Fits MC fractions to data histogram.

A la HMCMLL, see R. Barlow and C. Beeston, Comp. Phys. Comm. 77 (1993) 219-228, and http://www.hep.man.ac.uk/~roger/hfrac.f

The virtue of this fit is that it takes into account both data and Monte Carlo statistical uncertainties. The way in which this is done is through a standard likelihood fit using Poisson statistics; however, the template (MC) predictions are also varied within statistics, leading to additional contributions to the overall likelihood. This leads to many more fit parameters (one per bin per template), but the minimisation with respect to these additional parameters is done analytically rather than introducing them as formal fit parameters. Some special care needs to be taken in the case of bins with zero content. For more details please see the original publication cited above.

An example application of this fit is given below. For a TH1* histogram ("data") fitted as the sum of three Monte Carlo sources ("mc"):

{
  TH1F *data;                              //data histogram
  TH1F *mc0;                               // first MC histogram
  TH1F *mc1;                               // second MC histogram
  TH1F *mc2;                               // third MC histogram
  ....                                     // retrieve histograms
   TObjArray *mc = new TObjArray(3);        // MC histograms are put in this array
   mc->Add(mc0);
   mc->Add(mc1);
   mc->Add(mc2);
   TFractionFitter* fit = new TFractionFitter(data, mc); // initialise
   fit->Constrain(1,0.0,1.0);               // constrain fraction 1 to be between 0 and 1
   fit->SetRangeX(1,15);                    // use only the first 15 bins in the fit
   Int_t status = fit->Fit();               // perform the fit
   std::cout << "fit status: " << status << std::endl;
   if (status == 0) {                       // check on fit status
     TH1F* result = (TH1F*) fit->GetPlot();
     data->Draw("Ep");
     result->Draw("same");
   }
}

Assumptions

A few assumptions need to be made for the fit procedure to be carried out: 1 The total number of events in each template is not too small (so that its Poisson uncertainty can be neglected). 2 The number of events in each bin is much smaller than the total number of events in each template (so that multinomial uncertainties can be replaced with Poisson uncertainties).

Biased fit uncertainties may result if these conditions are not fulfilled (see e.g. arXiv:0803.2711).

Instantiation

A fit object is instantiated through TFractionFitter* fit = new TFractionFitter(data, mc); A number of basic checks (intended to ensure that the template histograms represent the same "kind" of distribution as the data one) are carried out. The TVirtualFitter object is then addressed and all fit parameters (the template fractions) declared (initially unbounded).

Applying constraints

Fit parameters can be constrained through

fit->Constrain(parameter #, lower bound, upper bound);

Setting lower bound = upper bound = 0 removes the constraint (a la Minuit); however, a function

fit->Unconstrain(parameter #)

is also provided to simplify this.

Setting parameter values

The function

TVirtualFitter* vFit = fit->GetFitter();

is provided for direct access to the TVirtualFitter object. This allows to set and fix parameter values, and set step sizes directly.

Restricting the fit range

The fit range can be restricted through

fit->SetRangeX(first bin #, last bin #);

and freed using

fit->ReleaseRangeX();

For 2D histograms the Y range can be similarly restricted using

fit->SetRangeY(first bin #, last bin #);
fit->ReleaseRangeY();

and for 3D histograms also

fit->SetRangeZ(first bin #, last bin #);
fit->ReleaseRangeZ();

It is also possible to exclude individual bins from the fit through

fit->ExcludeBin(bin #);

where the given bin number is assumed to follow the TH1::GetBin() numbering. Any bins excluded in this way can be included again using the corresponding

fit->IncludeBin(bin #);

Weights histograms

Weights histograms (for a motivation see the above publication) can be specified for the individual MC sources through

fit->SetWeight(parameter #, pointer to weights histogram);

and unset by specifying a null pointer.

