TUnfoldDensity Class Reference

An algorithm to unfold distributions from detector to truth level.

TUnfoldDensity is used to decompose a measurement y into several sources x, given the measurement uncertainties, background b and a matrix of migrations A. The method can be applied to a large number of problems, where the measured distribution y is a linear superposition of several Monte Carlo shapes. Beyond such a simple template fit, TUnfoldDensity has an adjustable regularisation term and also supports an optional constraint on the total number of events. Background sources can be specified, with a normalisation constant and normalisation uncertainty. In addition, variants of the response matrix may be specified, these are taken to determine systematic uncertainties. Complex, multidimensional arrangements of signal and background bins are managed with the help of the class TUnfoldBinning.

If you use this software, please consider the following citation
S.Schmitt, JINST 7 (2012) T10003 [arXiv:1205.6201]
Detailed documentation and updates are available on http://www.desy.de/~sschmitt

Brief recipy to use TUnfoldSys:

• Set up binning schemes for the truth and measured distributions. The binning schemes may be coded in the XML language, for reading use TUnfoldBinningXML.
• A matrix (truth,reconstructed) is given as a two-dimensional histogram as argument to the constructor of TUnfold
• A vector of measurements is given as one-dimensional histogram using the SetInput() method
• Repeated calls to SubtractBackground() to specify background sources
• Repeated calls to AddSysError() to specify systematic uncertainties
• The unfolding is performed
  • either once with a fixed parameter tau, method DoUnfold(tau)
  • or multiple times in a scan to determine the best chouce of tau, method ScanLCurve()
  • or multiple times in a scan to determine the best chouce of tau, method ScanTau()
• Unfolding results are retrieved using various GetXXX() methods

A detailed documentation of the various GetXXX() methods to control systematic uncertainties is given with the method TUnfoldSys.

Why to use complex binning schemes

in literature on unfolding, the "standard" test case is a one-dimensional distribution without underflow or overflow bins. The migration matrix is almost diagonal.
This "standard" case is rarely realized for real problems.
Often one has to deal with multi-dimensional distributions. In addition, there are underflow and overflow bins or other background bins, possibly determined with the help of auxillary measurements.
In TUnfoldDensity, such complex binning schemes are handled with the help of the class TUnfoldBinning. For both the measurement and the truth there is a tree structure. The tree nodes may correspond to single bins (e.g. nuisance parameters) or may hold multi-dimensional distributions.
For example, the "measurement" tree could have two leaves, one for the primary distribution and one for auxillary measurements. Similarly, the "truth" tree could have two leaves, one for the signal and one for the background. Each of the leaves may then have a multi-dimensional distribution.
The class TUnfoldBinning takes care to map all bins of the "measurement" to a one-dimensional vector y. Similarly, the "truth" bins are mapped to the vector x.

How to choose the regularisation settings

In TUnfoldDensity, two methods are implemented to determine tau**2

1. ScanLcurve() locate the tau where the L-curve plot has a "kink" this function is implemented in the TUnfold class
2. ScanTau() finds the solution such that some variable (e.g. global correlation coefficient) is minimized. This function is implemented in the TUnfoldDensity class

Each of the algorithms has its own advantages and disadvantages. The algorithm (1) does not work if the input data are too similar to the MC prediction. Typical no-go cases of the L-curve scan are:

• the number of measurements is too small (e.g. ny=nx)
• the input data have no statistical fluctuations [identical MC events are used to fill the matrix of migrations and the vector y for a "closure test"]

The algorithm (2) only works if the variable does have a real minimum as a function of tau. If global correlations are minimized, the situation is as follows: The matrix of migration typically introduces negative correlations. The area constraint introduces some positive correlation. Regularisation on the "size" introduces no correlation. Regularisation on 1st or 2nd derivatives adds positive correlations.
For these reasons, "size" regularisation does not work well with the tau-scan: the higher tau, the smaller rho, but there is no minimum. As a result, large values of tau (too strong regularisation) are found. In contrast, the tau-scan is expected to work better with 1st or 2nd derivative regularisation, because at some point the negative correlations from migrations are approximately cancelled by the positive correlations from the regularisation conditions.
whichever algorithm is used, the output has to be checked:

1. The L-curve should have approximate L-shape and the final choice of tau should not be at the very edge of the scanned region
2. The scan result should have a well-defined minimum and the final choice of tau should sit right in the minimum

Definition at line 52 of file TUnfoldDensity.h.

Public Types
enum	{ kSingleKey = (1ULL << (0)) , kOverwrite = (1ULL << (1)) , kWriteDelete = (1ULL << (2)) }
enum	{   kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 ,   kBitMask = 0x00ffffff }
enum	EConstraint { kEConstraintNone =0 , kEConstraintArea =1 }
	type of extra constraint More...
enum	EDensityMode { kDensityModeNone =0 , kDensityModeBinWidth =1 , kDensityModeUser =2 , kDensityModeBinWidthAndUser =3 }
	choice of regularisation scale factors to cinstruct the matrix L More...
enum	EDeprecatedStatusBits { kObjInCanvas = (1ULL << (3)) }
enum	EHistMap { kHistMapOutputHoriz = 0 , kHistMapOutputVert = 1 }
	arrangement of axes for the response matrix (TH2 histogram) More...
enum	ERegMode {   kRegModeNone = 0 , kRegModeSize = 1 , kRegModeDerivative = 2 , kRegModeCurvature = 3 ,   kRegModeMixed = 4 }
	choice of regularisation scheme More...
enum	EScanTauMode {   kEScanTauRhoAvg =0 , kEScanTauRhoMax =1 , kEScanTauRhoAvgSys =2 , kEScanTauRhoMaxSys =3 ,   kEScanTauRhoSquareAvg =4 , kEScanTauRhoSquareAvgSys =5 }
	scan mode for correlation scan More...
enum	EStatusBits {   kCanDelete = (1ULL << (0)) , kMustCleanup = (1ULL << (3)) , kIsReferenced = (1ULL << (4)) , kHasUUID = (1ULL << (5)) ,   kCannotPick = (1ULL << (6)) , kNoContextMenu = (1ULL << (8)) , kInvalidObject = (1ULL << (13)) }
enum	ESysErrMode { kSysErrModeMatrix =0 , kSysErrModeShift =1 , kSysErrModeRelative =2 }
	type of matrix specified with AddSysError() More...

