgList &obs, const RooArgList &pars=RooArgList(), const RooArgSet &nset=RooArgSet()) const
	Return a RooFunctor object bound to this RooAbsReal with given definition of observables and parameters. More...

TF1 *	asTF (const RooArgList &obs, const RooArgList &pars=RooArgList(), const RooArgSet &nset=RooArgSet()) const
	Return a ROOT TF1,2,3 object bound to this RooAbsReal with given definition of observables and parameters. More...

RooDerivative *	derivative (RooRealVar &obs, Int_t order=1, Double_t eps=0.001)
	Return function representing first, second or third order derivative of this function. More...

RooDerivative *	derivative (RooRealVar &obs, const RooArgSet &normSet, Int_t order, Double_t eps=0.001)
	Return function representing first, second or third order derivative of this function. More...

RooAbsMoment *	moment (RooRealVar &obs, Int_t order, Bool_t central, Bool_t takeRoot)
	Return function representing moment of function of given order. More...

RooAbsMoment *	moment (RooRealVar &obs, const RooArgSet &normObs, Int_t order, Bool_t central, Bool_t takeRoot, Bool_t intNormObs)
	Return function representing moment of p.d.f (normalized w.r.t given observables) of given order. More...

RooAbsMoment *	mean (RooRealVar &obs)

RooAbsMoment *	mean (RooRealVar &obs, const RooArgSet &nset)

RooAbsMoment *	sigma (RooRealVar &obs)

RooAbsMoment *	sigma (RooRealVar &obs, const RooArgSet &nset)

Double_t	findRoot (RooRealVar &x, Double_t xmin, Double_t xmax, Double_t yval)
	Return value of x (in range xmin,xmax) at which function equals yval. More...

virtual Bool_t	setData (RooAbsData &, Bool_t=kTRUE)

virtual void	enableOffsetting (Bool_t)

virtual Bool_t	isOffsetting () const

virtual Double_t	offset () const

const RooAbsReal *	createPlotProjection (const RooArgSet &depVars, const RooArgSet &projVars) const
	Utility function for plotOn() that creates a projection of a function or p.d.f to be plotted on a RooPlot. More...

const RooAbsReal *	createPlotProjection (const RooArgSet &depVars, const RooArgSet &projVars, RooArgSet *&cloneSet) const
	Utility function for plotOn() that creates a projection of a function or p.d.f to be plotted on a RooPlot. More...

const RooAbsReal *	createPlotProjection (const RooArgSet &dependentVars, const RooArgSet projectedVars, RooArgSet &cloneSet, const char rangeName=0, const RooArgSet condObs=0) const
	Utility function for plotOn() that creates a projection of a function or p.d.f to be plotted on a RooPlot. More...

Public Member Functions inherited from RooAbsArg
	RooAbsArg ()
	Default constructor. More...

virtual	~RooAbsArg ()
	Destructor. More...

	RooAbsArg (const char name, const char title)
	Create an object with the specified name and descriptive title. More...

	RooAbsArg (const RooAbsArg &other, const char *name=0)
	Copy constructor transfers all boolean and string properties of the original object. More...

virtual TObject *	clone (const char *newname=0) const =0

virtual TObject *	Clone (const char *newname=0) const
	Make a clone of an object using the Streamer facility. More...

virtual RooAbsArg *	cloneTree (const char *newname=0) const
	Clone tree expression of objects. More...

virtual Bool_t	isDerived () const

Bool_t	isCloneOf (const RooAbsArg &other) const
	Check if this object was created as a clone of 'other'. More...

Bool_t	dependsOnValue (const RooAbsCollection &serverList, const RooAbsArg *ignoreArg=0) const

Bool_t	dependsOnValue (const RooAbsArg &server, const RooAbsArg *ignoreArg=0) const

Bool_t	dependsOn (const RooAbsCollection &serverList, const RooAbsArg *ignoreArg=0, Bool_t valueOnly=kFALSE) const
	Test whether we depend on (ie, are served by) any object in the specified collection. More...

Bool_t	dependsOn (const RooAbsArg &server, const RooAbsArg *ignoreArg=0, Bool_t valueOnly=kFALSE) const
	Test whether we depend on (ie, are served by) the specified object. More...

Bool_t	overlaps (const RooAbsArg &testArg, Bool_t valueOnly=kFALSE) const
	Test if any of the nodes of tree are shared with that of the given tree. More...

Bool_t	hasClients () const

TIterator *	clientIterator () const

TIterator *	valueClientIterator () const

TIterator *	shapeClientIterator () const

TIterator *	serverIterator () const

RooFIter	valueClientMIterator () const

RooFIter	shapeClientMIterator () const

RooFIter	serverMIterator () const

RooAbsArg *	findServer (const char *name) const

RooAbsArg *	findServer (const RooAbsArg &arg) const

RooAbsArg *	findServer (Int_t index) const

Bool_t	isValueServer (const RooAbsArg &arg) const

Bool_t	isValueServer (const char *name) const

Bool_t	isShapeServer (const RooAbsArg &arg) const

Bool_t	isShapeServer (const char *name) const

void	leafNodeServerList (RooAbsCollection list, const RooAbsArg arg=0, Bool_t recurseNonDerived=kFALSE) const
	Fill supplied list with all leaf nodes of the arg tree, starting with ourself as top node. More...

void	branchNodeServerList (RooAbsCollection list, const RooAbsArg arg=0, Bool_t recurseNonDerived=kFALSE) const
	Fill supplied list with all branch nodes of the arg tree starting with ourself as top node. More...

void	treeNodeServerList (RooAbsCollection list, const RooAbsArg arg=0, Bool_t doBranch=kTRUE, Bool_t doLeaf=kTRUE, Bool_t valueOnly=kFALSE, Bool_t recurseNonDerived=kFALSE) const
	Fill supplied list with nodes of the arg tree, following all server links, starting with ourself as top node. More...

virtual Bool_t	isFundamental () const

virtual Bool_t	isLValue () const

void	addParameters (RooArgSet &params, const RooArgSet *nset=0, Bool_t stripDisconnected=kTRUE) const
	INTERNAL helper function for getParameters() More...

RooArgSet *	getVariables (Bool_t stripDisconnected=kTRUE) const
	Return RooArgSet with all variables (tree leaf nodes of expresssion tree) More...

RooArgSet *	getParameters (const RooAbsData *data, Bool_t stripDisconnected=kTRUE) const
	Create a list of leaf nodes in the arg tree starting with ourself as top node that don't match any of the names of the variable list of the supplied data set (the dependents). More...

RooArgSet *	getParameters (const RooAbsData &data, Bool_t stripDisconnected=kTRUE) const

RooArgSet *	getParameters (const RooArgSet &set, Bool_t stripDisconnected=kTRUE) const

virtual RooArgSet *	getParameters (const RooArgSet *depList, Bool_t stripDisconnected=kTRUE) const
	Create a list of leaf nodes in the arg tree starting with ourself as top node that don't match any of the names the args in the supplied argset. More...

RooArgSet *	getObservables (const RooArgSet &set, Bool_t valueOnly=kTRUE) const

RooArgSet *	getObservables (const RooAbsData *data) const
	Create a list of leaf nodes in the arg tree starting with ourself as top node that match any of the names of the variable list of the supplied data set (the dependents). More...

RooArgSet *	getObservables (const RooAbsData &data) const

RooArgSet *	getObservables (const RooArgSet *depList, Bool_t valueOnly=kTRUE) const
	Create a list of leaf nodes in the arg tree starting with ourself as top node that match any of the names the args in the supplied argset. More...

Bool_t	observableOverlaps (const RooAbsData *dset, const RooAbsArg &testArg) const
	Test if any of the dependents of the arg tree (as determined by getObservables) overlaps with those of the testArg. More...

Bool_t	observableOverlaps (const RooArgSet *depList, const RooAbsArg &testArg) const
	Test if any of the dependents of the arg tree (as determined by getObservables) overlaps with those of the testArg. More...

virtual Bool_t	checkObservables (const RooArgSet *nset) const
	Overloadable function in which derived classes can implement consistency checks of the variables. More...

Bool_t	recursiveCheckObservables (const RooArgSet *nset) const
	Recursively call checkObservables on all nodes in the expression tree. More...

RooArgSet *	getComponents () const

RooArgSet *	getDependents (const RooArgSet &set) const

RooArgSet *	getDependents (const RooAbsData *set) const

RooArgSet *	getDependents (const RooArgSet *depList) const

Bool_t	dependentOverlaps (const RooAbsData *dset, const RooAbsArg &testArg) const

Bool_t	dependentOverlaps (const RooArgSet *depList, const RooAbsArg &testArg) const

Bool_t	checkDependents (const RooArgSet *nset) const

Bool_t	recursiveCheckDependents (const RooArgSet *nset) const

void	attachDataSet (const RooAbsData &set)
	Replace server nodes with names matching the dataset variable names with those data set variables, making this PDF directly dependent on the dataset. More...

void	attachDataStore (const RooAbsDataStore &set)
	Replace server nodes with names matching the dataset variable names with those data set variables, making this PDF directly dependent on the dataset. More...

virtual void	Print (Option_t *options=0) const
	Print TNamed name and title. More...

virtual void	printName (std::ostream &os) const
	Print object name. More...

virtual void	printTitle (std::ostream &os) const
	Print object title. More...

virtual void	printClassName (std::ostream &os) const
	Print object class name. More...

virtual void	printAddress (std::ostream &os) const
	Print class name of object. More...

virtual void	printArgs (std::ostream &os) const
	Print object arguments, ie its proxies. More...

virtual void	printMetaArgs (std::ostream &) const

virtual void	printTree (std::ostream &os, TString indent="") const
	Print object tree structure. More...

virtual Int_t	defaultPrintContents (Option_t *opt) const
	Define default contents to print. More...

void	setAttribute (const Text_t *name, Bool_t value=kTRUE)
	Set (default) or clear a named boolean attribute of this object. More...

Bool_t	getAttribute (const Text_t *name) const
	Check if a named attribute is set. By default, all attributes are unset. More...

const std::set< std::string > &	attributes () const

void	setStringAttribute (const Text_t key, const Text_t value)
	Associate string 'value' to this object under key 'key'. More...

const Text_t *	getStringAttribute (const Text_t *key) const
	Get string attribute mapped under key 'key'. More...

const std::map< std::string, std::string > &	stringAttributes () const

void	setTransientAttribute (const Text_t *name, Bool_t value=kTRUE)
	Set (default) or clear a named boolean attribute of this object. More...

Bool_t	getTransientAttribute (const Text_t *name) const
	Check if a named attribute is set. More...

const std::set< std::string > &	transientAttributes () const

Bool_t	isConstant () const

RooLinkedList	getCloningAncestors () const
	Return ancestors in cloning chain of this RooAbsArg. More...

Int_t	Compare (const TObject *other) const
	Utility function used by TCollection::Sort to compare contained TObjects We implement comparison by name, resulting in alphabetical sorting by object name. More...

virtual Bool_t	IsSortable () const

void	printDirty (Bool_t depth=kTRUE) const
	Print information about current value dirty state information. More...

virtual Bool_t	inRange (const char *) const

virtual Bool_t	hasRange (const char *) const

virtual void	optimizeCacheMode (const RooArgSet &observables)
	Activate cache mode optimization with given definition of observables. More...

virtual void	optimizeCacheMode (const RooArgSet &observables, RooArgSet &optNodes, RooLinkedList &processedNodes)
	Activate cache mode optimization with given definition of observables. More...

Bool_t	findConstantNodes (const RooArgSet &observables, RooArgSet &cacheList)
	Find branch nodes with all-constant parameters, and add them to the list of nodes that can be cached with a dataset in a test statistic calculation. More...

