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 27 of file TFractionFitter.h.

Public Member Functions
	TFractionFitter ()
	TFractionFitter default constructor. More...

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

virtual	~TFractionFitter ()
	TFractionFitter default destructor. 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	ErrorAnalysis (Double_t UP)
	Set UP to the given value (see class TMinuit), and perform a MINOS minimisation. More...

Double_t	EvaluateFCN (const Double_t *par)

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

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

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

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

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

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	GetProb () const
	return the fit probability 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...

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

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

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

void	ReleaseRangeZ ()
	Release restrictions on the Z range of the histogram to be used in the fit. 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	SetRangeX (Int_t low, Int_t high)
	Set 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	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	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...

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

Public Member Functions inherited from TObject
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virtual void	Error (const char method, const char msgfmt,...) const
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virtual void	Execute (const char method, const char params, Int_t *error=0)
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	Returns kTRUE if object inherits from class "classname". More...

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void	InvertBit (UInt_t f)

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

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virtual Bool_t	IsSortable () const

R__ALWAYS_INLINE Bool_t	IsZombie () const

virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout. 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...

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

void *	operator new[] (size_t sz)

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

TObject &	operator= (const TObject &rhs)
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virtual void	Pop ()
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void	ResetBit (UInt_t f)

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...

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)

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	SysError (const char method, const char msgfmt,...) const
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R__ALWAYS_INLINE Bool_t	TestBit (UInt_t f) const

Int_t	TestBits (UInt_t f) const

virtual void	UseCurrentStyle ()
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Protected Attributes
TObjArray	fAji

Double_t	fChisquare

TH1 *	fData

std::vector< Int_t >	fExcludedBins

Bool_t	fFitDone

ROOT::Fit::Fitter *	fFractionFitter

Double_t *	fFractions

Int_t	fHighLimitX

Int_t	fHighLimitY

Int_t	fHighLimitZ

Double_t	fIntegralData

Double_t *	fIntegralMCs

Int_t	fLowLimitX

Int_t	fLowLimitY

Int_t	fLowLimitZ

TObjArray	fMCs

Int_t	fNDF

Int_t	fNpar

Int_t	fNpfits

TH1 *	fPlot

TObjArray	fWeights

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

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

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

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

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	{ kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000, kBitMask = 0x00ffffff }

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

enum	EDeprecatedStatusBits { kObjInCanvas = BIT(3) }

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

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	Get status of object stat flag. More...

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	Set destructor only flag. More...

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

void	MakeZombie ()

#include <TFractionFitter.h>

Inheritance diagram for TFractionFitter:

[legend]

Constructor & Destructor Documentation

◆ TFractionFitter() [1/2]

TFractionFitter::TFractionFitter ( )

TFractionFitter default constructor.

Definition at line 162 of file TFractionFitter.cxx.

◆ TFractionFitter() [2/2]

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 192 of file TFractionFitter.cxx.

◆ ~TFractionFitter()

TFractionFitter::~TFractionFitter ( )

virtual

TFractionFitter default destructor.

Definition at line 254 of file TFractionFitter.cxx.

Member Function Documentation

◆ CheckConsistency()

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 481 of file TFractionFitter.cxx.

◆ CheckParNo()

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 324 of file TFractionFitter.cxx.

◆ ComputeChisquareLambda()

void TFractionFitter::ComputeChisquareLambda ( )

private

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

Definition at line 909 of file TFractionFitter.cxx.

◆ ComputeFCN()

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

private

Used internally to compute the likelihood value.

Definition at line 661 of file TFractionFitter.cxx.

◆ Constrain()

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 460 of file TFractionFitter.cxx.

◆ ErrorAnalysis()

void TFractionFitter::ErrorAnalysis ( Double_t UP )

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

Definition at line 580 of file TFractionFitter.cxx.

◆ EvaluateFCN()

Double_t TFractionFitter::EvaluateFCN ( const Double_t * par )

inline

Definition at line 66 of file TFractionFitter.h.

◆ ExcludeBin()

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 415 of file TFractionFitter.cxx.

◆ FindPrediction()

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 752 of file TFractionFitter.cxx.

◆ Fit()

TFitResultPtr TFractionFitter::Fit ( )

Perform the fit with the default UP value.

The value returned is the minimisation status.

Definition at line 550 of file TFractionFitter.cxx.

◆ GetChisquare()

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 878 of file TFractionFitter.cxx.

◆ GetFitter()

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 316 of file TFractionFitter.cxx.

◆ GetMCPrediction()

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 956 of file TFractionFitter.cxx.

◆ GetNDF()

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 889 of file TFractionFitter.cxx.

◆ GetPlot()

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 618 of file TFractionFitter.cxx.

◆ GetProb()

Double_t TFractionFitter::GetProb ( ) const

return the fit probability

Definition at line 898 of file TFractionFitter.cxx.

◆ GetRanges()

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 636 of file TFractionFitter.cxx.

◆ GetResult()

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 599 of file TFractionFitter.cxx.

◆ IncludeBin()

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 432 of file TFractionFitter.cxx.

◆ IsExcluded()

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 449 of file TFractionFitter.cxx.

◆ ReleaseRangeX()

void TFractionFitter::ReleaseRangeX ( )

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

Definition at line 347 of file TFractionFitter.cxx.

◆ ReleaseRangeY()

void TFractionFitter::ReleaseRangeY ( )

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

Definition at line 375 of file TFractionFitter.cxx.