Public Member Functions
	TUnfoldDensity (const TH2 *hist_A, EHistMap histmap, ERegMode regmode=kRegModeCurvature, EConstraint constraint=kEConstraintArea, EDensityMode densityMode=kDensityModeBinWidthAndUser, const TUnfoldBinning *outputBins=nullptr, const TUnfoldBinning *inputBins=nullptr, const char *regularisationDistribution=nullptr, const char *regularisationAxisSteering="*[UOB]")
	set up response matrix A, uncorrelated uncertainties of A, regularisation scheme and binning schemes
	TUnfoldDensity (void)
	only for use by root streamer or derived classes
	~TUnfoldDensity (void) override
void	AbstractMethod (const char *method) const
	Call this function within a function that you don't want to define as purely virtual, in order not to force all users deriving from that class to implement that maybe (on their side) unused function; but at the same time, emit a run-time warning if they try to call it, telling that it is not implemented in the derived class: action must thus be taken on the user side to override it.
void	AddSysError (const TH2 *sysError, const char *name, EHistMap histmap, ESysErrMode mode)
	Specify a correlated systematic uncertainty.
virtual void	AppendPad (Option_t *option="")
	Append graphics object to current pad.
virtual void	Browse (TBrowser *b)
	Browse object. May be overridden for another default action.
ULong_t	CheckedHash ()
	Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object.
virtual const char *	ClassName () const
	Returns name of class to which the object belongs.
virtual void	Clear (Option_t *="")
virtual TObject *	Clone (const char *newname="") const
	Make a clone of an object using the Streamer facility.
virtual Int_t	Compare (const TObject *obj) const
	Compare abstract method.
virtual void	Copy (TObject &object) const
	Copy this to obj.
virtual void	Delete (Option_t *option="")
	Delete this object.
virtual Int_t	DistancetoPrimitive (Int_t px, Int_t py)
	Computes distance from point (px,py) to the object.
virtual Double_t	DoUnfold (Double_t tau)
	perform the unfolding for a given regularisation parameter tau
Double_t	DoUnfold (Double_t tau, const TH1 *hist_y, Double_t scaleBias=0.0)
	perform the unfolding for a given input and regularisation
virtual void	Draw (Option_t *option="")
	Default Draw method for all objects.
virtual void	DrawClass () const
	Draw class inheritance tree of the class to which this object belongs.
virtual TObject *	DrawClone (Option_t *option="") const
	Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1).
virtual void	Dump () const
	Dump contents of object on stdout.
virtual void	Error (const char *method, const char *msgfmt,...) const
	Issue error message.
virtual void	Execute (const char *method, const char *params, Int_t *error=nullptr)
	Execute method on this object with the given parameter string, e.g.
virtual void	Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr)
	Execute method on this object with parameters stored in the TObjArray.
virtual void	ExecuteEvent (Int_t event, Int_t px, Int_t py)
	Execute action corresponding to an event at (px,py).
virtual void	Fatal (const char *method, const char *msgfmt,...) const
	Issue fatal error message.
virtual TObject *	FindObject (const char *name) const
	Must be redefined in derived classes.
virtual TObject *	FindObject (const TObject *obj) const
	Must be redefined in derived classes.
TH1 *	GetBackground (const char *histogramName, const char *bgrSource=nullptr, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE, Int_t includeError=3) const
	retreive a background source in a new histogram
void	GetBackground (TH1 *bgr, const char *bgrSource=nullptr, const Int_t *binMap=nullptr, Int_t includeError=3, Bool_t clearHist=kTRUE) const
	get background into a histogram
TSortedList *	GetBgrSources (void) const
	Get a new list of all background sources.
void	GetBias (TH1 *bias, const Int_t *binMap=nullptr) const
	get bias vector including bias scale
TH1 *	GetBias (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE) const
	retreive bias vector as a new histogram
Double_t	GetChi2A (void) const
	get χ2A contribution determined in recent unfolding
Double_t	GetChi2L (void) const
	get χ2L contribution determined in recent unfolding
Double_t	GetChi2Sys (void)
	calculate total chi**2 including all systematic errors
TH1 *	GetDeltaSysBackgroundScale (const char *bgrSource, const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive systematic 1-sigma shift corresponding to a background scale uncertainty
Bool_t	GetDeltaSysBackgroundScale (TH1 *delta, const char *source, const Int_t *binMap=nullptr)
	correlated one-sigma shifts from background normalisation uncertainty
TH1 *	GetDeltaSysSource (const char *source, const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive a correlated systematic 1-sigma shift
Bool_t	GetDeltaSysSource (TH1 *hist_delta, const char *source, const Int_t *binMap=nullptr)
	correlated one-sigma shifts correspinding to a given systematic uncertainty
TH1 *	GetDeltaSysTau (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive1-sigma shift corresponding to the previously specified uncertainty on tau
Bool_t	GetDeltaSysTau (TH1 *delta, const Int_t *binMap=nullptr)
	correlated one-sigma shifts from shifting tau
double	GetDF (void) const
	return the effecive number of degrees of freedom See e.g.
virtual Option_t *	GetDrawOption () const
	Get option used by the graphics system to draw this object.
void	GetDXDY (TH2 *dxdy) const
	get matrix connecting input and output changes
TH2 *	GetDXDY (const char *histogramName, const char *histogramTitle=nullptr, bool useAxisBinning=true) const
	get matrix DX/DY in a new histogram
void	GetEmatrix (TH2 *ematrix, const Int_t *binMap=nullptr) const
	get output covariance matrix, possibly cumulated over several bins
TH2 *	GetEmatrixInput (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	get covariance contribution from the input uncertainties (data statistical uncertainties)
void	GetEmatrixInput (TH2 *ematrix, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	covariance matrix contribution from input measurement uncertainties
void	GetEmatrixSysBackgroundScale (TH2 *ematrix, const char *source, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	covariance contribution from background normalisation uncertainty