Bool_t	findConstantNodes (const RooArgSet &observables, RooArgSet &cacheList, RooLinkedList &processedNodes)
	Find branch nodes with all-constant parameters, and add them to the list of nodes that can be cached with a dataset in a test statistic calculation. More...

virtual void	constOptimizeTestStatistic (ConstOpCode opcode, Bool_t doAlsoTrackingOpt=kTRUE)
	Interface function signaling a request to perform constant term optimization. More...

virtual CacheMode	canNodeBeCached () const

virtual void	setCacheAndTrackHints (RooArgSet &)

void	graphVizTree (const char fileName, const char delimiter="\n", bool useTitle=false, bool useLatex=false)
	Create a GraphViz .dot file visualizing the expression tree headed by this RooAbsArg object. More...

void	graphVizTree (std::ostream &os, const char *delimiter="\n", bool useTitle=false, bool useLatex=false)
	Write the GraphViz representation of the expression tree headed by this RooAbsArg object to the given ostream. More...

void	printComponentTree (const char indent="", const char namePat=0, Int_t nLevel=999)
	Print tree structure of expression tree on given ostream, only branch nodes are printed. More...

void	printCompactTree (const char indent="", const char fileName=0, const char namePat=0, RooAbsArg client=0)
	Print tree structure of expression tree on stdout, or to file if filename is specified. More...

void	printCompactTree (std::ostream &os, const char indent="", const char namePat=0, RooAbsArg *client=0)
	Print tree structure of expression tree on given ostream. More...

virtual void	printCompactTreeHook (std::ostream &os, const char *ind="")
	Hook function interface for object to insert additional information when printed in the context of a tree structure. More...

Bool_t	isShapeDirty () const

Bool_t	isValueDirty () const

Bool_t	isValueDirtyAndClear () const

Bool_t	isValueOrShapeDirtyAndClear () const

void	registerCache (RooAbsCache &cache)
	Register RooAbsCache with this object. More...

void	unRegisterCache (RooAbsCache &cache)
	Unregister a RooAbsCache. Called from the RooAbsCache destructor. More...

Int_t	numCaches () const
	Return number of registered caches. More...

RooAbsCache *	getCache (Int_t index) const
	Return registered cache object by index. More...

OperMode	operMode () const

void	setOperMode (OperMode mode, Bool_t recurseADirty=kTRUE)
	Change cache operation mode to given mode. More...

Bool_t	addOwnedComponents (const RooArgSet &comps)
	Take ownership of the contents of 'comps'. More...

const RooArgSet *	ownedComponents () const

void	setProhibitServerRedirect (Bool_t flag)

void	setValueDirty () const

void	setShapeDirty () const

void	clearValueAndShapeDirty () const

void	clearValueDirty () const

void	clearShapeDirty () const

const char *	aggregateCacheUniqueSuffix () const

virtual const char *	cacheUniqueSuffix () const

void	wireAllCaches ()

const TNamed *	namePtr () const

void	SetName (const char *name)
	Change (i.e. More...

void	SetNameTitle (const char name, const char title)
	Change (i.e. set) all the TNamed parameters (name and title). More...

Bool_t	redirectServers (const RooAbsCollection &newServerList, Bool_t mustReplaceAll=kFALSE, Bool_t nameChange=kFALSE, Bool_t isRecursionStep=kFALSE)
	Iterator over _clientListValue. More...

Bool_t	recursiveRedirectServers (const RooAbsCollection &newServerList, Bool_t mustReplaceAll=kFALSE, Bool_t nameChange=kFALSE, Bool_t recurseInNewSet=kTRUE)

virtual void	serverNameChangeHook (const RooAbsArg , const RooAbsArg )

void	addServer (RooAbsArg &server, Bool_t valueProp=kTRUE, Bool_t shapeProp=kFALSE)
	Register another RooAbsArg as a server to us, ie, declare that we depend on it. More...

void	addServerList (RooAbsCollection &serverList, Bool_t valueProp=kTRUE, Bool_t shapeProp=kFALSE)
	Register a list of RooAbsArg as servers to us by calls addServer() for each arg in the list. More...

void	replaceServer (RooAbsArg &oldServer, RooAbsArg &newServer, Bool_t valueProp, Bool_t shapeProp)
	Replace 'oldServer' with 'newServer'. More...

void	changeServer (RooAbsArg &server, Bool_t valueProp, Bool_t shapeProp)
	Change dirty flag propagation mask for specified server. More...

void	removeServer (RooAbsArg &server, Bool_t force=kFALSE)
	Unregister another RooAbsArg as a server to us, ie, declare that we no longer depend on its value and shape. More...

RooAbsArg *	findNewServer (const RooAbsCollection &newSet, Bool_t nameChange) const
	Find the new server in the specified set that matches the old server. More...

RooExpensiveObjectCache &	expensiveObjectCache () const

virtual void	setExpensiveObjectCache (RooExpensiveObjectCache &cache)

virtual Bool_t	importWorkspaceHook (RooWorkspace &)

void	setLocalNoDirtyInhibit (Bool_t flag) const

Bool_t	localNoDirtyInhibit () const

virtual void	ioStreamerPass2 ()
	Prevent 'AlwaysDirty' mode for this node. More...

Public Member Functions inherited from TNamed
	TNamed ()

	TNamed (const char name, const char title)

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

	TNamed (const TNamed &named)

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

virtual	~TNamed ()

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

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

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

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

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

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

virtual void	SetTitle (const char *title="")
	Change (i.e. set) the title of the TNamed. More...

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

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

Public Member Functions inherited from TObject
	TObject ()

	TObject (const TObject &object)
	TObject copy ctor. More...

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

virtual	~TObject ()
	TObject destructor. More...

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

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

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

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

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

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

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

virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current pad. More...

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

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. More...

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

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

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

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

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

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

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

virtual Option_t *	GetOption () const

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

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

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

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

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

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

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

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

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

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

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

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

virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list. More...

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

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

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

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

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

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

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

void *	operator new (size_t sz)

void *	operator new[] (size_t sz)

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

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

void	operator delete (void *ptr)
	Operator delete. More...

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

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

void	SetBit (UInt_t f)

void	ResetBit (UInt_t f)

Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

void	InvertBit (UInt_t f)

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

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

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

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

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

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

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). More...

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

Public Member Functions inherited from RooPrintable
	RooPrintable ()

virtual	~RooPrintable ()

virtual void	printStream (std::ostream &os, Int_t contents, StyleOption style, TString indent="") const
	Print description of object on ostream, printing contents set by contents integer, which is interpreted as an OR of 'enum ContentsOptions' values and in the style given by 'enum StyleOption'. More...

virtual void	printExtras (std::ostream &os) const
	Interface to print extras of object. More...

virtual StyleOption	defaultPrintStyle (Option_t *opt) const

Static Public Member Functions
static RooNumGenConfig *	defaultGeneratorConfig ()
	Returns the default numeric MC generator configuration for all RooAbsReals. More...

static void	verboseEval (Int_t stat)
	Change global level of verbosity for p.d.f. evaluations. More...

static int	verboseEval ()
	Return global level of verbosity for p.d.f. evaluations. More...

static void	clearEvalError ()
	Clear the evaluation error flag. More...

static Bool_t	evalError ()
	Return the evaluation error flag. More...

Static Public Member Functions inherited from RooAbsReal
static RooNumIntConfig *	defaultIntegratorConfig ()
	Returns the default numeric integration configuration for all RooAbsReals. More...

static void	setCacheCheck (Bool_t flag)
	Activate cache validation mode. More...

static ErrorLoggingMode	evalErrorLoggingMode ()
	Return current evaluation error logging mode. More...

static void	setEvalErrorLoggingMode (ErrorLoggingMode m)
	Set evaluation error logging mode. More...

static void	logEvalError (const RooAbsReal originator, const char origName, const char message, const char serverValueString=0)
	Interface to insert remote error logging messages received by RooRealMPFE into current error loggin stream. More...

static void	printEvalErrors (std::ostream &os=std::cout, Int_t maxPerNode=10000000)
	Print all outstanding logged evaluation error on the given ostream. More...

static Int_t	numEvalErrors ()
	Return the number of logged evaluation errors since the last clearing. More...

static Int_t	numEvalErrorItems ()

static EvalErrorIter	evalErrorIter ()

static void	clearEvalErrorLog ()
	Clear the stack of evaluation error messages. More...

static void	setHideOffset (Bool_t flag)

static Bool_t	hideOffset ()

Static Public Member Functions inherited from RooAbsArg
static void	verboseDirty (Bool_t flag)
	Activate verbose messaging related to dirty flag propagation. More...

static void	setDirtyInhibit (Bool_t flag)
	Control global dirty inhibit mode. More...

static UInt_t	crc32 (const char *data)

static UInt_t	crc32 (const char *data, ULong_t sz, UInt_t crc=0)

static UInt_t	fnv1a32 (const char *data)

static UInt_t	fnv1a32 (const char *data, ULong_t sz, UInt_t hash=fnv1a32start)

static ULong64_t	fnv1a64 (const char *data)

static ULong64_t	fnv1a64 (const char *data, ULong_t sz, ULong64_t hash=fnv1a64start)

static void	ioStreamerPass2Finalize ()
	Method called by workspace container to finalize schema evolution issues that cannot be handled in a single ioStreamer pass. More...

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

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

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

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

Static Public Member Functions inherited from RooPrintable
static std::ostream &	defaultPrintStream (std::ostream *os=0)
	Return a reference to the current default stream to use in Print(). More...

static void	nameFieldLength (Int_t newLen)
	Set length of field reserved from printing name of RooAbsArgs in multi-line collection printing to given amount. More...

Protected Member Functions
RooDataSet *	generate (RooAbsGenContext &context, const RooArgSet &whatVars, const RooDataSet *prototype, Double_t nEvents, Bool_t verbose, Bool_t randProtoOrder, Bool_t resampleProto, Bool_t skipInit=kFALSE, Bool_t extended=kFALSE) const
	Internal method. More...

virtual RooPlot *	paramOn (RooPlot frame, const RooArgSet &params, Bool_t showConstants=kFALSE, const char label="", Int_t sigDigits=2, Option_t options="NELU", Double_t xmin=0.65, Double_t xmax=0.99, Double_t ymax=0.95, const RooCmdArg formatCmd=0)
	Add a text box with the current parameter values and their errors to the frame. More...

virtual RooPlot *	plotOn (RooPlot *frame, PlotOpt o) const

Int_t *	randomizeProtoOrder (Int_t nProto, Int_t nGen, Bool_t resample=kFALSE) const
	Return lookup table with randomized access order for prototype events, given nProto prototype data events and nGen events that will actually be accessed. More...

	RooAbsPdf (const RooAbsPdf &other, const char *name=0)
	Copy constructor. More...

virtual Bool_t	syncNormalization (const RooArgSet *dset, Bool_t adjustProxies=kTRUE) const
	Verify that the normalization integral cached with this PDF is valid for given set of normalization observables. More...

virtual Bool_t	redirectServersHook (const RooAbsCollection &, Bool_t, Bool_t, Bool_t)

Protected Member Functions inherited from RooAbsReal
virtual void	selectNormalization (const RooArgSet *depSet=0, Bool_t force=kFALSE)
	Interface function to force use of a given set of observables to interpret function value. More...

virtual void	selectNormalizationRange (const char *rangeName=0, Bool_t force=kFALSE)
	Interface function to force use of a given normalization range to interpret function value. More...

Bool_t	plotSanityChecks (RooPlot *frame) const
	Utility function for plotOn(), perform general sanity check on frame to ensure safe plotting operations. More...

void	makeProjectionSet (const RooAbsArg plotVar, const RooArgSet allVars, RooArgSet &projectedVars, Bool_t silent) const
	Utility function for plotOn() that constructs the set of observables to project when plotting ourselves as function of 'plotVar'. More...