◆ ReleaseRangeZ()

void TFractionFitter::ReleaseRangeZ ( )

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

Definition at line 405 of file TFractionFitter.cxx.

◆ SetData()

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 268 of file TFractionFitter.cxx.

◆ SetMC()

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 280 of file TFractionFitter.cxx.

◆ SetRangeX()

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 338 of file TFractionFitter.cxx.

◆ SetRangeY()

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 361 of file TFractionFitter.cxx.

◆ SetRangeZ()

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 390 of file TFractionFitter.cxx.

◆ SetWeight()

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 295 of file TFractionFitter.cxx.

◆ UnConstrain()

void TFractionFitter::UnConstrain ( Int_t parm )

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

Definition at line 469 of file TFractionFitter.cxx.

Member Data Documentation

◆ fAji

TObjArray TFractionFitter::fAji

protected

Definition at line 96 of file TFractionFitter.h.

◆ fChisquare

Double_t TFractionFitter::fChisquare

protected

Definition at line 94 of file TFractionFitter.h.

◆ fData

TH1* TFractionFitter::fData

protected

Definition at line 99 of file TFractionFitter.h.

◆ fExcludedBins

std::vector<Int_t> TFractionFitter::fExcludedBins

protected

Definition at line 90 of file TFractionFitter.h.

◆ fFitDone

Bool_t TFractionFitter::fFitDone

protected

Definition at line 83 of file TFractionFitter.h.

◆ fFractionFitter

ROOT::Fit::Fitter* TFractionFitter::fFractionFitter

protected

Definition at line 106 of file TFractionFitter.h.

◆ fFractions

Double_t* TFractionFitter::fFractions

protected

Definition at line 104 of file TFractionFitter.h.

◆ fHighLimitX

Int_t TFractionFitter::fHighLimitX

protected

Definition at line 85 of file TFractionFitter.h.

◆ fHighLimitY

Int_t TFractionFitter::fHighLimitY

protected

Definition at line 87 of file TFractionFitter.h.

◆ fHighLimitZ

Int_t TFractionFitter::fHighLimitZ

protected

Definition at line 89 of file TFractionFitter.h.

◆ fIntegralData

Double_t TFractionFitter::fIntegralData

protected

Definition at line 102 of file TFractionFitter.h.

◆ fIntegralMCs

Double_t* TFractionFitter::fIntegralMCs

protected

Definition at line 103 of file TFractionFitter.h.

◆ fLowLimitX

Int_t TFractionFitter::fLowLimitX

protected

Definition at line 84 of file TFractionFitter.h.

◆ fLowLimitY

Int_t TFractionFitter::fLowLimitY

protected

Definition at line 86 of file TFractionFitter.h.

◆ fLowLimitZ

Int_t TFractionFitter::fLowLimitZ

protected

Definition at line 88 of file TFractionFitter.h.

◆ fMCs

TObjArray TFractionFitter::fMCs

protected

Definition at line 100 of file TFractionFitter.h.

◆ fNDF

Int_t TFractionFitter::fNDF

protected

Definition at line 93 of file TFractionFitter.h.

◆ fNpar

Int_t TFractionFitter::fNpar

protected

Definition at line 108 of file TFractionFitter.h.

◆ fNpfits

Int_t TFractionFitter::fNpfits

protected

Definition at line 92 of file TFractionFitter.h.

◆ fPlot

TH1* TFractionFitter::fPlot

protected

Definition at line 105 of file TFractionFitter.h.

◆ fWeights

TObjArray TFractionFitter::fWeights

protected

Definition at line 101 of file TFractionFitter.h.

Libraries for TFractionFitter:

[legend]

Assumptions

Instantiation

Applying constraints

Setting parameter values

Restricting the fit range

Weights histograms

Obtaining fit results

Using different histograms

Errors

Public Member Functions

Protected Attributes

Private Member Functions

Additional Inherited Members

Constructor & Destructor Documentation

◆ TFractionFitter() [1/2]

◆ TFractionFitter() [2/2]

◆ ~TFractionFitter()

Member Function Documentation

◆ CheckConsistency()

◆ CheckParNo()

◆ ComputeChisquareLambda()

◆ ComputeFCN()

◆ Constrain()

◆ ErrorAnalysis()

◆ EvaluateFCN()

◆ ExcludeBin()

◆ FindPrediction()

◆ Fit()

◆ GetChisquare()

◆ GetFitter()

◆ GetMCPrediction()

◆ GetNDF()

◆ GetPlot()

◆ GetProb()

◆ GetRanges()

◆ GetResult()

◆ IncludeBin()

◆ IsExcluded()

◆ ReleaseRangeX()

◆ ReleaseRangeY()

◆ ReleaseRangeZ()

◆ SetData()

◆ SetMC()

◆ SetRangeX()

◆ SetRangeY()

◆ SetRangeZ()

◆ SetWeight()

◆ UnConstrain()

Member Data Documentation

◆ fAji

◆ fChisquare

◆ fData

◆ fExcludedBins

◆ fFitDone

◆ fFractionFitter

◆ fFractions

◆ fHighLimitX

◆ fHighLimitY

◆ fHighLimitZ

◆ fIntegralData

◆ fIntegralMCs

◆ fLowLimitX

◆ fLowLimitY

◆ fLowLimitZ

◆ fMCs

◆ fNDF

◆ fNpar

◆ fNpfits

◆ fPlot

◆ fWeights