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

ROOT::Fit::Fitter* fitter = fit->GetFitter();

is provided for direct access to the ROOT::Fit::Fitter object. This allows to set and fix parameter values, limits and set step sizes directly via

fitter->Config().ParSettings(parameter #).Set(const std::string &name, double value, double step, double lower, double upper);

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.

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

	~TFractionFitter () override
	TFractionFitter default destructor.

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).

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

Double_t	EvaluateFCN (const Double_t *par)

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

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

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

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

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

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

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).

Double_t	GetProb () const
	return the fit probability

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).

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

TClass *	IsA () const override

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

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

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

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

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

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

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).

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

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).

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

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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

Public Member Functions inherited from TObject
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	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.

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virtual void	Clear (Option_t *="")

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	Compare abstract method.

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	Operator delete.

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Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

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

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

static Longptr_t	GetDtorOnly ()
	Return destructor only flag.

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

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

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

Protected Attributes
TObjArray	fAji
	Array of pointers to predictions of real template distributions.

Double_t	fChisquare
	Template fit chisquare.

std::vector< Int_t >	fExcludedBins
	Bins excluded from the fit.

Bool_t	fFitDone
	Flags whether a valid fit has been performed.

Int_t	fHighLimitX
	Last bin in X dimension.

Int_t	fHighLimitY
	Last bin in Y dimension.

Int_t	fHighLimitZ
	Last bin in Z dimension.

Int_t	fLowLimitX
	First bin in X dimension.

Int_t	fLowLimitY
	First bin in Y dimension.

Int_t	fLowLimitZ
	First bin in Z dimension.

Int_t	fNDF
	Number of degrees of freedom in the fit.

Int_t	fNpar
	number of fit parameters

Int_t	fNpfits
	Number of points used in the fit.

Histograms
TH1 *	fData
	Pointer to the "data" histogram to be fitted to.

TObjArray	fMCs
	Array of pointers to template histograms.

TObjArray	fWeights
	Array of pointers to corresponding weight factors (may be null)

Double_t	fIntegralData
	"data" histogram content integral over allowed fit range

Double_t *	fIntegralMCs
	Same for template histograms (weights not taken into account)

Double_t *	fFractions
	Template fractions scaled to the "data" histogram statistics.

TH1 *	fPlot
	Pointer to histogram containing summed template predictions.

ROOT::Fit::Fitter *	fFractionFitter
	Pointer to Fitter class.

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

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

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

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

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)

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.

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

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

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

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

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

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

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

void	MakeZombie ()

#include <TFractionFitter.h>

Inheritance diagram for TFractionFitter:

[legend]

Constructor & Destructor Documentation

◆ TFractionFitter() [1/2]

TFractionFitter::TFractionFitter ( )

TFractionFitter default constructor.

Definition at line 163 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 193 of file TFractionFitter.cxx.

◆ ~TFractionFitter()

TFractionFitter::~TFractionFitter ( )

override

TFractionFitter default destructor.

Definition at line 257 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 484 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 327 of file TFractionFitter.cxx.

◆ Class()

static TClass * TFractionFitter::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * TFractionFitter::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t TFractionFitter::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 112 of file TFractionFitter.h.

◆ ComputeChisquareLambda()

void TFractionFitter::ComputeChisquareLambda ( )

private

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

Definition at line 914 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 664 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 463 of file TFractionFitter.cxx.

◆ DeclFileName()

static const char * TFractionFitter::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 112 of file TFractionFitter.h.

◆ ErrorAnalysis()

void TFractionFitter::ErrorAnalysis ( Double_t UP )

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

Definition at line 583 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 418 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 757 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 553 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 883 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 319 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 961 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 894 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 621 of file TFractionFitter.cxx.

◆ GetProb()

Double_t TFractionFitter::GetProb ( ) const

return the fit probability

Definition at line 903 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 639 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 602 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 435 of file TFractionFitter.cxx.

◆ IsA()

TClass * TFractionFitter::IsA ( ) const

inlineoverridevirtual

Returns: TClass describing current object

Reimplemented from TObject.

Definition at line 112 of file TFractionFitter.h.

◆ 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 452 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 350 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 378 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 408 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 271 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 283 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 341 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 364 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 393 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 298 of file TFractionFitter.cxx.

◆ Streamer()

void TFractionFitter::Streamer ( TBuffer & R__b )

overridevirtual

Stream an object of class TObject.

Reimplemented from TObject.

◆ StreamerNVirtual()

void TFractionFitter::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 112 of file TFractionFitter.h.

◆ UnConstrain()

void TFractionFitter::UnConstrain ( Int_t parm )

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

Definition at line 472 of file TFractionFitter.cxx.