TString	integralNameSuffix (const RooArgSet &iset, const RooArgSet nset=0, const char rangeName=0, Bool_t omitEmpty=kFALSE) const
	Construct string with unique suffix name to give to integral object that encodes integrated observables, normalization observables and the integration range name. More...

Bool_t	isSelectedComp () const
	If true, the current pdf is a selected component (for use in plotting) More...

RooFitResult *	chi2FitDriver (RooAbsReal &fcn, RooLinkedList &cmdList)
	Internal driver function for chi2 fits. More...

void	plotOnCompSelect (RooArgSet *selNodes) const
	Helper function for plotting of composite p.d.fs. More...

RooPlot *	plotOnWithErrorBand (RooPlot frame, const RooFitResult &fr, Double_t Z, const RooArgSet params, const RooLinkedList &argList, Bool_t method1) const
	Plot function or p.d.f. More...

Bool_t	matchArgs (const RooArgSet &allDeps, RooArgSet &numDeps, const RooArgProxy &a) const
	Utility function for use in getAnalyticalIntegral(). More...

Bool_t	matchArgs (const RooArgSet &allDeps, RooArgSet &numDeps, const RooArgProxy &a, const RooArgProxy &b) const
	Utility function for use in getAnalyticalIntegral(). More...

Bool_t	matchArgs (const RooArgSet &allDeps, RooArgSet &numDeps, const RooArgProxy &a, const RooArgProxy &b, const RooArgProxy &c) const
	Utility function for use in getAnalyticalIntegral(). More...

Bool_t	matchArgs (const RooArgSet &allDeps, RooArgSet &numDeps, const RooArgProxy &a, const RooArgProxy &b, const RooArgProxy &c, const RooArgProxy &d) const
	Utility function for use in getAnalyticalIntegral(). More...

Bool_t	matchArgs (const RooArgSet &allDeps, RooArgSet &numDeps, const RooArgSet &set) const
	Utility function for use in getAnalyticalIntegral(). More...

RooAbsReal *	createIntObj (const RooArgSet &iset, const RooArgSet nset, const RooNumIntConfig cfg, const char *rangeName) const
	Utility function for createIntegral that creates the actual integreal object. More...

void	findInnerMostIntegration (const RooArgSet &allObs, RooArgSet &innerObs, const char *rangeName) const
	Utility function for createIntObj() that aids in the construct of recursive integrals over functions with multiple observables with parameterized ranges. More...

virtual Bool_t	isValid () const
	Check if current value is valid. More...

virtual Bool_t	isValidReal (Double_t value, Bool_t printError=kFALSE) const
	Interface function to check if given value is a valid value for this object. More...

Double_t	traceEval (const RooArgSet *set) const
	Calculate current value of object, with error tracing wrapper. More...

virtual Double_t	evaluate () const =0

virtual void	syncCache (const RooArgSet *set=0)

virtual void	copyCache (const RooAbsArg *source, Bool_t valueOnly=kFALSE, Bool_t setValDirty=kTRUE)
	Copy the cached value of another RooAbsArg to our cache. More...

virtual void	attachToTree (TTree &t, Int_t bufSize=32000)
	Attach object to a branch of given TTree. More...

virtual void	attachToVStore (RooVectorDataStore &vstore)

virtual void	setTreeBranchStatus (TTree &t, Bool_t active)
	(De)Activate associated tree branch More...

virtual void	fillTreeBranch (TTree &t)
	Fill the tree branch that associated with this object with its current value. More...

virtual RooPlot *	plotAsymOn (RooPlot *frame, const RooAbsCategoryLValue &asymCat, PlotOpt o) const

void	selectComp (Bool_t flag)

Protected Member Functions inherited from RooAbsArg
void	graphVizAddConnections (std::set< std::pair< RooAbsArg , RooAbsArg > > &)
	Utility function that inserts all point-to-point client-server connections between any two RooAbsArgs in the expression tree headed by this object in the linkSet argument. More...

virtual void	operModeHook ()

virtual void	optimizeDirtyHook (const RooArgSet *)

virtual void	getParametersHook (const RooArgSet , RooArgSet , Bool_t) const

virtual void	getObservablesHook (const RooArgSet , RooArgSet ) const

void	registerProxy (RooArgProxy &proxy)
	Register an RooArgProxy in the proxy list. More...

void	registerProxy (RooSetProxy &proxy)
	Register an RooSetProxy in the proxy list. More...

void	registerProxy (RooListProxy &proxy)
	Register an RooListProxy in the proxy list. More...

void	unRegisterProxy (RooArgProxy &proxy)
	Remove proxy from proxy list. More...

void	unRegisterProxy (RooSetProxy &proxy)
	Remove proxy from proxy list. More...

void	unRegisterProxy (RooListProxy &proxy)
	Remove proxy from proxy list. More...

RooAbsProxy *	getProxy (Int_t index) const
	Return the nth proxy from the proxy list. More...

void	setProxyNormSet (const RooArgSet *nset)
	Forward a change in the cached normalization argset to all the registered proxies. More...

Int_t	numProxies () const
	Return the number of registered proxies. More...

void	printAttribList (std::ostream &os) const
	Transient boolean attributes (not copied in ctor) More...

void	attachToStore (RooAbsDataStore &store)

TString	cleanBranchName () const
	Construct a mangled name from the actual name that is free of any math symbols that might be interpreted by TTree. More...

Bool_t	inhibitDirty () const
	Delete watch flag. More...

void	setValueDirty (const RooAbsArg *source) const
	Mark this object as having changed its value, and propagate this status change to all of our clients. More...

void	setShapeDirty (const RooAbsArg *source) const
	Mark this object as having changed its shape, and propagate this status change to all of our clients. More...

Protected Member Functions inherited from TObject
void	MakeZombie ()

virtual void	DoError (int level, const char location, const char fmt, va_list va) const
	Interface to ErrorHandler (protected). More...

Static Protected Member Functions
static void	raiseEvalError ()
	Raise the evaluation error flag. More...

Static Protected Member Functions inherited from RooAbsReal
static void	globalSelectComp (Bool_t flag)
	Global switch controlling the activation of the selectComp() functionality. More...

Protected Attributes
Double_t	_rawValue

RooAbsReal *	_norm

RooArgSet *	_normSet
	Normalization integral (owned by _normMgr) More...

RooObjCacheManager	_normMgr

Int_t	_errorCount

Int_t	_traceCount

Int_t	_negCount

Bool_t	_selectComp

RooNumGenConfig *	_specGeneratorConfig

TString	_normRange
	MC generator configuration specific for this object. More...

Protected Attributes inherited from RooAbsReal
Double_t	_plotMin

Double_t	_plotMax

Int_t	_plotBins

Double_t	_value

TString	_unit

TString	_label

Bool_t	_forceNumInt

Float_t	_floatValue

Int_t	_intValue
	Transient cache for floating point values from tree branches. More...

Bool_t	_boolValue
	Transient cache for integer values from tree branches. More...

UChar_t	_byteValue
	Transient cache for bool values from tree branches. More...

Char_t	_sbyteValue
	Transient cache for byte values from tree branches. More...

UInt_t	_uintValue
	Transient cache for signed byte values from tree branches. More...

RooNumIntConfig *	_specIntegratorConfig

Bool_t	_treeVar

Bool_t	_selectComp

RooArgSet *	_lastNSet

Protected Attributes inherited from RooAbsArg
RooRefCountList	_serverList

RooRefCountList	_clientList

RooRefCountList	_clientListShape

RooRefCountList	_clientListValue

RooRefArray	_proxyList

std::deque< RooAbsCache * >	_cacheList

TIterator *	_clientShapeIter

TIterator *	_clientValueIter
	Iterator over _clientListShape. More...

std::set< std::string >	_boolAttrib

std::map< std::string, std::string >	_stringAttrib

std::set< std::string >	_boolAttribTransient

Bool_t	_deleteWatch

Bool_t	_valueDirty

Bool_t	_shapeDirty

OperMode	_operMode

Bool_t	_fast

RooArgSet *	_ownedComponents

Bool_t	_prohibitServerRedirect
	Set of owned component. More...

RooExpensiveObjectCache *	_eocache
	Prohibit server redirects – Debugging tool. More...

TNamed *	_namePtr

Bool_t	_isConstant
	Do not persist. Pointer to global instance of string that matches object named. More...

Bool_t	_localNoInhibitDirty
	Cached isConstant status. More...

Protected Attributes inherited from TNamed
TString	fName

TString	fTitle

Static Protected Attributes
static Int_t	_verboseEval = 0

static Bool_t	_evalError = kFALSE

static TString	_normRangeOverride

Static Protected Attributes inherited from RooAbsReal
static Bool_t	_cacheCheck

static Bool_t	_globalSelectComp = kFALSE
	Component selection flag for RooAbsPdf::plotCompOn. More...

static Bool_t	_hideOffset = kTRUE

Static Protected Attributes inherited from RooAbsArg
static Bool_t	_verboseDirty

static Bool_t	_inhibitDirty

Static Protected Attributes inherited from RooPrintable
static Int_t	_nameLength

Friends
class	RooEffGenContext

class	RooAddGenContext

class	RooProdGenContext

class	RooSimGenContext

class	RooSimSplitGenContext

class	RooConvGenContext

class	RooSimultaneous

class	RooAddGenContextOrig

class	RooProdPdf

class	RooMCStudy

class	RooExtendPdf

class	RooRealIntegral

class	RooAbsAnaConvPdf

class	CacheElem

Additional Inherited Members
Static Public Attributes inherited from RooAbsArg
static const UInt_t	fnv1a32start = 2166136261u

static const ULong64_t	fnv1a64start = (ULong64_t(3421674724u) << 32) \| ULong64_t(2216829733u)

static std::map< RooAbsArg , TRefArray >	_ioEvoList

static std::stack< RooAbsArg * >	_ioReadStack

#include <RooAbsPdf.h>

Inheritance diagram for RooAbsPdf:

[legend]

Member Enumeration Documentation

enum RooAbsPdf::ExtendMode

Enumerator
CanNotBeExtended
CanBeExtended
MustBeExtended

Definition at line 209 of file RooAbsPdf.h.

Constructor & Destructor Documentation

RooAbsPdf::RooAbsPdf ( )

Default constructor.

Definition at line 176 of file RooAbsPdf.cxx.

RooAbsPdf::RooAbsPdf	(	const char *	name,
		const char *	title = `0`
	)

Constructor with name and title only.

Definition at line 190 of file RooAbsPdf.cxx.

RooAbsPdf::RooAbsPdf	(	const char *	name,
		const char *	title,
		Double_t	minVal,
		Double_t	maxVal
	)

Constructor with name, title, and plot range.

Definition at line 202 of file RooAbsPdf.cxx.

RooAbsPdf::~RooAbsPdf ( )

virtual

Destructor.

Definition at line 234 of file RooAbsPdf.cxx.

RooAbsPdf::RooAbsPdf	(	const RooAbsPdf &	other,
		const char *	name = `0`
	)

protected

Copy constructor.

Definition at line 215 of file RooAbsPdf.cxx.

Member Function Documentation

Double_t RooAbsPdf::analyticalIntegralWN	(	Int_t	code,
		const RooArgSet *	normSet,
		const char *	rangeName = `0`
	)		const

virtual

Analytical integral with normalization (see RooAbsReal::analyticalIntegralWN() for further information)

This function applies the normalization specified by 'normSet' to the integral returned by RooAbsReal::analyticalIntegral(). The passthrough scenario (code=0) is also changed to return a normalized answer

Reimplemented from RooAbsReal.

Reimplemented in RooProdPdf, RooSimultaneous, RooAddPdf, RooAddModel, RooRealSumPdf, RooEffProd, RooExtendPdf, and RooProjectedPdf.