TH2 *	GetEmatrixSysBackgroundUncorr (const char *bgrSource, const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive covariance contribution from uncorrelated background uncertainties
void	GetEmatrixSysBackgroundUncorr (TH2 *ematrix, const char *source, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	covariance contribution from background uncorrelated uncertainty
void	GetEmatrixSysSource (TH2 *ematrix, const char *source, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	covariance contribution from a systematic variation of the response matrix
void	GetEmatrixSysTau (TH2 *ematrix, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	covariance matrix contribution from error on regularisation parameter
TH2 *	GetEmatrixSysUncorr (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive covaraince contribution from uncorrelated (statistical) uncertainties of the response matrix
void	GetEmatrixSysUncorr (TH2 *ematrix, const Int_t *binMap=nullptr, Bool_t clearEmat=kTRUE)
	Covariance contribution from uncorrelated uncertainties of the response matrix.
TH2 *	GetEmatrixTotal (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	get covariance matrix including all contributions
void	GetEmatrixTotal (TH2 *ematrix, const Int_t *binMap=nullptr)
	Get total error matrix, summing up all contributions.
Double_t	GetEpsMatrix (void) const
	get numerical accuracy for Eigenvalue analysis when inverting matrices with rank problems
void	GetFoldedOutput (TH1 *folded, const Int_t *binMap=nullptr) const
	get unfolding result on detector level
TH1 *	GetFoldedOutput (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE, Bool_t addBgr=kFALSE) const
	retreive unfolding result folded back as a new histogram
virtual const char *	GetIconName () const
	Returns mime type name of object.
void	GetInput (TH1 *inputData, const Int_t *binMap=nullptr) const
	Input vector of measurements.
TH1 *	GetInput (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE) const
	retreive input distribution in a new histogram
const TUnfoldBinning *	GetInputBinning (const char *distributionName=nullptr) const
	locate a binning node for the input (measured) quantities
void	GetInputInverseEmatrix (TH2 *ematrix)
	get inverse of the measurement's covariance matrix
void	GetL (TH2 *l) const
	get matrix of regularisation conditions
TH2 *	GetL (const char *histogramName, const char *histogramTitle=nullptr, Bool_t useAxisBinning=kTRUE)
	access matrix of regularisation conditions in a new histogram
TUnfoldBinning *	GetLBinning (void) const
	return binning scheme for regularisation conditions (matrix L)
virtual Double_t	GetLcurveX (void) const
	get value on x-axis of L-curve determined in recent unfolding
virtual Double_t	GetLcurveY (void) const
	get value on y-axis of L-curve determined in recent unfolding
void	GetLsquared (TH2 *lsquared) const
	get matrix of regularisation conditions squared
TH1 *	GetLxMinusBias (const char *histogramName, const char *histogramTitle=nullptr)
	get regularisation conditions multiplied by result vector minus bias L(x-biasScale*biasVector)
virtual const char *	GetName () const
	Returns name of object.
Int_t	GetNdf (void) const
	get number of degrees of freedom determined in recent unfolding
void	GetNormalisationVector (TH1 *s, const Int_t *binMap=nullptr) const
	histogram of truth bins, determined from suming over the response matrix
Int_t	GetNpar (void) const
	get number of truth parameters determined in recent unfolding
Int_t	GetNr (void) const
	get number of regularisation conditions
virtual char *	GetObjectInfo (Int_t px, Int_t py) const
	Returns string containing info about the object at position (px,py).
virtual Option_t *	GetOption () const
void	GetOutput (TH1 *output, const Int_t *binMap=nullptr) const
	get output distribution, possibly cumulated over several bins
TH1 *	GetOutput (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE) const
	retreive unfolding result as a new histogram
const TUnfoldBinning *	GetOutputBinning (const char *distributionName=nullptr) const
	locate a binning node for the unfolded (truth level) quantities
void	GetProbabilityMatrix (TH2 *A, EHistMap histmap) const
	get matrix of probabilities
TH2 *	GetProbabilityMatrix (const char *histogramName, const char *histogramTitle=nullptr, Bool_t useAxisBinning=kTRUE) const
	get matrix of probabilities in a new histogram
Double_t	GetRhoAvg (void) const
	get average global correlation determined in recent unfolding
Double_t	GetRhoI (TH1 *rhoi, const Int_t *binMap=nullptr, TH2 *invEmat=nullptr) const
	get global correlation coefficiencts, possibly cumulated over several bins
void	GetRhoIJ (TH2 *rhoij, const Int_t *binMap=nullptr) const
	get correlation coefficiencts, possibly cumulated over several bins
TH2 *	GetRhoIJtotal (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE)
	retreive correlation coefficients, including all uncertainties
TH1 *	GetRhoIstatbgr (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE, TH2 **ematInv=nullptr)
	retreive global correlation coefficients including input (statistical) and background uncertainties
TH1 *	GetRhoItotal (const char *histogramName, const char *histogramTitle=nullptr, const char *distributionName=nullptr, const char *projectionMode=nullptr, Bool_t useAxisBinning=kTRUE, TH2 **ematInv=nullptr)
	retreive global correlation coefficients including all uncertainty sources
void	GetRhoItotal (TH1 *rhoi, const Int_t *binMap=nullptr, TH2 *invEmat=nullptr)
	Get global correlatiocn coefficients, summing up all contributions.
Double_t	GetRhoMax (void) const
	get maximum global correlation determined in recent unfolding
virtual Double_t	GetScanVariable (Int_t mode, const char *distribution, const char *projectionMode)
	calculate the function for ScanTau()
TVectorD	GetSqrtEvEmatrix (void) const
double	GetSURE (void) const
	return Stein's unbiased risk estimator See e.g.
TSortedList *	GetSysSources (void) const
	Get a new list of all systematic uuncertainty sources.
Double_t	GetTau (void) const
	return regularisation parameter
virtual const char *	GetTitle () const
	Returns title of object.
virtual UInt_t	GetUniqueID () const
	Return the unique object id.
virtual Bool_t	HandleTimer (TTimer *timer)