Obtaining fit results

The fit is carried out through

Int_t status = fit->Fit();

where status is the code returned from the "MINIMIZE" command. For fits that converged, parameter values and errors can be obtained through

fit->GetResult(parameter #, value, error);

and the histogram corresponding to the total Monte Carlo prediction (which is not the same as a simple weighted sum of the input Monte Carlo distributions) can be obtained by

TH1* result = fit->GetPlot();

Using different histograms

It is possible to change the histogram being fitted through

fit->SetData(TH1* data);

and to change the template histogram for a given parameter number through

fit->SetMC(parameter #, TH1* MC);

This can speed up code in case of multiple data or template histograms; however, it should be done with care as any settings are taken over from the previous fit. In addition, neither the dimensionality nor the numbers of bins of the histograms should change (in that case it is better to instantiate a new TFractionFitter object).

Errors

Any serious inconsistency results in an error.

Definition at line 29 of file TFractionFitter.h.

Public Member Functions
	TFractionFitter ()

	TFractionFitter (TH1 data, TObjArray MCs, Option_t *option="")
	TFractionFitter constructor. More...

virtual	~TFractionFitter ()
	TFractionFitter default destructor. More...

ROOT::Fit::Fitter *	GetFitter () const
	Give direct access to the underlying fitter class. More...

void	ErrorAnalysis (Double_t UP)
	Set UP to the given value (see class TMinuit), and perform a MINOS minimisation. More...

void	SetRangeX (Int_t low, Int_t high)
	Set the X range of the histogram to be used in the fit. More...

void	ReleaseRangeX ()
	Release restrictions on the X range of the histogram to be used in the fit. More...

void	SetRangeY (Int_t low, Int_t high)
	Set the Y range of the histogram to be used in the fit (2D or 3D histograms only). More...

void	ReleaseRangeY ()
	Release restrictions on the Y range of the histogram to be used in the fit. More...

void	SetRangeZ (Int_t low, Int_t high)
	Set the Z range of the histogram to be used in the fit (3D histograms only). More...

void	ReleaseRangeZ ()
	Release restrictions on the Z range of the histogram to be used in the fit. More...

void	ExcludeBin (Int_t bin)
	Exclude the given bin from the fit. More...

void	IncludeBin (Int_t bin)
	Include the given bin in the fit, if it was excluded before using ExcludeBin(). More...

void	Constrain (Int_t parm, Double_t low, Double_t high)
	Constrain the values of parameter number <parm> (the parameter numbering follows that of the input template vector). More...

void	UnConstrain (Int_t parm)
	Remove the constraints on the possible values of parameter <parm>. More...

void	SetData (TH1 *data)
	Change the histogram to be fitted to. More...

void	SetMC (Int_t parm, TH1 *MC)
	Change the histogram for template number <parm>. More...

void	SetWeight (Int_t parm, TH1 *weight)
	Set bin by bin weights for template number <parm> (the parameter numbering follows that of the input template vector). More...

TFitResultPtr	Fit ()
	Perform the fit with the default UP value. More...

void	GetResult (Int_t parm, Double_t &value, Double_t &error) const
	Obtain the fit result for parameter <parm> (the parameter numbering follows that of the input template vector). More...

TH1 *	GetPlot ()
	Return the "template prediction" corresponding to the fit result (this is not the same as the weighted sum of template distributions, as template statistical uncertainties are taken into account). More...

Double_t	GetChisquare () const
	Return the likelihood ratio Chi-squared (chi2) for the fit. More...

Int_t	GetNDF () const
	return the number of degrees of freedom in the fit the fNDF parameter has been previously computed during a fit. More...

Double_t	GetProb () const
	return the fit probability More...

TH1 *	GetMCPrediction (Int_t parm) const
	Return the adjusted MC template (Aji) for template (parm). More...

Double_t	EvaluateFCN (const Double_t *par)

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	Clear (Option_t *="")

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

virtual Int_t	Compare (const TObject *obj) const
	Compare abstract method. More...

virtual void	Copy (TObject &object) const
	Copy this to obj. 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 *	GetName () const
	Returns name of object. 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 const char *	GetTitle () const
	Returns title of object. More...

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

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

virtual Bool_t	IsSortable () const

Bool_t	IsOnHeap () const

Bool_t	IsZombie () const

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

virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout. 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 void	Print (Option_t *option="") const
	This method must be overridden when a class wants to print itself. 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...