Definition at line 321 of file RooAbsPdf.cxx.

Referenced by RooAddPdf::analyticalIntegralWN(), and RooAbsCachedPdf::analyticalIntegralWN().

RooAbsGenContext * RooAbsPdf::autoGenContext	(	const RooArgSet &	vars,
		const RooDataSet *	prototype = `0`,
		const RooArgSet *	auxProto = `0`,
		Bool_t	verbose = `kFALSE`,
		Bool_t	autoBinned = `kTRUE`,
		const char *	binnedTag = `""`
	)		const

virtual

Reimplemented in RooSimultaneous.

Definition at line 1647 of file RooAbsPdf.cxx.

Referenced by generate(), prepareMultiGen(), and RooSimSplitGenContext::RooSimSplitGenContext().

RooAbsGenContext * RooAbsPdf::binnedGenContext	(	const RooArgSet &	vars,
		Bool_t	verbose = `kFALSE`
	)		const

virtual

Return a binned generator context.

Definition at line 1628 of file RooAbsPdf.cxx.

Referenced by autoGenContext().

Bool_t RooAbsPdf::canBeExtended ( ) const

inline

Definition at line 216 of file RooAbsPdf.h.

Referenced by ClassImp(), RooSimultaneous::evaluate(), RooStats::NumEventsTestStat::Evaluate(), RooExtendPdf::expectedEvents(), extendedTerm(), RooSimultaneous::extendMode(), RooBinnedGenContext::generate(), RooStats::AsymptoticCalculator::GenerateAsimovDataSinglePdf(), generateBinned(), RooProdPdf::initializeFromCmdArgList(), OneSidedFrequentistUpperLimitWithBands(), plotOn(), RooStats::HypoTestInverter::RebuildDistributions(), RooAbsGenContext::RooAbsGenContext(), RooAddPdf::RooAddPdf(), RooProdPdf::RooProdPdf(), RooSimGenContext::RooSimGenContext(), RooSimSplitGenContext::RooSimSplitGenContext(), RooXYChi2Var::RooXYChi2Var(), StandardFeldmanCousinsDemo(), StandardFrequentistDiscovery(), StandardHypoTestDemo(), StandardTestStatDistributionDemo(), and TwoSidedFrequentistUpperLimitWithBands().

RooFitResult * RooAbsPdf::chi2FitTo	(	RooDataHist &	data,
		const RooLinkedList &	cmdList
	)

virtual

Internal back-end function to steer chi2 fits.

Reimplemented from RooAbsReal.

Definition at line 1451 of file RooAbsPdf.cxx.

void RooAbsPdf::clearEvalError ( )

static

Clear the evaluation error flag.

Definition at line 3150 of file RooAbsPdf.cxx.

Referenced by RooMinimizerFcn::DoEval(), and RooMinuitGlue().

RooAbsReal * RooAbsPdf::createCdf	(	const RooArgSet &	iset,
		const RooArgSet &	nset = `RooArgSet()`
	)

Create a cumulative distribution function of this p.d.f in terms of the observables listed in iset.

If no nset argument is given the c.d.f normalization is constructed over the integrated observables, so that its maximum value is precisely 1. It is also possible to choose a different normalization for multi-dimensional p.d.f.s: eg. for a pdf f(x,y,z) one can construct a partial cdf c(x,y) that only when integrated itself over z results in a maximum value of 1. To construct such a cdf pass z as argument to the optional nset argument

Definition at line 3027 of file RooAbsPdf.cxx.

Referenced by ClassImp(), RooStats::BayesianCalculator::ComputeIntervalUsingRooFit(), RooFactoryWSTool::SpecialsIFace::create(), RooIntegralMorph::MorphCacheElem::MorphCacheElem(), and Zbi_Zgamma().

RooAbsReal * RooAbsPdf::createCdf	(	const RooArgSet &	iset,
		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()`
	)

Create an object that represents the integral of the function over one or more observables listed in iset The actual integration calculation is only performed when the return object is evaluated.

The name of the integral object is automatically constructed from the name of the input function, the variables it integrates and the range integrates over

The following named arguments are accepted

SupNormSet(const RooArgSet&) – Observables over which should be normalized in_addition to the integration observables ScanNumCdf() – Apply scanning technique if cdf integral involves numeric integration [ default ] ScanAllCdf() – Always apply scanning technique ScanNoCdf() – Never apply scanning technique ScanParameters(Int_t nbins, – Parameters for scanning technique of making CDF: number Int_t intOrder) of sampled bins and order of interpolation applied on numeric cdf

Definition at line 3050 of file RooAbsPdf.cxx.

RooAbsReal * RooAbsPdf::createChi2	(	RooDataHist &	data,
		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()`
	)

virtual

Create a chi-2 from a histogram and this function.

The following named arguments are supported

Options to control construction of the chi^2

Extended() – Use expected number of events of an extended p.d.f as normalization DataError() – Choose between Expected error [RooAbsData::Expected] , or Observed error (e.g. Sum-of-weights [RooAbsData:SumW2] or Poisson interval [RooAbsData::Poisson] ) Default is AUTO : Expected error for unweighted data, Sum-of-weights for weighted data NumCPU() – Activate parallel processing feature Range() – Fit only selected region SumCoefRange() – Set the range in which to interpret the coefficients of RooAddPdf components SplitRange() – Fit range is split by index catory of simultaneous PDF ConditionalObservables() – Define projected observables

Reimplemented from RooAbsReal.

Definition at line 1487 of file RooAbsPdf.cxx.

Referenced by chi2FitTo().

RooAbsReal * RooAbsPdf::createChi2	(	RooDataSet &	data,
		const RooLinkedList &	cmdList
	)

virtual

Internal back-end function to create a chi^2 from a p.d.f. and a dataset.

Reimplemented from RooAbsReal.

Definition at line 1562 of file RooAbsPdf.cxx.

RooAbsReal * RooAbsPdf::createNLL	(	RooAbsData &	data,
		const RooLinkedList &	cmdList
	)

virtual

Construct representation of -log(L) of PDFwith given dataset.

If dataset is unbinned, an unbinned likelihood is constructed. If the dataset is binned, a binned likelihood is constructed.

See RooAbsPdf::createNLL(RooAbsData& data, RooCmdArg arg1, RooCmdArg arg2, RooCmdArg arg3, RooCmdArg arg4, RooCmdArg arg5, RooCmdArg arg6, RooCmdArg arg7, RooCmdArg arg8)

for documentation of options

Reimplemented in RooStats::HistFactory::HistFactorySimultaneous.

Definition at line 777 of file RooAbsPdf.cxx.

Referenced by ClassImp(), RooStats::HistFactory::HistFactorySimultaneous::createNLL(), createNLL(), RooStats::FeldmanCousins::CreateParameterPoints(), RooStats::ProfileLikelihoodCalculator::DoGlobalFit(), RooStats::MaxLikelihoodEstimateTestStat::Evaluate(), RooStats::AsymptoticCalculator::EvaluateNLL(), RooStats::HistFactory::FitModelAndPlot(), fitTo(), RooStats::MCMCCalculator::GetInterval(), RooStats::ProfileInspector::GetListOfProfilePlots(), RooStats::BayesianCalculator::GetPosteriorFunction(), OneSidedFrequentistUpperLimitWithBands(), and TwoSidedFrequentistUpperLimitWithBands().

RooAbsReal * RooAbsPdf::createNLL	(	RooAbsData &	data,
		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()`
	)

virtual

Construct representation of -log(L) of PDFwith given dataset.

If dataset is unbinned, an unbinned likelihood is constructed. If the dataset is binned, a binned likelihood is constructed.

The following named arguments are supported

ConditionalObservables(const RooArgSet& set) – Do not normalize PDF over listed observables Extended(Bool_t flag) – Add extended likelihood term, off by default Range(const char* name) – Fit only data inside range with given name Range(Double_t lo, Double_t hi) – Fit only data inside given range. A range named "fit" is created on the fly on all observables. Multiple comma separated range names can be specified. SumCoefRange(const char* name) – Set the range in which to interpret the coefficients of RooAddPdf components NumCPU(int num, int strat) – Parallelize NLL calculation on num CPUs

                               Strategy 0 = RooFit::BulkPartition (Default) --> Divide events in N equal chunks 
                               Strategy 1 = RooFit::Interleave --> Process event i%N in process N. Recommended for binned data with 
                                            a substantial number of zero-bins, which will be distributed across processes more equitably in this strategy
                               Strategy 2 = RooFit::SimComponents --> Process each component likelihood of a RooSimultaneous fully in a single process
                                            and distribute components over processes. This approach can be benificial if normalization calculation time
                                            dominates the total computation time of a component (since the normalization calculation must be performed
                                            in each process in strategies 0 and 1. However beware that if the RooSimultaneous components do not share many
                                            parameters this strategy is inefficient: as most minuit-induced likelihood calculations involve changing
                                            a single parameter, only 1 of the N processes will be active most of the time if RooSimultaneous components
                                            do not share many parameters
                               Strategy 3 = RooFit::Hybrid --> Follow strategy 0 for all RooSimultaneous components, except those with less than
                                            30 dataset entries, for which strategy 2 is followed.

Optimize(Bool_t flag) – Activate constant term optimization (on by default) SplitRange(Bool_t flag) – Use separate fit ranges in a simultaneous fit. Actual range name for each subsample is assumed to by rangeName_{indexState} where indexState is the state of the master index category of the simultaneous fit Constrain(const RooArgSet&pars) – For p.d.f.s that contain internal parameter constraint terms, only apply constraints to given subset of parameters ExternalConstraints(const RooArgSet& ) – Include given external constraints to likelihood GlobalObservables(const RooArgSet&) – Define the set of normalization observables to be used for the constraint terms. If none are specified the constrained parameters are used GlobalObservablesTag(const char* tagName) – Define the set of normalization observables to be used for the constraint terms by a string attribute associated with pdf observables that match the given tagName Verbose(Bool_t flag) – Constrols RooFit informational messages in likelihood construction CloneData(Bool flag) – Use clone of dataset in NLL (default is true) Offset(Bool_t) – Offset likelihood by initial value (so that starting value of FCN in minuit is zero). This can improve numeric stability in simultaneously fits with components with large likelihood values

Reimplemented in RooStats::HistFactory::HistFactorySimultaneous.

Definition at line 754 of file RooAbsPdf.cxx.

RooAbsPdf * RooAbsPdf::createProjection ( const RooArgSet & iset )

virtual

Return a p.d.f that represent a projection of this p.d.f integrated over given observables.

Reimplemented in RooProjectedPdf.

Definition at line 2989 of file RooAbsPdf.cxx.

Referenced by RooFactoryWSTool::SpecialsIFace::create(), RooProjectedPdf::createProjection(), and rs401d_FeldmanCousins().

RooAbsReal * RooAbsPdf::createScanCdf	(	const RooArgSet &	iset,
		const RooArgSet &	nset,
		Int_t	numScanBins,
		Int_t	intOrder
	)

Definition at line 3106 of file RooAbsPdf.cxx.

Referenced by createCdf().

RooNumGenConfig * RooAbsPdf::defaultGeneratorConfig ( )

static

Returns the default numeric MC generator configuration for all RooAbsReals.

Definition at line 3180 of file RooAbsPdf.cxx.

Referenced by getGeneratorConfig(), and specialGeneratorConfig().

Bool_t RooAbsPdf::evalError ( )

static

Return the evaluation error flag.

Definition at line 3160 of file RooAbsPdf.cxx.

Referenced by RooMinimizerFcn::DoEval(), and RooMinuitGlue().

Double_t RooAbsPdf::expectedEvents ( const RooArgSet * nset ) const

virtual

Return expected number of events from this p.d.f for use in extended likelihood calculations.