	Execute action in response of a timer timing out.
virtual ULong_t	Hash () const
	Return hash value for this object.
Bool_t	HasInconsistentHash () const
	Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.
virtual void	Info (const char *method, const char *msgfmt,...) const
	Issue info message.
virtual Bool_t	InheritsFrom (const char *classname) const
	Returns kTRUE if object inherits from class "classname".
virtual Bool_t	InheritsFrom (const TClass *cl) const
	Returns kTRUE if object inherits from TClass cl.
virtual void	Inspect () const
	Dump contents of this object in a graphics canvas.
void	InvertBit (UInt_t f)
TClass *	IsA () const override
Bool_t	IsDestructed () const
	IsDestructed.
virtual Bool_t	IsEqual (const TObject *obj) const
	Default equal comparison (objects are equal if they have the same address in memory).
virtual Bool_t	IsFolder () const
	Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).
Bool_t	IsOnHeap () const
virtual Bool_t	IsSortable () const
Bool_t	IsZombie () const
virtual void	ls (Option_t *option="") const
	The ls function lists the contents of a class on stdout.
void	MayNotUse (const char *method) const
	Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary).
virtual Bool_t	Notify ()
	This method must be overridden to handle object notification (the base implementation is no-op).
void	Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
	Use this method to declare a method obsolete.
void	operator delete (void *, size_t)
	Operator delete for sized deallocation.
void	operator delete (void *ptr)
	Operator delete.
void	operator delete (void *ptr, void *vp)
	Only called by placement new when throwing an exception.
void	operator delete[] (void *, size_t)
	Operator delete [] for sized deallocation.
void	operator delete[] (void *ptr)
	Operator delete [].
void	operator delete[] (void *ptr, void *vp)
	Only called by placement new[] when throwing an exception.
void *	operator new (size_t sz)
void *	operator new (size_t sz, void *vp)
void *	operator new[] (size_t sz)
void *	operator new[] (size_t sz, void *vp)
virtual void	Paint (Option_t *option="")
	This method must be overridden if a class wants to paint itself.
virtual void	Pop ()
	Pop on object drawn in a pad to the top of the display list.
virtual void	Print (Option_t *option="") const
	This method must be overridden when a class wants to print itself.
virtual Int_t	Read (const char *name)
	Read contents of object with specified name from the current directory.
virtual void	RecursiveRemove (TObject *obj)
	Recursively remove this object from a list.
Int_t	RegularizeBins (int start, int step, int nbin, ERegMode regmode)
	add regularisation conditions for a group of bins
Int_t	RegularizeBins2D (int start_bin, int step1, int nbin1, int step2, int nbin2, ERegMode regmode)
	add regularisation conditions for 2d unfolding
Int_t	RegularizeCurvature (int left_bin, int center_bin, int right_bin, Double_t scale_left=1.0, Double_t scale_right=1.0)
	add a regularisation condition on the curvature of three truth bin
Int_t	RegularizeDerivative (int left_bin, int right_bin, Double_t scale=1.0)
	add a regularisation condition on the difference of two truth bin
void	RegularizeDistribution (ERegMode regmode, EDensityMode densityMode, const char *distribution, const char *axisSteering)
	set up regularisation conditions
Int_t	RegularizeSize (int bin, Double_t scale=1.0)
	add a regularisation condition on the magnitude of a truth bin
void	ResetBit (UInt_t f)
virtual void	SaveAs (const char *filename="", Option_t *option="") const
	Save this object in the file specified by filename.
virtual void	SavePrimitive (std::ostream &out, Option_t *option="")
	Save a primitive as a C++ statement(s) on output stream "out".
virtual Int_t	ScanLcurve (Int_t nPoint, Double_t tauMin, Double_t tauMax, TGraph **lCurve, TSpline **logTauX=nullptr, TSpline **logTauY=nullptr, TSpline **logTauCurvature=nullptr)
	scan the L curve, determine tau and unfold at the final value of tau
virtual Int_t	ScanSURE (Int_t nPoint, Double_t tauMin, Double_t tauMax, TGraph **logTauSURE=nullptr, TGraph **df_chi2A=nullptr, TGraph **lCurve=nullptr)
	minimize Stein's unbiased risk estimator "SURE" using successive calls to DoUnfold at various tau.
virtual Int_t	ScanTau (Int_t nPoint, Double_t tauMin, Double_t tauMax, TSpline **scanResult, Int_t mode=kEScanTauRhoAvg, const char *distribution=nullptr, const char *projectionMode=nullptr, TGraph **lCurvePlot=nullptr, TSpline **logTauXPlot=nullptr, TSpline **logTauYPlot=nullptr)
	scan a function wrt tau and determine the minimum
void	SetBias (const TH1 *bias)
	set bias vector
void	SetBit (UInt_t f)
void	SetBit (UInt_t f, Bool_t set)
	Set or unset the user status bits as specified in f.
void	SetConstraint (EConstraint constraint)
	set type of area constraint
virtual void	SetDrawOption (Option_t *option="")
	Set drawing option for object.
void	SetEpsMatrix (Double_t eps)
	set numerical accuracy for Eigenvalue analysis when inverting matrices with rank problems
Int_t	SetInput (const TH1 *hist_y, Double_t scaleBias=0.0, Double_t oneOverZeroError=0.0, const TH2 *hist_vyy=nullptr, const TH2 *hist_vyy_inv=nullptr) override
	Define input data for subsequent calls to DoUnfold(tau).
void	SetTauError (Double_t delta_tau)
	Specify an uncertainty on tau.
virtual void	SetUniqueID (UInt_t uid)
	Set the unique object id.
void	Streamer (TBuffer &) override
	Stream an object of class TObject.
void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
void	SubtractBackground (const TH1 *hist_bgr, const char *name, Double_t scale=1.0, Double_t scale_error=0.0)
	Specify a source of background.
virtual void	SysError (const char *method, const char *msgfmt,...) const
	Issue system error message.
Bool_t	TestBit (UInt_t f) const
Int_t	TestBits (UInt_t f) const
virtual void	UseCurrentStyle ()
	Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked.
virtual void	Warning (const char *method, const char *msgfmt,...) const
	Issue warning message.
virtual Int_t	Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0)
	Write this object to the current directory.
virtual Int_t	Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const
	Write this object to the current directory.