Protected Attributes
Bool_t	fFitDone

Int_t	fLowLimitX

Int_t	fHighLimitX

Int_t	fLowLimitY

Int_t	fHighLimitY

Int_t	fLowLimitZ

Int_t	fHighLimitZ

std::vector< Int_t >	fExcludedBins

Int_t	fNpfits

Int_t	fNDF

Double_t	fChisquare

TObjArray	fAji

TH1 *	fData

TObjArray	fMCs

TObjArray	fWeights

Double_t	fIntegralData

Double_t *	fIntegralMCs

Double_t *	fFractions

TH1 *	fPlot

ROOT::Fit::Fitter *	fFractionFitter

Int_t	fNpar

Private Member Functions
void	CheckParNo (Int_t parm) const
	Function for internal use, checking parameter validity An invalid parameter results in an error. More...

void	CheckConsistency ()
	Function used internally to check the consistency between the various histograms. More...

void	FindPrediction (int bin, double &t_i, int &k_0, double &A_ki) const
	Function used internally to obtain the template prediction in the individual bins 'bin' <=> 'i' (paper) 'par' <=> 'j' (paper) More...

void	ComputeFCN (Double_t &f, const Double_t *par, Int_t flag)
	Used internally to compute the likelihood value. More...

void	GetRanges (Int_t &minX, Int_t &maxX, Int_t &minY, Int_t &maxY, Int_t &minZ, Int_t &maxZ) const
	Used internally to obtain the bin ranges according to the dimensionality of the histogram and the limits set by hand. More...

void	ComputeChisquareLambda ()
	Method used internally to compute the likelihood ratio chi2 See the function GetChisquare() for details. More...

bool	IsExcluded (Int_t bin) const
	Function for internal use, checking whether the given bin is excluded from the fit or not. More...

Additional Inherited Members
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) }

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...

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...

#include <TFractionFitter.h>

Inheritance diagram for TFractionFitter:

Collaboration diagram for TFractionFitter:

Constructor & Destructor Documentation

TFractionFitter::TFractionFitter ( )

TFractionFitter::TFractionFitter	(	TH1 *	data,
		TObjArray *	MCs,
		Option_t *	option = `""`
	)

TFractionFitter constructor.

Does a complete initialisation (including consistency checks, default fit range as the whole histogram but without under- and overflows, and declaration of the fit parameters). Note that the histograms are not copied, only references are used.

Parameters

[in]	data	histogram to be fitted
[in]	MCs	array of TH1* corresponding template distributions
[in]	option	can be used to control the print level of the minimization algorithm option = "Q" : quite - no message is printed option = "V" : verbose - max print out option = "" : default: print initial fraction values and result

Definition at line 191 of file TFractionFitter.cxx.

TFractionFitter::~TFractionFitter ( )

virtual

TFractionFitter default destructor.

Definition at line 253 of file TFractionFitter.cxx.

Member Function Documentation

void TFractionFitter::CheckConsistency ( )

private

Function used internally to check the consistency between the various histograms.

Checks are performed on nonexistent or empty histograms, the precise histogram class, and the number of bins. In addition, integrals over the "allowed" bin ranges are computed. Any inconsistency results in a error.

Definition at line 480 of file TFractionFitter.cxx.

Referenced by ExcludeBin(), IncludeBin(), ReleaseRangeX(), ReleaseRangeY(), ReleaseRangeZ(), SetData(), SetMC(), SetRangeX(), SetRangeY(), SetRangeZ(), and TFractionFitter().

void TFractionFitter::CheckParNo ( Int_t parm ) const

private

Function for internal use, checking parameter validity An invalid parameter results in an error.

Definition at line 323 of file TFractionFitter.cxx.

Referenced by Constrain(), GetMCPrediction(), GetResult(), SetMC(), SetWeight(), and UnConstrain().

void TFractionFitter::ComputeChisquareLambda ( )

private

Method used internally to compute the likelihood ratio chi2 See the function GetChisquare() for details.

Definition at line 908 of file TFractionFitter.cxx.

Referenced by Fit().

void TFractionFitter::ComputeFCN	(	Double_t &	f,
		const Double_t *	par,
		Int_t	flag
	)

private

Used internally to compute the likelihood value.

Definition at line 660 of file TFractionFitter.cxx.