This default implementation returns zero

Reimplemented in RooProdPdf, RooAddPdf, RooAddModel, RooSimultaneous, RooRealSumPdf, RooExtendPdf, and RooExtendedTerm.

Definition at line 2930 of file RooAbsPdf.cxx.

Referenced by ClassImp(), RooAbsReal::createHistogram(), RooStats::HistFactory::RooBarlowBeestonLL::evaluate(), RooNLLVar::evaluatePartition(), RooExtendPdf::expectedEvents(), RooAddModel::expectedEvents(), RooAddPdf::expectedEvents(), expectedEvents(), extendedTerm(), RooStats::AsymptoticCalculator::FillBins(), RooXYChi2Var::fy(), RooBinnedGenContext::generate(), RooSimSplitGenContext::generate(), generate(), generateBinned(), plotOn(), RooAbsGenContext::RooAbsGenContext(), RooMCStudy::RooMCStudy(), RooSimGenContext::RooSimGenContext(), RooSimSplitGenContext::RooSimSplitGenContext(), RooMCStudy::run(), StandardHistFactoryPlotsWithCategories(), RooAddPdf::updateCoefficients(), and RooSimGenContext::updateFractions().

virtual Double_t RooAbsPdf::expectedEvents ( const RooArgSet & nset ) const

inlinevirtual

Reimplemented in RooProdPdf, RooAddPdf, RooAddModel, RooSimultaneous, RooRealSumPdf, RooExtendPdf, and RooExtendedTerm.

Definition at line 225 of file RooAbsPdf.h.

Double_t RooAbsPdf::extendedTerm	(	Double_t	observed,
		const RooArgSet *	nset = `0`
	)		const

virtual

Returned the extended likelihood term (Nexpect - Nobserved*log(NExpected) of this PDF for the given number of observed events.

For successfull operation the PDF implementation must indicate it is extendable by overloading canBeExtended() and must implemented the expectedEvents() function.

Definition at line 646 of file RooAbsPdf.cxx.

Referenced by RooNLLVar::evaluatePartition().

virtual ExtendMode RooAbsPdf::extendMode ( ) const

inlinevirtual

Reimplemented in RooProdPdf, RooAddPdf, RooAddModel, RooSimultaneous, RooRealSumPdf, RooExtendPdf, and RooExtendedTerm.

Definition at line 210 of file RooAbsPdf.h.

Referenced by canBeExtended(), RooAbsReal::createHistogram(), createNLL(), generate(), mustBeExtended(), and RooAbsGenContext::RooAbsGenContext().

RooFitResult * RooAbsPdf::fitTo	(	RooAbsData &	data,
		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()`
	)

virtual

Fit PDF to given dataset.

If dataset is unbinned, an unbinned maximum likelihood is performed. If the dataset is binned, a binned maximum likelihood is performed. By default the fit is executed through the MINUIT commands MIGRAD, HESSE in succession.

The following named arguments are supported

Options to control construction of -log(L)

ConditionalObservables(const RooArgSet& set) – Do not normalize PDF over listed observables Extended(Bool_t flag) – Add extended likelihood term, off by default Range(const char* name) – Fit only data inside range with given name Range(Double_t lo, Double_t hi) – Fit only data inside given range. A range named "fit" is created on the fly on all observables. Multiple comma separated range names can be specified. SumCoefRange(const char* name) – Set the range in which to interpret the coefficients of RooAddPdf components NumCPU(int num, int strat) – Parallelize NLL calculation on num CPUs

                               Strategy 0 = RooFit::BulkPartition (Default) --> Divide events in N equal chunks 
                               Strategy 1 = RooFit::Interleave --> Process event i%N in process N. Recommended for binned data with 
                                            a substantial number of zero-bins, which will be distributed across processes more equitably in this strategy
                               Strategy 2 = RooFit::SimComponents --> Process each component likelihood of a RooSimultaneous fully in a single process
                                            and distribute components over processes. This approach can be benificial if normalization calculation time
                                            dominates the total computation time of a component (since the normalization calculation must be performed
                                            in each process in strategies 0 and 1. However beware that if the RooSimultaneous components do not share many
                                            parameters this strategy is inefficient: as most minuit-induced likelihood calculations involve changing
                                            a single parameter, only 1 of the N processes will be active most of the time if RooSimultaneous components
                                            do not share many parameters
                               Strategy 3 = RooFit::Hybrid --> Follow strategy 0 for all RooSimultaneous components, except those with less than
                                            30 dataset entries, for which strategy 2 is followed.

SplitRange(Bool_t flag) – Use separate fit ranges in a simultaneous fit. Actual range name for each subsample is assumed to by rangeName_{indexState} where indexState is the state of the master index category of the simultaneous fit Constrained() – Apply all constrained contained in the p.d.f. in the likelihood Contrain(const RooArgSet&pars) – Apply constraints to listed parameters in likelihood using internal constrains in p.d.f GlobalObservables(const RooArgSet&) – Define the set of normalization observables to be used for the constraint terms. If none are specified the constrained parameters are used ExternalConstraints(const RooArgSet& ) – Include given external constraints to likelihood Offset(Bool_t) – Offset likelihood by initial value (so that starting value of FCN in minuit is zero). This can improve numeric stability in simultaneously fits with components with large likelihood values

Options to control flow of fit procedure

Minimizer(type,algo) – Choose minimization package and algorithm to use. Default is MINUIT/MIGRAD through the RooMinimizer interface, but others can be specified (through RooMinimizer interface). Select OldMinuit to use MINUIT through the old RooMinuit interface

   Type         Algorithm
   ------       ---------
   OldMinuit    migrad, simplex, minimize (=migrad+simplex), migradimproved (=migrad+improve)
   Minuit       migrad, simplex, minimize (=migrad+simplex), migradimproved (=migrad+improve)
   Minuit2      migrad, simplex, minimize, scan
   GSLMultiMin  conjugatefr, conjugatepr, bfgs, bfgs2, steepestdescent
   GSLSimAn     -

InitialHesse(Bool_t flag) – Flag controls if HESSE before MIGRAD as well, off by default Optimize(Bool_t flag) – Activate constant term optimization of test statistic during minimization (on by default) Hesse(Bool_t flag) – Flag controls if HESSE is run after MIGRAD, on by default Minos(Bool_t flag) – Flag controls if MINOS is run after HESSE, off by default Minos(const RooArgSet& set) – Only run MINOS on given subset of arguments Save(Bool_t flag) – Flac controls if RooFitResult object is produced and returned, off by default Strategy(Int_t flag) – Set Minuit strategy (0 through 2, default is 1) FitOptions(const char* optStr) – Steer fit with classic options string (for backward compatibility). Use of this option excludes use of any of the new style steering options.

SumW2Error(Bool_t flag) – Apply correaction to errors and covariance matrix using sum-of-weights covariance matrix to obtain correct error for weighted likelihood fits. If this option is activated the corrected covariance matrix is calculated as Vcorr = V C-1 V, where V is the original covariance matrix and C is the inverse of the covariance matrix calculated using the weights squared

Options to control informational output

Verbose(Bool_t flag) – Flag controls if verbose output is printed (NLL, parameter changes during fit Timer(Bool_t flag) – Time CPU and wall clock consumption of fit steps, off by default PrintLevel(Int_t level) – Set Minuit print level (-1 through 3, default is 1). At -1 all RooFit informational messages are suppressed as well Warnings(Bool_t flag) – Enable or disable MINUIT warnings (enabled by default) PrintEvalErrors(Int_t numErr) – Control number of p.d.f evaluation errors printed per likelihood evaluation. A negative value suppress output completely, a zero value will only print the error count per p.d.f component, a positive value is will print details of each error up to numErr messages per p.d.f component.

Definition at line 1056 of file RooAbsPdf.cxx.

Referenced by RooStats::SPlot::AddSWeight(), ClassImp(), RooStats::BernsteinCorrection::CreateQSamplingDist(), RooMCStudy::doFit(), DoSPlot(), RooGenFitStudy::execute(), RooStats::HistFactory::FitModel(), RooStats::HistFactory::FitModelAndPlot(), FitUsingRooFit(), FourBinInstructional(), RooStats::BernsteinCorrection::ImportCorrectedPdf(), JeffreysPriorDemo(), RooStats::AsymptoticCalculator::MakeAsimovData(), MakePlots(), MultivariateGaussianTest(), RooMCStudy::plotPull(), rs101_limitexample(), rs401d_FeldmanCousins(), rs601_HLFactoryexample(), rs603_HLFactoryElaborateExample(), rs_bernsteinCorrection(), RooStats::HybridCalculatorOriginal::RunToys(), StandardBayesianNumericalDemo(), StandardHistFactoryPlotsWithCategories(), TestJeffreysGaussMean(), TestJeffreysGaussMeanAndSigma(), and TestJeffreysGaussSigma().

RooFitResult * RooAbsPdf::fitTo	(	RooAbsData &	data,
		const RooLinkedList &	cmdList
	)

virtual

Fit PDF to given dataset.

If dataset is unbinned, an unbinned maximum likelihood is performed. If the dataset is binned, a binned maximum likelihood is performed. By default the fit is executed through the MINUIT commands MIGRAD, HESSE and MINOS in succession.

See RooAbsPdf::fitTo(RooAbsData& data, RooCmdArg arg1, RooCmdArg arg2, RooCmdArg arg3, RooCmdArg arg4, RooCmdArg arg5, RooCmdArg arg6, RooCmdArg arg7, RooCmdArg arg8)

for documentation of options

Definition at line 1079 of file RooAbsPdf.cxx.

RooAbsGenContext * RooAbsPdf::genContext	(	const RooArgSet &	vars,
		const RooDataSet *	prototype = `0`,
		const RooArgSet *	auxProto = `0`,
		Bool_t	verbose = `kFALSE`
	)		const

virtual

Interface function to create a generator context from a p.d.f.

This default implementation returns a 'standard' context that works for any p.d.f

Reimplemented in RooProdPdf, RooAddPdf, RooFFTConvPdf, RooSimultaneous, RooAddModel, RooAbsAnaConvPdf, RooNumConvPdf, and RooEffProd.

Definition at line 1638 of file RooAbsPdf.cxx.

Referenced by autoGenContext(), RooProdPdf::genContext(), generate(), RooAddGenContext::RooAddGenContext(), RooConvGenContext::RooConvGenContext(), RooEffGenContext::RooEffGenContext(), RooMCStudy::RooMCStudy(), RooProdGenContext::RooProdGenContext(), and RooSimGenContext::RooSimGenContext().

RooDataSet * RooAbsPdf::generate	(	const RooArgSet &	whatVars,
		Int_t	nEvents,
		const RooCmdArg &	arg1,
		const RooCmdArg &	arg2 = `RooCmdArg::none()`,
		const RooCmdArg &	arg3 = `RooCmdArg::none()`,
		const RooCmdArg &	arg4 = `RooCmdArg::none()`,
		const RooCmdArg &	arg5 = `RooCmdArg::none()`
	)

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or expectedEvents() if not specified.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

The following named arguments are supported

Name(const char* name) – Name of the output dataset Verbose(Bool_t flag) – Print informational messages during event generation Extended() – The actual number of events generated will be sampled from a Poisson distribution with mu=nevt. For use with extended maximum likelihood fits AutoBinned(Bool_t flag) – Automatically deploy binned generation for binned distributions (e.g. RooHistPdf, sums and products of RooHistPdfs etc) NB: Datasets that are generated in binned mode are returned as weighted unbinned datasets

GenBinned(const char* tag) – Use binned generation for all component pdfs that have 'setAttribute(tag)' set AllBinned() – As above, but for all components.

                                  Note that the notion of components is only meaningful for simultaneous pdf
                                  as binned generation is always executed at the top-level node for a regular
                                  pdf, so for those it only mattes that the top-level node is tagged.