Static Public Member Functions
static TClass *	Class ()
static const char *	Class_Name ()
static constexpr Version_t	Class_Version ()
static const char *	DeclFileName ()
static Longptr_t	GetDtorOnly ()
	Return destructor only flag.
static Bool_t	GetObjectStat ()
	Get status of object stat flag.
static const char *	GetTUnfoldVersion (void)
	return a string describing the TUnfold version
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 Types
enum	{ kOnlyPrepStep = (1ULL << (3)) }

Protected Member Functions
void	AddMSparse (TMatrixDSparse *dest, Double_t f, const TMatrixDSparse *src) const
	add a sparse matrix, scaled by a factor, to another scaled matrix
Bool_t	AddRegularisationCondition (Int_t i0, Double_t f0, Int_t i1=-1, Double_t f1=0., Int_t i2=-1, Double_t f2=0.)
	add a row of regularisation conditions to the matrix L
Bool_t	AddRegularisationCondition (Int_t nEle, const Int_t *indices, const Double_t *rowData)
	add a row of regularisation conditions to the matrix L
void	ClearHistogram (TH1 *h, Double_t x=0.) const
	Initialize bin contents and bin errors for a given histogram.
void	ClearResults (void) override
	Clear all data members which depend on the unfolding results.
TMatrixDSparse *	CreateSparseMatrix (Int_t nrow, Int_t ncol, Int_t nele, Int_t *row, Int_t *col, Double_t *data) const
	create a sparse matrix, given the nonzero elements
void	DoBackgroundSubtraction (void)
	perform background subtraction
virtual void	DoError (int level, const char *location, const char *fmt, va_list va) const
	Interface to ErrorHandler (protected).
virtual Double_t	DoUnfold (void)
	core unfolding algorithm
void	ErrorMatrixToHist (TH2 *ematrix, const TMatrixDSparse *emat, const Int_t *binMap, Bool_t doClear) const
	add up an error matrix, also respecting the bin mapping
const TMatrixDSparse *	GetAx (void) const
	vector of folded-back result
Int_t	GetBinFromRow (int ix) const
	converts matrix row to truth histogram bin number
Double_t	GetDensityFactor (EDensityMode densityMode, Int_t iBin) const
	density correction factor for a given bin
const TMatrixDSparse *	GetDXDAM (int i) const
	matrix contributions of the derivative dx/dA
const TMatrixDSparse *	GetDXDAZ (int i) const
	vector contributions of the derivative dx/dA
const TMatrixDSparse *	GetDXDtauSquared (void) const
	vector of derivative dx/dtauSquared, using internal bin counting
const TMatrixDSparse *	GetDXDY (void) const
	matrix of derivatives dx/dy
const TMatrixDSparse *	GetE (void) const
	matrix E, using internal bin counting
const TMatrixDSparse *	GetEinv (void) const
	matrix E-1, using internal bin counting
void	GetEmatrixFromVyy (const TMatrixDSparse *vyy, TH2 *ematrix, const Int_t *binMap, Bool_t clearEmat)
	propagate an error matrix on the input vector to the unfolding result
Int_t	GetNx (void) const
	returns internal number of output (truth) matrix rows
Int_t	GetNy (void) const
	returns the number of measurement bins
TString	GetOutputBinName (Int_t iBinX) const override
	Get bin name of an outpt bin.
Double_t	GetRhoIFromMatrix (TH1 *rhoi, const TMatrixDSparse *eOrig, const Int_t *binMap, TH2 *invEmat) const
Int_t	GetRowFromBin (int ix) const
	converts truth histogram bin number to matrix row
TMatrixDSparse *	GetSummedErrorMatrixXX (void)
	determine total error matrix on the vector x
TMatrixDSparse *	GetSummedErrorMatrixYY (void)
	determine total error matrix on the vector Ax
const TMatrixDSparse *	GetVxx (void) const
	covariance matrix of the result
const TMatrixDSparse *	GetVxxInv (void) const
	inverse of covariance matrix of the result
const TMatrixDSparse *	GetVyyInv (void) const
	inverse of covariance matrix of the data y
const TMatrixD *	GetX (void) const
	vector of the unfolding result
TMatrixDSparse *	InvertMSparseSymmPos (const TMatrixDSparse *A, Int_t *rank) const
	get the inverse or pseudo-inverse of a positive, sparse matrix
void	MakeZombie ()
TMatrixDSparse *	MultiplyMSparseM (const TMatrixDSparse *a, const TMatrixD *b) const
	multiply sparse matrix and a non-sparse matrix
TMatrixDSparse *	MultiplyMSparseMSparse (const TMatrixDSparse *a, const TMatrixDSparse *b) const
	multiply two sparse matrices
TMatrixDSparse *	MultiplyMSparseMSparseTranspVector (const TMatrixDSparse *m1, const TMatrixDSparse *m2, const TMatrixTBase< Double_t > *v) const
	calculate a sparse matrix product M1*V*M2T where the diagonal matrix V is given by a vector
TMatrixDSparse *	MultiplyMSparseTranspMSparse (const TMatrixDSparse *a, const TMatrixDSparse *b) const
	multiply a transposed Sparse matrix with another Sparse matrix
virtual TMatrixDSparse *	PrepareCorrEmat (const TMatrixDSparse *m1, const TMatrixDSparse *m2, const TMatrixDSparse *dsys)
	propagate correlated systematic shift to an output vector
virtual void	PrepareSysError (void)
	Matrix calculations required to propagate systematic errors.
virtual TMatrixDSparse *	PrepareUncorrEmat (const TMatrixDSparse *m1, const TMatrixDSparse *m2)
	propagate uncorrelated systematic errors to a covariance matrix
void	RegularizeDistributionRecursive (const TUnfoldBinning *binning, ERegMode regmode, EDensityMode densityMode, const char *distribution, const char *axisSteering)
	recursively add regularisation conditions for this node and its children
void	RegularizeOneDistribution (const TUnfoldBinning *binning, ERegMode regmode, EDensityMode densityMode, const char *axisSteering)
	regularize the distribution fof the given node
void	ScaleColumnsByVector (TMatrixDSparse *m, const TMatrixTBase< Double_t > *v) const
	scale columns of a matrix by the corresponding rows of a vector
void	VectorMapToHist (TH1 *hist_delta, const TMatrixDSparse *delta, const Int_t *binMap)
	map delta to hist_delta, possibly summing up bins