Referenced by EvaluateFCN(), and GetPlot().

void TFractionFitter::Constrain	(	Int_t	parm,
		Double_t	low,
		Double_t	high
	)

Constrain the values of parameter number <parm> (the parameter numbering follows that of the input template vector).

Use UnConstrain() to remove this constraint.

Definition at line 459 of file TFractionFitter.cxx.

void TFractionFitter::ErrorAnalysis ( Double_t UP )

Set UP to the given value (see class TMinuit), and perform a MINOS minimisation.

Definition at line 579 of file TFractionFitter.cxx.

Double_t TFractionFitter::EvaluateFCN ( const Double_t * par )

inline

Definition at line 68 of file TFractionFitter.h.

Referenced by Fit().

void TFractionFitter::ExcludeBin ( Int_t bin )

Exclude the given bin from the fit.

The bin numbering to be used is that of TH1::GetBin().

Definition at line 414 of file TFractionFitter.cxx.

void TFractionFitter::FindPrediction	(	int	bin,
		double &	t_i,
		int &	k_0,
		double &	A_ki
	)		const

private

Function used internally to obtain the template prediction in the individual bins 'bin' <=> 'i' (paper) 'par' <=> 'j' (paper)

Definition at line 751 of file TFractionFitter.cxx.

Referenced by ComputeFCN().

TFitResultPtr TFractionFitter::Fit ( )

Perform the fit with the default UP value.

The value returned is the minimisation status.

Definition at line 549 of file TFractionFitter.cxx.

Double_t TFractionFitter::GetChisquare ( ) const

Return the likelihood ratio Chi-squared (chi2) for the fit.

The value is computed when the fit is executed successfully. Chi2 calculation is based on the "likelihood ratio" lambda, lambda = L(y;n) / L(m;n), where L(y;n) is the likelihood of the fit result <y> describing the data <n> and L(m;n) is the likelihood of an unknown "true" underlying distribution <m> describing the data <n>. Since <m> is unknown, the data distribution is used instead, lambda = L(y;n) / L(n;n). Note that this ratio is 1 if the fit is perfect. The chi2 value is then computed according to chi2 = -2*ln(lambda). This parameter can be shown to follow a Chi-square distribution. See for example S. Baker and R. Cousins, "Clarification of the use of chi-square and likelihood functions in fits to histograms", Nucl. Instr. Meth. A221, pp. 437-442 (1984)

Definition at line 877 of file TFractionFitter.cxx.

ROOT::Fit::Fitter * TFractionFitter::GetFitter ( ) const

Give direct access to the underlying fitter class.

This can be used e.g. to modify parameter values or step sizes.

Definition at line 315 of file TFractionFitter.cxx.

TH1 * TFractionFitter::GetMCPrediction ( Int_t parm ) const

Return the adjusted MC template (Aji) for template (parm).

Note that the (Aji) times fractions only sum to the total prediction of the fit if all weights are 1. Note also that the histogram is managed by the TFractionFitter class, so the returned pointer will be invalid if the class is deleted

Definition at line 955 of file TFractionFitter.cxx.

Int_t TFractionFitter::GetNDF ( ) const

return the number of degrees of freedom in the fit the fNDF parameter has been previously computed during a fit.

The number of degrees of freedom corresponds to the number of points used in the fit minus the number of templates.

Definition at line 888 of file TFractionFitter.cxx.

TH1 * TFractionFitter::GetPlot ( )

Return the "template prediction" corresponding to the fit result (this is not the same as the weighted sum of template distributions, as template statistical uncertainties are taken into account).

Note that the name of this histogram will simply be the same as that of the "data" histogram, prefixed with the string "Fraction fit to hist: ". Note also that the histogram is managed by the TFractionFitter class, so the returned pointer will be invalid if the class is deleted

Definition at line 617 of file TFractionFitter.cxx.

Referenced by ComputeChisquareLambda().

Double_t TFractionFitter::GetProb ( ) const

return the fit probability

Definition at line 897 of file TFractionFitter.cxx.

void TFractionFitter::GetRanges	(	Int_t &	minX,
		Int_t &	maxX,
		Int_t &	minY,
		Int_t &	maxY,
		Int_t &	minZ,
		Int_t &	maxZ
	)		const

private

Used internally to obtain the bin ranges according to the dimensionality of the histogram and the limits set by hand.