ProtoData(const RooDataSet& data, – Use specified dataset as prototype dataset. If randOrder is set to true Bool_t randOrder) the order of the events in the dataset will be read in a random order if the requested number of events to be generated does not match the number of events in the prototype dataset

If ProtoData() is used, the specified existing dataset as a prototype: the new dataset will contain the same number of events as the prototype (unless otherwise specified), and any prototype variables not in whatVars will be copied into the new dataset for each generated event and also used to set our PDF parameters. The user can specify a number of events to generate that will override the default. The result is a copy of the prototype dataset with only variables in whatVars randomized. Variables in whatVars that are not in the prototype will be added as new columns to the generated dataset.

Definition at line 1702 of file RooAbsPdf.cxx.

Referenced by AddData(), ClassImp(), RooStats::BernsteinCorrection::CreateQSamplingDist(), RooGenFitStudy::execute(), FourBinInstructional(), generate(), RooSimultaneous::generateSimGlobal(), generateSimGlobal(), HybridOriginalDemo(), IntervalExamples(), MultivariateGaussianTest(), OneSidedFrequentistUpperLimitWithBands(), RooStats::PdfProposal::Propose(), rs401c_FeldmanCousins(), rs401d_FeldmanCousins(), rs601_HLFactoryexample(), rs603_HLFactoryElaborateExample(), rs801_HypoTestInverterOriginal(), rs_bernsteinCorrection(), RooStats::HybridCalculatorOriginal::RunToys(), TestNonCentral(), and TwoSidedFrequentistUpperLimitWithBands().

RooDataSet * RooAbsPdf::generate	(	const RooArgSet &	whatVars,
		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()`
	)

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or expectedEvents() if not specified.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

The following named arguments are supported

Name(const char* name) – Name of the output dataset Verbose(Bool_t flag) – Print informational messages during event generation NumEvent(int nevt) – Generate specified number of events

AutoBinned(Bool_t flag) – Automatically deploy binned generation for binned distributions (e.g. RooHistPdf, sums and products of RooHistPdfs etc) NB: Datasets that are generated in binned mode are returned as weighted unbinned datasets

GenBinned(const char* tag) – Use binned generation for all component pdfs that have 'setAttribute(tag)' set AllBinned() – As above, but for all components.

                                  Note that the notion of components is only meaningful for simultaneous pdf
                                  as binned generation is always executed at the top-level node for a regular
                                  pdf, so for those it only mattes that the top-level node is tagged.

                                  Binned generation cannot be used when prototype data is supplied

Extended() – The actual number of events generated will be sampled from a Poisson distribution with mu=nevt. For use with extended maximum likelihood fits ProtoData(const RooDataSet& data, – Use specified dataset as prototype dataset. If randOrder is set to true Bool_t randOrder, the order of the events in the dataset will be read in a random order Bool_t resample) if the requested number of events to be generated does not match the number of events in the prototype dataset. If resample is also set to true, the prototype dataset will be resampled rather than be strictly reshuffled. In this mode events of the protodata may be used more than once.

If ProtoData() is used, the specified existing dataset as a prototype: the new dataset will contain the same number of events as the prototype (unless otherwise specified), and any prototype variables not in whatVars will be copied into the new dataset for each generated event and also used to set our PDF parameters. The user can specify a number of events to generate that will override the default. The result is a copy of the prototype dataset with only variables in whatVars randomized. Variables in whatVars that are not in the prototype will be added as new columns to the generated dataset.

Definition at line 1753 of file RooAbsPdf.cxx.

RooDataSet * RooAbsPdf::generate	(	const RooArgSet &	whatVars,
		Double_t	nEvents = `0`,
		Bool_t	verbose = `kFALSE`,
		Bool_t	autoBinned = `kTRUE`,
		const char *	binnedTag = `""`,
		Bool_t	expectedData = `kFALSE`,
		Bool_t	extended = `kFALSE`
	)		const

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or else try to use expectedEvents() if nEvents <= 0. Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

Definition at line 1959 of file RooAbsPdf.cxx.

RooDataSet * RooAbsPdf::generate	(	const RooArgSet &	whatVars,
		const RooDataSet &	prototype,
		Int_t	nEvents = `0`,
		Bool_t	verbose = `kFALSE`,
		Bool_t	randProtoOrder = `kFALSE`,
		Bool_t	resampleProto = `kFALSE`
	)		const

Generate a new dataset with values of the whatVars variables sampled from our distribution.

Use the specified existing dataset as a prototype: the new dataset will contain the same number of events as the prototype (by default), and any prototype variables not in whatVars will be copied into the new dataset for each generated event and also used to set our PDF parameters. The user can specify a number of events to generate that will override the default. The result is a copy of the prototype dataset with only variables in whatVars randomized. Variables in whatVars that are not in the prototype will be added as new columns to the generated dataset. Returns zero in case of an error. The caller takes ownership of the returned dataset.

Definition at line 2036 of file RooAbsPdf.cxx.

RooDataSet * RooAbsPdf::generate ( RooAbsPdf::GenSpec & spec ) const

Generate data according to a pre-configured specification created by RooAbsPdf::prepareMultiGen().

If many identical generation requests are needed, e.g. in toy MC studies, it is more efficient to use the prepareMultiGen()/generate() combination than calling the standard generate() multiple times as initialization overhead is only incurred once.

Definition at line 1932 of file RooAbsPdf.cxx.

RooDataSet * RooAbsPdf::generate	(	RooAbsGenContext &	context,
		const RooArgSet &	whatVars,
		const RooDataSet *	prototype,
		Double_t	nEvents,
		Bool_t	verbose,
		Bool_t	randProtoOrder,
		Bool_t	resampleProto,
		Bool_t	skipInit = `kFALSE`,
		Bool_t	extended = `kFALSE`
	)		const

protected

Internal method.

Definition at line 1988 of file RooAbsPdf.cxx.

RooDataHist * RooAbsPdf::generateBinned	(	const RooArgSet &	whatVars,
		Double_t	nEvents,
		const RooCmdArg &	arg1,
		const RooCmdArg &	arg2 = `RooCmdArg::none()`,
		const RooCmdArg &	arg3 = `RooCmdArg::none()`,
		const RooCmdArg &	arg4 = `RooCmdArg::none()`,
		const RooCmdArg &	arg5 = `RooCmdArg::none()`
	)

virtual

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or expectedEvents() if not specified.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

The following named arguments are supported

Name(const char* name) – Name of the output dataset Verbose(Bool_t flag) – Print informational messages during event generation Extended() – The actual number of events generated will be sampled from a Poisson distribution with mu=nevt. For use with extended maximum likelihood fits ExpectedData() – Return a binned dataset without statistical fluctuations (also aliased as Asimov())

Definition at line 2175 of file RooAbsPdf.cxx.

Referenced by generateBinned(), JeffreysPriorDemo(), RooMCStudy::run(), RooStats::HybridCalculatorOriginal::RunToys(), TestJeffreysGaussMean(), TestJeffreysGaussMeanAndSigma(), and TestJeffreysGaussSigma().

RooDataHist * RooAbsPdf::generateBinned	(	const RooArgSet &	whatVars,
		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()`
	)

virtual

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or expectedEvents() if not specified.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

The following named arguments are supported

Name(const char* name) – Name of the output dataset Verbose(Bool_t flag) – Print informational messages during event generation NumEvent(int nevt) – Generate specified number of events Extended() – The actual number of events generated will be sampled from a Poisson distribution with mu=nevt. For use with extended maximum likelihood fits ExpectedData() – Return a binned dataset without statistical fluctuations (also aliased as Asimov())

Definition at line 2201 of file RooAbsPdf.cxx.

RooDataHist * RooAbsPdf::generateBinned	(	const RooArgSet &	whatVars,
		Double_t	nEvents,
		Bool_t	expectedData = `kFALSE`,
		Bool_t	extended = `kFALSE`
	)		const

virtual

Generate a new dataset containing the specified variables with events sampled from our distribution.

Generate the specified number of events or else try to use expectedEvents() if nEvents <= 0.

If expectedData is kTRUE (it is kFALSE by default), the returned histogram returns the 'expected' data sample, i.e. no statistical fluctuations are present.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

Definition at line 2271 of file RooAbsPdf.cxx.

void RooAbsPdf::generateEvent ( Int_t code )

virtual

Interface for generation of anan event using the algorithm corresponding to the specified code.

The meaning of each code is defined by the getGenerator() implementation. The default implementation does nothing.

Reimplemented in RooNonCPEigenDecay, RooAddModel, RooProdPdf, RooGExpModel, RooGaussModel, RooBDecay, RooTruthModel, RooBCPGenDecay, RooMultiVarGaussian, RooBCPEffDecay, RooBMixDecay, RooProjectedPdf, RooDecay, RooGaussian, RooUniform, RooGamma, RooLandau, RooLognormal, and RooPoisson.

Definition at line 2123 of file RooAbsPdf.cxx.

Referenced by RooGenContext::generateEvent(), and RooProdPdf::generateEvent().

RooDataSet * RooAbsPdf::generateSimGlobal	(	const RooArgSet &	whatVars,
		Int_t	nEvents
	)

virtual

Special generator interface for generation of 'global observables' – for RooStats tools.

Reimplemented in RooSimultaneous.

Definition at line 2383 of file RooAbsPdf.cxx.

Referenced by ClassImp().

RooArgSet * RooAbsPdf::getAllConstraints	(	const RooArgSet &	observables,
		RooArgSet &	constrainedParams,
		Bool_t	stripDisconnected = `kTRUE`
	)		const

virtual

This helper function finds and collects all constraints terms of all coponent p.d.f.s and returns a RooArgSet with all those terms.

Definition at line 3123 of file RooAbsPdf.cxx.

Referenced by createNLL(), and RooMCStudy::RooMCStudy().

virtual RooArgSet* RooAbsPdf::getConstraints	(	const RooArgSet &	,
		RooArgSet &	,
		Bool_t
	)		const

inlinevirtual

Reimplemented in RooProdPdf.

Definition at line 168 of file RooAbsPdf.h.

Referenced by getAllConstraints().

Int_t RooAbsPdf::getGenerator	(	const RooArgSet &	directVars,
		RooArgSet &	generateVars,
		Bool_t	staticInitOK = `kTRUE`
	)		const

virtual

Load generatedVars with the subset of directVars that we can generate events for, and return a code that specifies the generator algorithm we will use.

A code of zero indicates that we cannot generate any of the directVars (in this case, nothing should be added to generatedVars). Any non-zero codes will be passed to our generateEvent() implementation, but otherwise its value is arbitrary. The default implemetation of this method returns zero. Subclasses will usually implement this method using the matchArgs() methods to advertise the algorithms they provide.

Reimplemented in RooNonCPEigenDecay, RooAddModel, RooProdPdf, RooGExpModel, RooGaussModel, RooBDecay, RooTruthModel, RooBCPGenDecay, RooMultiVarGaussian, RooBCPEffDecay, RooBMixDecay, RooDecay, RooGaussian, RooProjectedPdf, RooUniform, RooGamma, RooLandau, RooLognormal, and RooPoisson.

Definition at line 2101 of file RooAbsPdf.cxx.

Referenced by RooNumConvPdf::genContext(), RooAbsAnaConvPdf::genContext(), RooFFTConvPdf::genContext(), RooProdPdf::getGenerator(), RooAddModel::getGenerator(), and RooGenContext::RooGenContext().

const RooNumGenConfig * RooAbsPdf::getGeneratorConfig ( ) const

Return the numeric MC generator configuration used for this object.

If a specialized configuration was associated with this object, that configuration is returned, otherwise the default configuration for all RooAbsReals is returned

Definition at line 3218 of file RooAbsPdf.cxx.

Referenced by RooGenContext::RooGenContext().