Static Protected Member Functions
static void	DeleteMatrix (TMatrixD **m)
	delete matrix and invalidate pointer
static void	DeleteMatrix (TMatrixDSparse **m)
	delete sparse matrix and invalidate pointer
static void	SavePrimitiveConstructor (std::ostream &out, TClass *cl, const char *variable_name, const char *constructor_agrs="", Bool_t empty_line=kTRUE)
	Save object constructor in the output stream "out".
static void	SavePrimitiveDraw (std::ostream &out, const char *variable_name, Option_t *option=nullptr)
	Save invocation of primitive Draw() method Skipped if option contains "nodraw" string.
static TString	SavePrimitiveVector (std::ostream &out, const char *prefix, Int_t len, Double_t *arr, Int_t flag=0)
	Save array in the output stream "out" as vector.

Protected Attributes
TMatrixDSparse *	fA
	response matrix A
TMatrixD *	fAoutside
	Input: underflow/overflow bins.
TMap *	fBgrErrScaleIn
	Input: background sources correlated error.
TMap *	fBgrErrUncorrInSq
	Input: uncorr error squared from bgr sources.
TMap *	fBgrIn
	Input: size of background sources.
Double_t	fBiasScale
	scale factor for the bias
const TUnfoldBinning *	fConstInputBins
	binning scheme for the input (detector level)
const TUnfoldBinning *	fConstOutputBins
	binning scheme for the output (truth level)
EConstraint	fConstraint
	type of constraint to use for the unfolding
TMatrixD *	fDAinColRelSq
	Input: normalized column err.sq. (inp.matr.).
TMatrixDSparse *	fDAinRelSq
	Input: normalized errors from input matrix.
TMap *	fDeltaCorrAx
	Result: syst.shift from fSysIn on fAx.
TMap *	fDeltaCorrX
	Result: syst.shift from fSysIn on fX.
TMatrixDSparse *	fDeltaSysTau
	Result: systematic shift from tau.
Double_t	fDtau
	Input: error on tau.
TMatrixDSparse *	fEmatUncorrAx
	Result: syst.error from fDA2 on fAx.
TMatrixDSparse *	fEmatUncorrX
	Result: syst.error from fDA2 on fX.
TArrayI	fHistToX
	mapping of histogram bins to matrix indices
TMatrixDSparse *	fL
	regularisation conditions L
TUnfoldBinning *	fOwnedInputBins
	pointer to input binning scheme if owned by this class
TUnfoldBinning *	fOwnedOutputBins
	pointer to output binning scheme if owned by this class
ERegMode	fRegMode
	type of regularisation
TUnfoldBinning *	fRegularisationConditions
	binning scheme for the regularisation conditions
TArrayD	fSumOverY
	truth vector calculated from the non-normalized response matrix
TMap *	fSysIn
	Input: correlated errors.
Double_t	fTauSquared
	regularisation parameter tau squared
TMatrixDSparse *	fVyy
	covariance matrix Vyy corresponding to y
TMatrixDSparse *	fVyyData
	Input: error on fY prior to bgr subtraction.
TMatrixD *	fX0
	bias vector x0
TArrayI	fXToHist
	mapping of matrix indices to histogram bins
TMatrixD *	fY
	input (measured) data y
TMatrixD *	fYData
	Input: fY prior to bgr subtraction.