Definition at line 635 of file TFractionFitter.cxx.

Referenced by CheckConsistency(), ComputeChisquareLambda(), and ComputeFCN().

void TFractionFitter::GetResult	(	Int_t	parm,
		Double_t &	value,
		Double_t &	error
	)		const

Obtain the fit result for parameter <parm> (the parameter numbering follows that of the input template vector).

Definition at line 598 of file TFractionFitter.cxx.

void TFractionFitter::IncludeBin ( Int_t bin )

Include the given bin in the fit, if it was excluded before using ExcludeBin().

The bin numbering to be used is that of TH1::GetBin().

Definition at line 431 of file TFractionFitter.cxx.

bool TFractionFitter::IsExcluded ( Int_t bin ) const

private

Function for internal use, checking whether the given bin is excluded from the fit or not.

Definition at line 448 of file TFractionFitter.cxx.

Referenced by CheckConsistency(), ComputeChisquareLambda(), and ComputeFCN().

void TFractionFitter::ReleaseRangeX ( )

Release restrictions on the X range of the histogram to be used in the fit.

Definition at line 346 of file TFractionFitter.cxx.

void TFractionFitter::ReleaseRangeY ( )

Release restrictions on the Y range of the histogram to be used in the fit.

Definition at line 374 of file TFractionFitter.cxx.

void TFractionFitter::ReleaseRangeZ ( )

Release restrictions on the Z range of the histogram to be used in the fit.

Definition at line 404 of file TFractionFitter.cxx.

void TFractionFitter::SetData ( TH1 * data )

Change the histogram to be fitted to.

Notes:

Parameter constraints and settings are retained from a possible previous fit.
Modifying the dimension or number of bins results in an error (in this case rather instantiate a new TFractionFitter object)

Definition at line 267 of file TFractionFitter.cxx.

void TFractionFitter::SetMC	(	Int_t	parm,
		TH1 *	MC
	)

Change the histogram for template number <parm>.

Notes:

Parameter constraints and settings are retained from a possible previous fit.
Modifying the dimension or number of bins results in an error (in this case rather instantiate a new TFractionFitter object)

Definition at line 279 of file TFractionFitter.cxx.

void TFractionFitter::SetRangeX	(	Int_t	low,
		Int_t	high
	)

Set the X range of the histogram to be used in the fit.

Use ReleaseRangeX() to go back to fitting the full histogram. The consistency check ensures that no empty fit range occurs (and also recomputes the bin content integrals).

Parameters

[in]	low	lower X bin number
[in]	high	upper X bin number

Definition at line 337 of file TFractionFitter.cxx.

void TFractionFitter::SetRangeY	(	Int_t	low,
		Int_t	high
	)

Set the Y range of the histogram to be used in the fit (2D or 3D histograms only).

Use ReleaseRangeY() to go back to fitting the full histogram. The consistency check ensures that no empty fit range occurs (and also recomputes the bin content integrals).

Parameters

[in]	low	lower X bin number
[in]	high	upper X bin number

Definition at line 360 of file TFractionFitter.cxx.

void TFractionFitter::SetRangeZ	(	Int_t	low,
		Int_t	high
	)

Set the Z range of the histogram to be used in the fit (3D histograms only).

Use ReleaseRangeY() to go back to fitting the full histogram. The consistency check ensures that no empty fit range occurs (and also recomputes the bin content integrals).

Parameters

[in]	low	lower X bin number
[in]	high	upper X bin number

Definition at line 389 of file TFractionFitter.cxx.

void TFractionFitter::SetWeight	(	Int_t	parm,
		TH1 *	weight
	)

Set bin by bin weights for template number <parm> (the parameter numbering follows that of the input template vector).

Weights can be "unset" by passing a null pointer. Consistency of the weights histogram with the data histogram is checked at this point, and an error in case of problems.

Definition at line 294 of file TFractionFitter.cxx.

void TFractionFitter::UnConstrain ( Int_t parm )

Remove the constraints on the possible values of parameter <parm>.

Definition at line 468 of file TFractionFitter.cxx.