Double_t RooAbsPdf::getLogVal ( const RooArgSet * nset = 0 ) const

virtual

Return the log of the current value with given normalization An error message is printed if the argument of the log is negative.

Reimplemented in RooGaussian, RooPoisson, and RooHistConstraint.

Definition at line 606 of file RooAbsPdf.cxx.

Referenced by RooNLLVar::evaluatePartition(), RooPoisson::getLogVal(), and RooGaussian::getLogVal().

Double_t RooAbsPdf::getNorm ( const RooArgSet & nset ) const

inline

Definition at line 190 of file RooAbsPdf.h.

Referenced by analyticalIntegralWN(), RooRealSumPdf::expectedEvents(), RooGenContext::generateEvent(), and RooGenContext::RooGenContext().

Double_t RooAbsPdf::getNorm ( const RooArgSet * set = 0 ) const

virtual

Return the integral of this PDF over all observables listed in 'nset'.

Reimplemented in RooResolutionModel.

Definition at line 376 of file RooAbsPdf.cxx.

const RooAbsReal* RooAbsPdf::getNormIntegral ( const RooArgSet & nset ) const

inline

Definition at line 248 of file RooAbsPdf.h.

const RooAbsReal * RooAbsPdf::getNormObj	(	const RooArgSet *	set,
		const RooArgSet *	iset,
		const TNamed *	rangeName = `0`
	)		const

virtual

Return pointer to RooAbsReal object that implements calculation of integral over observables iset in range rangeName, optionally taking the integrand normalized over observables nset.

Definition at line 400 of file RooAbsPdf.cxx.

Referenced by RooAbsAnaConvPdf::analyticalIntegralWN(), RooExtendPdf::expectedEvents(), and getNormIntegral().

Double_t RooAbsPdf::getValV ( const RooArgSet * nset = 0 ) const

virtual

Return current value, normalizated by integrating over the observables in 'nset'.

If 'nset' is 0, the unnormalized value. is returned. All elements of 'nset' must be lvalues

Unnormalized values are not cached Doing so would be complicated as _norm->getVal() could spoil the cache and interfere with returning the cached return value. Since unnormalized calls are typically done in integration calls, there is no performance hit.

Reimplemented from RooAbsReal.

Reimplemented in RooProdPdf, RooResolutionModel, RooAbsCachedPdf, RooProjectedPdf, and RooEffProd.

Definition at line 252 of file RooAbsPdf.cxx.

Referenced by RooEffProd::getValV(), RooAbsCachedPdf::getValV(), RooProjectedPdf::getValV(), RooResolutionModel::getValV(), and RooProdPdf::getValV().

void RooAbsPdf::initGenerator ( Int_t code )

virtual

Interface for one-time initialization to setup the generator for the specified code.

Reimplemented in RooNonCPEigenDecay, RooProdPdf, RooBCPGenDecay, RooMultiVarGaussian, RooBCPEffDecay, RooBMixDecay, and RooProjectedPdf.

Definition at line 2111 of file RooAbsPdf.cxx.

Referenced by RooGenContext::initGenerator(), and RooProdPdf::initGenerator().

Bool_t RooAbsPdf::isDirectGenSafe ( const RooAbsArg & arg ) const

virtual

Check if given observable can be safely generated using the pdfs internal generator mechanism (if that existsP).

Observables on which a PDF depends via more than route are not safe for use with internal generators because they introduce correlations not known to the internal generator

Reimplemented in RooAddModel, RooProdPdf, and RooAbsAnaConvPdf.

Definition at line 2136 of file RooAbsPdf.cxx.

Referenced by RooNumConvPdf::genContext(), RooAbsAnaConvPdf::genContext(), RooFFTConvPdf::genContext(), RooAbsAnaConvPdf::isDirectGenSafe(), RooAddModel::isDirectGenSafe(), RooProdPdf::isDirectGenSafe(), and RooGenContext::RooGenContext().

Bool_t RooAbsPdf::mustBeExtended ( ) const

inline

Definition at line 220 of file RooAbsPdf.h.

Referenced by RooSimultaneous::extendMode().

const char* RooAbsPdf::normRange ( ) const

inline

Definition at line 243 of file RooAbsPdf.h.

Referenced by RooProdPdf::getPartIntList(), RooAbsReal::integralNameSuffix(), RooProdPdf::processProductTerm(), and RooAbsGenContext::RooAbsGenContext().

RooPlot * RooAbsPdf::paramOn	(	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()`
	)

virtual

Add a box with parameter values (and errors) to the specified frame.

The following named arguments are supported

Parameters(const RooArgSet& param) – Only the specified subset of parameters will be shown. By default all non-contant parameters are shown ShowConstants(Bool_t flag) – Also display constant parameters Format(const char* optStr) – Classing [arameter formatting options, provided for backward compatibility Format(const char* what,...) – Parameter formatting options, details given below Label(const chat* label) – Add header label to parameter box Layout(Double_t xmin, – Specify relative position of left,right side of box and top of box. Position of Double_t xmax, Double_t ymax) bottom of box is calculated automatically from number lines in box

The Format(const char* what,...) has the following structure

const char* what – Controls what is shown. "N" adds name, "E" adds error, "A" shows asymmetric error, "U" shows unit, "H" hides the value FixedPrecision(int n) – Controls precision, set fixed number of digits AutoPrecision(int n) – Controls precision. Number of shown digits is calculated from error

n specified additional digits (1 is sensible default)

Example use: pdf.paramOn(frame, Label("fit result"), Format("NEU",AutoPrecision(1)) ) ;

Definition at line 2779 of file RooAbsPdf.cxx.

Referenced by paramOn(), and RooMCStudy::plotPull().

RooPlot * RooAbsPdf::paramOn	(	RooPlot *	frame,
		const RooAbsData *	data,
		const char *	label = `""`,
		Int_t	sigDigits = `2`,
		Option_t *	options = `"NELU"`,
		Double_t	xmin = `0.50`,
		Double_t	xmax = `0.99`,
		Double_t	ymax = `0.95`
	)

virtual

OBSOLETE FUNCTION PROVIDED FOR BACKWARD COMPATIBILITY.

Definition at line 2852 of file RooAbsPdf.cxx.

RooPlot * RooAbsPdf::paramOn	(	RooPlot *	frame,
		const RooArgSet &	params,
		Bool_t	showConstants = `kFALSE`,
		const char *	label = `""`,
		Int_t	sigDigits = `2`,
		Option_t *	options = `"NELU"`,
		Double_t	xmin = `0.65`,
		Double_t	xmax = `0.99`,
		Double_t	ymax = `0.95`,
		const RooCmdArg *	formatCmd = `0`
	)

protectedvirtual

Add a text box with the current parameter values and their errors to the frame.

Observables of this PDF appearing in the 'data' dataset will be omitted.

Optional label will be inserted as first line of the text box. Use 'sigDigits' to modify the default number of significant digits printed. The 'xmin,xmax,ymax' values specify the inital relative position of the text box in the plot frame

Definition at line 2873 of file RooAbsPdf.cxx.

virtual RooPlot* RooAbsPdf::plotOn	(	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()`,
		const RooCmdArg &	arg9 = `RooCmdArg::none()`,
		const RooCmdArg &	arg10 = `RooCmdArg::none()`
	)		const

inlinevirtual

Plot (project) PDF on specified frame.

If a PDF is plotted in an empty frame, it will show a unit normalized curve in the frame variable, taken at the present value of other observables defined for this PDF

If a PDF is plotted in a frame in which a dataset has already been plotted, it will show a projected curve integrated over all variables that were present in the shown dataset except for the one on the x-axis. The normalization of the curve will also be adjusted to the event count of the plotted dataset. An informational message will be printed for each projection step that is performed

This function takes the following named arguments

Projection control

Slice(const RooArgSet& set) – Override default projection behaviour by omittting observables listed in set from the projection, resulting a 'slice' plot. Slicing is usually only sensible in discrete observables. The slice is position at the 'current' value of the observable objects

Slice(RooCategory& cat, – Override default projection behaviour by omittting specified category const char* label) observable from the projection, resulting in a 'slice' plot. The slice is positioned at the given label value. Multiple Slice() commands can be given to specify slices in multiple observables

Project(const RooArgSet& set) – Override default projection behaviour by projecting over observables given in set and complete ignoring the default projection behavior. Advanced use only.

ProjWData(const RooAbsData& d) – Override default projection technique (integration). For observables present in given dataset projection of PDF is achieved by constructing an average over all observable values in given set. Consult RooFit plotting tutorial for further explanation of meaning & use of this technique

ProjWData(const RooArgSet& s, – As above but only consider subset 's' of observables in dataset 'd' for projection through data averaging const RooAbsData& d)

ProjectionRange(const char* rn) – Override default range of projection integrals to a different range speficied by given range name. This technique allows you to project a finite width slice in a real-valued observable

NumCPU(Int_t ncpu) – Number of CPUs to use simultaneously to calculate data-weighted projections (only in combination with ProjWData)

Misc content control

PrintEvalErrors(Int_t numErr) – Control number of p.d.f evaluation errors printed per curve. A negative value suppress output completely, a zero value will only print the error count per p.d.f component, a positive value is will print details of each error up to numErr messages per p.d.f component.

EvalErrorValue(Double_t value) – Set curve points at which (pdf) evaluation error occur to specified value. By default the function value is plotted.

Normalization(Double_t scale, – Adjust normalization by given scale factor. Interpretation of number depends on code: Relative: ScaleType code) relative adjustment factor, NumEvent: scale to match given number of events.

Name(const chat* name) – Give curve specified name in frame. Useful if curve is to be referenced later

Asymmetry(const RooCategory& c) – Show the asymmetry of the PDF in given two-state category [F(+)-F(-)] / [F(+)+F(-)] rather than the PDF projection. Category must have two states with indices -1 and +1 or three states with indeces -1,0 and +1.

ShiftToZero(Bool_t flag) – Shift entire curve such that lowest visible point is at exactly zero. Mostly useful when plotting -log(L) or chi^2 distributions

AddTo(const char* name, – Add constructed projection to already existing curve with given name and relative weight factors double_t wgtSelf, double_t wgtOther)

Plotting control

DrawOption(const char* opt) – Select ROOT draw option for resulting TGraph object

LineStyle(Int_t style) – Select line style by ROOT line style code, default is solid

LineColor(Int_t color) – Select line color by ROOT color code, default is blue

LineWidth(Int_t width) – Select line with in pixels, default is 3

FillStyle(Int_t style) – Select fill style, default is not filled. If a filled style is selected, also use VLines() to add vertical downward lines at end of curve to ensure proper closure FillColor(Int_t color) – Select fill color by ROOT color code

Range(const char* name) – Only draw curve in range defined by given name

Range(double lo, double hi) – Only draw curve in specified range

VLines() – Add vertical lines to y=0 at end points of curve

Precision(Double_t eps) – Control precision of drawn curve w.r.t to scale of plot, default is 1e-3. Higher precision will result in more and more densely spaced curve points

Invisible(Bool_t flag) – Add curve to frame, but do not display. Useful in combination AddTo()

VisualizeError(const RooFitResult& fitres, Double_t Z=1, Bool_t linearMethod=kTRUE) – Visualize the uncertainty on the parameters, as given in fitres, at 'Z' sigma'

VisualizeError(const RooFitResult& fitres, const RooArgSet& param, Double_t Z=1, Bool_t linearMethod=kTRUE) ; – Visualize the uncertainty on the subset of parameters 'param', as given in fitres, at 'Z' sigma'

Details on error band visualization

By default (linMethod=kTRUE) a linearized error is shown which is calculated as follows T error(x) = Z* F_a(x) * Corr(a,a') F_a'(x)

where F_a(x) = [ f(x,a+da) - f(x,a-da) ] / 2, with f(x) the plotted curve and 'da' taken from the fit result Corr(a,a') = the correlation matrix from the fit result Z = requested significance 'Z sigma band'

The linear method is fast (required 2*N evaluations of the curve, where N is the number of parameters), but may not be accurate in the presence of strong correlations (~>0.9) and at Z>2 due to linear and Gaussian approximations made

Alternatively (linMethod=kFALSE), a more robust error is calculated using a sampling method. In this method a number of curves is calculated with variations of the parameter values, as drawn from a multi-variate Gaussian p.d.f. that is constructed from the fit results covariance matrix. The error(x) is determined by calculating a central interval that capture N% of the variations for each valye of x, where N% is controlled by Z (i.e. Z=1 gives N=68%). The number of sampling curves is chosen to be such that at least 30 curves are expected to be outside the N% interval, and is minimally 100 (e.g. Z=1->Ncurve=100, Z=2->Ncurve=659, Z=3->Ncurve=11111) Intervals from the sampling method can be asymmetric, and may perform better in the presence of strong correlations, but may take (much) longer to calculate

Reimplemented from RooAbsReal.