Private Member Functions
void	InitTUnfold (void)
	initialize data menbers, for use in constructors
void	InitTUnfoldSys (void)

Static Private Member Functions
static void	AddToTObjectTable (TObject *)
	Private helper function which will dispatch to TObjectTable::AddObj.

Private Attributes
TMatrixDSparse *	fAx
	result x folded back A*x
UInt_t	fBits
	bit field status word
Double_t	fChi2A
	chi**2 contribution from (y-Ax)Vyy-1(y-Ax)
TMatrixDSparse *	fDXDAM [2]
	matrix contribution to the of derivative dx_k/dA_ij
TMatrixDSparse *	fDXDAZ [2]
	vector contribution to the of derivative dx_k/dA_ij
TMatrixDSparse *	fDXDtauSquared
	derivative of the result wrt tau squared
TMatrixDSparse *	fDXDY
	derivative of the result wrt dx/dy
TMatrixDSparse *	fE
	matrix E
TMatrixDSparse *	fEinv
	matrix E^(-1)
Double_t	fEpsMatrix
	machine accuracy used to determine matrix rank after eigenvalue analysis
Int_t	fIgnoredBins
	number of input bins which are dropped because they have error=nullptr
Double_t	fLXsquared
	chi**2 contribution from (x-s*x0)TLTL(x-s*x0)
Int_t	fNdf
	number of degrees of freedom
Double_t	fRhoAvg
	average global correlation coefficient
Double_t	fRhoMax
	maximum global correlation coefficient
UInt_t	fUniqueID
	object unique identifier
TMatrixDSparse *	fVxx
	covariance matrix Vxx
TMatrixDSparse *	fVxxInv
	inverse of covariance matrix Vxx-1
TMatrixDSparse *	fVyyInv
	inverse of the input covariance matrix Vyy-1
TMatrixD *	fX
	unfolding result x

Static Private Attributes
static Longptr_t	fgDtorOnly = 0
	object for which to call dtor only (i.e. no delete)
static Bool_t	fgObjectStat = kTRUE
	if true keep track of objects in TObjectTable

#include <TUnfoldDensity.h>

Inheritance diagram for TUnfoldDensity:

Member Enumeration Documentation

anonymous enum

anonymous enum

protectedinherited

Enumerator

kOnlyPrepStep

Used to request that the class specific implementation of TObject::Write just prepare the objects to be ready to be written but do not actually write them into the TBuffer. This is just for example by TBufferMerger to request that the TTree inside the file calls TTree::FlushBaskets (outside of the merging lock) and TBufferMerger will later ask for the write (inside the merging lock). To take advantage of this feature the class needs to overload TObject::Write and use this enum value accordingly. (See TTree::Write and TObject::Write) Do not use, this feature will be migrate to the Merge function (See TClass and TTree::Merge)

Definition at line 106 of file TObject.h.

anonymous enum

anonymous enum

inherited

Enumerator
kSingleKey	write collection with single key
kOverwrite	overwrite existing object with same name
kWriteDelete	write object, then delete previous key with same name

Definition at line 99 of file TObject.h.

anonymous enum

anonymous enum

inherited

Enumerator
kIsOnHeap	object is on heap
kNotDeleted	object has not been deleted
kZombie	object ctor failed
kInconsistent	class overload Hash but does call RecursiveRemove in destructor
kBitMask

Definition at line 89 of file TObject.h.

EConstraint

enum TUnfold::EConstraint

inherited

type of extra constraint

Enumerator
kEConstraintNone	use no extra constraint
kEConstraintArea	enforce preservation of the area

Definition at line 113 of file TUnfold.h.

EDensityMode

enum TUnfoldDensity::EDensityMode

choice of regularisation scale factors to cinstruct the matrix L

Enumerator
kDensityModeNone	no scale factors, matrix L is similar to unity matrix
kDensityModeBinWidth	scale factors from multidimensional bin width
kDensityModeUser	scale factors from user function in TUnfoldBinning
kDensityModeBinWidthAndUser	scale factors from multidimensional bin width and user function

Definition at line 67 of file TUnfoldDensity.h.

EDeprecatedStatusBits

enum TObject::EDeprecatedStatusBits

inherited

Enumerator
kObjInCanvas	for backward compatibility only, use kMustCleanup

Definition at line 84 of file TObject.h.

EHistMap

enum TUnfold::EHistMap

inherited

arrangement of axes for the response matrix (TH2 histogram)

Enumerator
kHistMapOutputHoriz	truth level on x-axis of the response matrix
kHistMapOutputVert	truth level on y-axis of the response matrix

Definition at line 143 of file TUnfold.h.