Member Data Documentation

◆ fAji

TObjArray TFractionFitter::fAji

protected

Array of pointers to predictions of real template distributions.

Definition at line 96 of file TFractionFitter.h.

◆ fChisquare

Double_t TFractionFitter::fChisquare

protected

Template fit chisquare.

Definition at line 94 of file TFractionFitter.h.

◆ fData

TH1* TFractionFitter::fData

protected

Pointer to the "data" histogram to be fitted to.

Definition at line 100 of file TFractionFitter.h.

◆ fExcludedBins

std::vector<Int_t> TFractionFitter::fExcludedBins

protected

Bins excluded from the fit.

Definition at line 90 of file TFractionFitter.h.

◆ fFitDone

Bool_t TFractionFitter::fFitDone

protected

Flags whether a valid fit has been performed.

Definition at line 83 of file TFractionFitter.h.

◆ fFractionFitter

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

protected

Pointer to Fitter class.

Definition at line 107 of file TFractionFitter.h.

◆ fFractions

Double_t* TFractionFitter::fFractions

protected

Template fractions scaled to the "data" histogram statistics.

Definition at line 105 of file TFractionFitter.h.

◆ fHighLimitX

Int_t TFractionFitter::fHighLimitX

protected

Last bin in X dimension.

Definition at line 85 of file TFractionFitter.h.

◆ fHighLimitY

Int_t TFractionFitter::fHighLimitY

protected

Last bin in Y dimension.

Definition at line 87 of file TFractionFitter.h.

◆ fHighLimitZ

Int_t TFractionFitter::fHighLimitZ

protected

Last bin in Z dimension.

Definition at line 89 of file TFractionFitter.h.

◆ fIntegralData

Double_t TFractionFitter::fIntegralData

protected

"data" histogram content integral over allowed fit range

Definition at line 103 of file TFractionFitter.h.

◆ fIntegralMCs

Double_t* TFractionFitter::fIntegralMCs

protected

Same for template histograms (weights not taken into account)

Definition at line 104 of file TFractionFitter.h.

◆ fLowLimitX

Int_t TFractionFitter::fLowLimitX

protected

First bin in X dimension.

Definition at line 84 of file TFractionFitter.h.

◆ fLowLimitY

Int_t TFractionFitter::fLowLimitY

protected

First bin in Y dimension.

Definition at line 86 of file TFractionFitter.h.

◆ fLowLimitZ

Int_t TFractionFitter::fLowLimitZ

protected

First bin in Z dimension.

Definition at line 88 of file TFractionFitter.h.

◆ fMCs

TObjArray TFractionFitter::fMCs

protected

Array of pointers to template histograms.

Definition at line 101 of file TFractionFitter.h.

◆ fNDF

Int_t TFractionFitter::fNDF

protected

Number of degrees of freedom in the fit.

Definition at line 93 of file TFractionFitter.h.

◆ fNpar

Int_t TFractionFitter::fNpar

protected

number of fit parameters

Definition at line 110 of file TFractionFitter.h.

◆ fNpfits

Int_t TFractionFitter::fNpfits

protected

Number of points used in the fit.

Definition at line 92 of file TFractionFitter.h.

◆ fPlot

TH1* TFractionFitter::fPlot

protected

Pointer to histogram containing summed template predictions.

Definition at line 106 of file TFractionFitter.h.

◆ fWeights

TObjArray TFractionFitter::fWeights

protected

Array of pointers to corresponding weight factors (may be null)

Definition at line 102 of file TFractionFitter.h.

Libraries for TFractionFitter:

[legend]

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

hist/hist/inc/TFractionFitter.h
hist/hist/src/TFractionFitter.cxx

Assumptions

Instantiation

Applying constraints

Setting parameter values

Restricting the fit range

Weights histograms

Obtaining fit results

Using different histograms

Errors

Public Member Functions

Static 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()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ ComputeChisquareLambda()

◆ ComputeFCN()

◆ Constrain()

◆ DeclFileName()

◆ ErrorAnalysis()

◆ EvaluateFCN()

◆ ExcludeBin()

◆ FindPrediction()

◆ Fit()

◆ GetChisquare()

◆ GetFitter()

◆ GetMCPrediction()

◆ GetNDF()

◆ GetPlot()

◆ GetProb()

◆ GetRanges()

◆ GetResult()

◆ IncludeBin()

◆ IsA()

◆ IsExcluded()

◆ ReleaseRangeX()

◆ ReleaseRangeY()

◆ ReleaseRangeZ()

◆ SetData()

◆ SetMC()

◆ SetRangeX()

◆ SetRangeY()

◆ SetRangeZ()

◆ SetWeight()

◆ Streamer()

◆ StreamerNVirtual()

◆ 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