Reimplemented in RooSimultaneous.

Definition at line 105 of file RooAbsPdf.h.

Referenced by ClassImp(), MakePlots(), RooSimultaneous::plotOn(), RooMCStudy::plotPull(), rs401d_FeldmanCousins(), rs601_HLFactoryexample(), rs603_HLFactoryElaborateExample(), rs_bernsteinCorrection(), StandardHistFactoryPlotsWithCategories(), TestJeffreysGaussMean(), TestJeffreysGaussSigma(), TestNonCentral(), and Zbi_Zgamma().

RooPlot * RooAbsPdf::plotOn	(	RooPlot *	frame,
		RooLinkedList &	cmdList
	)		const

virtual

Plot (project) PDF on specified frame.

If a PDF is plotted in an empty frame, it will show a unit normalized curve in the frame variable, taken at the present value of other observables defined for this PDF

If a PDF is plotted in a frame in which a dataset has already been plotted, it will show a projected curve integrated over all variables that were present in the shown dataset except for the one on the x-axis. The normalization of the curve will also be adjusted to the event count of the plotted dataset. An informational message will be printed for each projection step that is performed

This function takes the following named arguments

Projection control

Slice(const RooArgSet& set) – Override default projection behaviour by omittting observables listed in set from the projection, resulting a 'slice' plot. Slicing is usually only sensible in discrete observables Project(const RooArgSet& set) – Override default projection behaviour by projecting over observables given in set and complete ignoring the default projection behavior. Advanced use only. ProjWData(const RooAbsData& d) – Override default projection technique (integration). For observables present in given dataset projection of PDF is achieved by constructing an average over all observable values in given set. Consult RooFit plotting tutorial for further explanation of meaning & use of this technique ProjWData(const RooArgSet& s, – As above but only consider subset 's' of observables in dataset 'd' for projection through data averaging const RooAbsData& d) ProjectionRange(const char* rn) – Override default range of projection integrals to a different range speficied by given range name. This technique allows you to project a finite width slice in a real-valued observable NormRange(const char* name) – Calculate curve normalization w.r.t. only in specified ranges. NB: A Range() by default implies a NormRange() on the same range, but this option allows to override the default, or specify a normalization ranges when the full curve is to be drawn

Misc content control

Normalization(Double_t scale, – Adjust normalization by given scale factor. Interpretation of number depends on code: Relative: ScaleType code) relative adjustment factor, NumEvent: scale to match given number of events. Name(const chat* name) – Give curve specified name in frame. Useful if curve is to be referenced later Asymmetry(const RooCategory& c) – Show the asymmetry of the PDF in given two-state category [F(+)-F(-)] / [F(+)+F(-)] rather than the PDF projection. Category must have two states with indices -1 and +1 or three states with indeces -1,0 and +1. ShiftToZero(Bool_t flag) – Shift entire curve such that lowest visible point is at exactly zero. Mostly useful when plotting -log(L) or chi^2 distributions AddTo(const char* name, – Add constructed projection to already existing curve with given name and relative weight factors double_t wgtSelf, double_t wgtOther)

Plotting control

LineStyle(Int_t style) – Select line style by ROOT line style code, default is solid LineColor(Int_t color) – Select line color by ROOT color code, default is blue LineWidth(Int_t width) – Select line with in pixels, default is 3 FillStyle(Int_t style) – Select fill style, default is not filled. If a filled style is selected, also use VLines() to add vertical downward lines at end of curve to ensure proper closure FillColor(Int_t color) – Select fill color by ROOT color code Range(const char* name) – Only draw curve in range defined by given name Range(double lo, double hi) – Only draw curve in specified range VLines() – Add vertical lines to y=0 at end points of curve Precision(Double_t eps) – Control precision of drawn curve w.r.t to scale of plot, default is 1e-3. Higher precision will result in more and more densely spaced curve points A negative precision value will disable adaptive point spacing and restrict sampling to the grid point of points defined by the binning of the plotted observabled (recommended for expensive functions such as profile likelihoods) Invisble(Bool_t flag) – Add curve to frame, but do not display. Useful in combination AddTo()

Reimplemented from RooAbsReal.

Reimplemented in RooSimultaneous.

Definition at line 2452 of file RooAbsPdf.cxx.

RooPlot * RooAbsPdf::plotOn	(	RooPlot *	frame,
		PlotOpt	o
	)		const

protectedvirtual

Reimplemented from RooAbsReal.

Definition at line 2705 of file RooAbsPdf.cxx.

RooAbsPdf::GenSpec * RooAbsPdf::prepareMultiGen	(	const RooArgSet &	whatVars,
		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()`
	)

Prepare GenSpec configuration object for efficient generation of multiple datasets from idetical specification This method does not perform any generation.

To generate according to generations specification call RooAbsPdf::generate(RooAbsPdf::GenSpec&)

Generate the specified number of events or expectedEvents() if not specified.

Any variables of this PDF that are not in whatVars will use their current values and be treated as fixed parameters. Returns zero in case of an error. The caller takes ownership of the returned dataset.

The following named arguments are supported

Name(const char* name) – Name of the output dataset Verbose(Bool_t flag) – Print informational messages during event generation NumEvent(int nevt) – Generate specified number of events

Definition at line 1855 of file RooAbsPdf.cxx.

Referenced by ClassImp(), and RooGenFitStudy::initialize().

void RooAbsPdf::printMultiline	(	std::ostream &	os,
		Int_t	contents,
		Bool_t	verbose = `kFALSE`,
		TString	indent = `""`
	)		const

virtual

Print multi line detailed information of this RooAbsPdf.

Reimplemented from RooAbsReal.

Reimplemented in RooResolutionModel, RooAbsAnaConvPdf, and RooGenericPdf.

Definition at line 1611 of file RooAbsPdf.cxx.

Referenced by RooGenericPdf::printMultiline(), RooAbsAnaConvPdf::printMultiline(), and RooResolutionModel::printMultiline().

void RooAbsPdf::printValue ( std::ostream & os ) const

virtual

Print value of p.d.f, also print normalization integral that was last used, if any.

Reimplemented from RooAbsReal.

Definition at line 1595 of file RooAbsPdf.cxx.

void RooAbsPdf::raiseEvalError ( )

staticprotected

Raise the evaluation error flag.

Definition at line 3170 of file RooAbsPdf.cxx.

Int_t * RooAbsPdf::randomizeProtoOrder	(	Int_t	nProto,
		Int_t	nGen,
		Bool_t	resample = `kFALSE`
	)		const

protected

Return lookup table with randomized access order for prototype events, given nProto prototype data events and nGen events that will actually be accessed.

Definition at line 2057 of file RooAbsPdf.cxx.

Referenced by generate(), and RooMCStudy::run().

virtual Bool_t RooAbsPdf::redirectServersHook	(	const RooAbsCollection &	,
		Bool_t	,
		Bool_t	,
		Bool_t
	)

inlineprotectedvirtual

Reimplemented from RooAbsArg.

Reimplemented in RooProdPdf, RooFFTConvPdf, RooResolutionModel, RooProjectedPdf, and RooGenericPdf.

Definition at line 316 of file RooAbsPdf.h.

void RooAbsPdf::resetErrorCounters ( Int_t resetValue = 10 )

virtual

Reset error counter to given value, limiting the number of future error messages for this pdf to 'resetValue'.

Reimplemented in RooAddPdf, and RooAddModel.

Definition at line 568 of file RooAbsPdf.cxx.

Referenced by RooGenContext::initGenerator(), RooAddModel::resetErrorCounters(), RooAddPdf::resetErrorCounters(), and RooAbsPdf().

virtual Bool_t RooAbsPdf::selfNormalized ( ) const

inlinevirtual

Reimplemented in RooHistPdf, RooProdPdf, RooRealSumPdf, RooAddPdf, RooSimultaneous, RooAddModel, RooMomentMorph, RooExtendPdf, RooProjectedPdf, RooIntegralMorph, and RooAbsCachedPdf.

Definition at line 202 of file RooAbsPdf.h.

Referenced by syncNormalization().

void RooAbsPdf::setGeneratorConfig ( )

Remove the specialized numeric MC generator configuration associated with this object.

Definition at line 3245 of file RooAbsPdf.cxx.

void RooAbsPdf::setGeneratorConfig ( const RooNumGenConfig & config )

Set the given configuration as default numeric MC generator configuration for this object.

Definition at line 3231 of file RooAbsPdf.cxx.

void RooAbsPdf::setNormRange ( const char * rangeName )

Definition at line 3276 of file RooAbsPdf.cxx.

void RooAbsPdf::setNormRangeOverride ( const char * rangeName )

Definition at line 3293 of file RooAbsPdf.cxx.

void RooAbsPdf::setTraceCounter	(	Int_t	value,
		Bool_t	allNodes = `kFALSE`
	)

Reset trace counter to given value, limiting the number of future trace messages for this pdf to 'value'.

Definition at line 580 of file RooAbsPdf.cxx.

Referenced by RooAbsPdf(), and setTraceCounter().

RooNumGenConfig * RooAbsPdf::specialGeneratorConfig ( ) const

Returns the specialized integrator configuration for this RooAbsReal.

If this object has no specialized configuration, a null pointer is returned

Definition at line 3190 of file RooAbsPdf.cxx.

Referenced by getGeneratorConfig().

RooNumGenConfig * RooAbsPdf::specialGeneratorConfig ( Bool_t createOnTheFly )

Returns the specialized integrator configuration for this RooAbsReal.

If this object has no specialized configuration, a null pointer is returned, unless createOnTheFly is kTRUE in which case a clone of the default integrator configuration is created, installed as specialized configuration, and returned

Definition at line 3203 of file RooAbsPdf.cxx.

Bool_t RooAbsPdf::syncNormalization	(	const RooArgSet *	nset,
		Bool_t	adjustProxies = `kTRUE`
	)		const

protectedvirtual

Verify that the normalization integral cached with this PDF is valid for given set of normalization observables.

If not, the cached normalization integral (if any) is deleted and a new integral is constructed for use with 'nset' Elements in 'nset' can be discrete and real, but must be lvalues

For functions that declare to be self-normalized by overloading the selfNormalized() function, a unit normalization is always constructed

Definition at line 435 of file RooAbsPdf.cxx.

Referenced by RooResolutionModel::getNorm(), getNorm(), and getValV().

Bool_t RooAbsPdf::traceEvalHook ( Double_t value ) const

virtual

WVE 08/21/01 Probably obsolete now.

Reimplemented from RooAbsReal.

Reimplemented in RooResolutionModel.

Definition at line 534 of file RooAbsPdf.cxx.

Bool_t RooAbsPdf::traceEvalPdf ( Double_t value ) const

Check that passed value is positive and not 'not-a-number'.

If not, print an error, until the error counter reaches its set maximum.