ERegMode

enum TUnfold::ERegMode

inherited

choice of regularisation scheme

Enumerator
kRegModeNone	no regularisation, or defined later by RegularizeXXX() methods
kRegModeSize	regularise the amplitude of the output distribution
kRegModeDerivative	regularize the 1st derivative of the output distribution
kRegModeCurvature	regularize the 2nd derivative of the output distribution
kRegModeMixed	mixed regularisation pattern

Definition at line 123 of file TUnfold.h.

EScanTauMode

enum TUnfoldDensity::EScanTauMode

scan mode for correlation scan

Enumerator
kEScanTauRhoAvg	average global correlation coefficient (from TUnfold::GetRhoI())
kEScanTauRhoMax	maximum global correlation coefficient (from TUnfold::GetRhoI())
kEScanTauRhoAvgSys	average global correlation coefficient (from TUnfoldSys::GetRhoItotal())
kEScanTauRhoMaxSys	maximum global correlation coefficient (from TUnfoldSys::GetRhoItotal())
kEScanTauRhoSquareAvg	average global correlation coefficient squared (from TUnfold::GetRhoI())
kEScanTauRhoSquareAvgSys	average global correlation coefficient squared (from TUnfoldSys::GetRhoItotal())

Definition at line 109 of file TUnfoldDensity.h.

EStatusBits

enum TObject::EStatusBits

inherited

Enumerator
kCanDelete	if object in a list can be deleted
kMustCleanup	if object destructor must call RecursiveRemove()
kIsReferenced	if object is referenced by a TRef or TRefArray
kHasUUID	if object has a TUUID (its fUniqueID=UUIDNumber)
kCannotPick	if object in a pad cannot be picked
kNoContextMenu	if object does not want context menu
kInvalidObject	if object ctor succeeded but object should not be used

Definition at line 70 of file TObject.h.

ESysErrMode

enum TUnfoldSys::ESysErrMode

inherited

type of matrix specified with AddSysError()

Enumerator
kSysErrModeMatrix	matrix is an alternative to the default matrix, the errors are the difference to the original matrix
kSysErrModeShift	matrix gives the absolute shifts
kSysErrModeRelative	matrix gives the relative shifts

Definition at line 106 of file TUnfoldSys.h.

Constructor & Destructor Documentation

TUnfoldDensity() [1/2]

TUnfoldDensity::TUnfoldDensity

(

void

)

only for use by root streamer or derived classes

Definition at line 181 of file TUnfoldDensity.cxx.

TUnfoldDensity() [2/2]

TUnfoldDensity::TUnfoldDensity	(	const TH2 *	hist_A,
		EHistMap	histmap,
		ERegMode	regmode = kRegModeCurvature,
		EConstraint	constraint = kEConstraintArea,
		EDensityMode	densityMode = kDensityModeBinWidthAndUser,
		const TUnfoldBinning *	outputBins = nullptr,
		const TUnfoldBinning *	inputBins = nullptr,
		const char *	regularisationDistribution = nullptr,
		const char *	regularisationAxisSteering = "*[UOB]" )

set up response matrix A, uncorrelated uncertainties of A, regularisation scheme and binning schemes

Parameters

[in]	hist_A	matrix that describes the migrations
[in]	histmap	mapping of the histogram axes to the unfolding output
[in]	regmode	(default=kRegModeSize) global regularisation mode
[in]	constraint	(default=kEConstraintArea) type of constraint
[in]	densityMode	(default=kDensityModeBinWidthAndUser) regularisation scale factors to construct the matrix L
[in]	outputBins	(default=nullptr) binning scheme for truth (unfolding output)
[in]	inputBins	(default=nullptr) binning scheme for measurement (unfolding input)
[in]	regularisationDistribution	(default=nullptr) selectin of regularized distribution
[in]	regularisationAxisSteering	(default=nullptr) detailed regularisation steeringfor selected distribution

The parameters hist_A, histmap, constraint are explained with the TUnfoldSys constructor.
The parameters outputBins,inputBins set the binning schemes. If these arguments are zero, simple binning schemes are constructed which correspond to the axes of the histogram hist_A.
The parameters regmode, densityMode, regularisationDistribution, regularisationAxisSteering together control how the initial matrix L of regularisation conditions is constructed. as explained in RegularizeDistribution().

Definition at line 220 of file TUnfoldDensity.cxx.

~TUnfoldDensity()

TUnfoldDensity::~TUnfoldDensity ( void )

override

Definition at line 170 of file TUnfoldDensity.cxx.

Member Function Documentation

AbstractMethod()

void TObject::AbstractMethod ( const char * method ) const

inherited

Call this function within a function that you don't want to define as purely virtual, in order not to force all users deriving from that class to implement that maybe (on their side) unused function; but at the same time, emit a run-time warning if they try to call it, telling that it is not implemented in the derived class: action must thus be taken on the user side to override it.

In other word, this method acts as a "runtime purely virtual" warning instead of a "compiler purely virtual" error.

Warning

This interface is a legacy function that is no longer recommended to be used by new development code.

Note

The name "AbstractMethod" does not imply that it's an abstract method in the strict C++ sense.

Definition at line 1149 of file TObject.cxx.

AddMSparse()

void TUnfold::AddMSparse ( TMatrixDSparse * dest, Double_t f, const TMatrixDSparse * src ) const

protectedinherited

add a sparse matrix, scaled by a factor, to another scaled matrix

Parameters

[in,out]	dest	destination matrix
[in]	f	scaling factor
[in]	src	matrix to be added to dest

a replacement for (*dest) += f * (*src) which suffered from a bug in old root versions

Definition at line 915 of file TUnfold.cxx.

AddRegularisationCondition() [1/2]

Bool_t TUnfold::AddRegularisationCondition ( Int_t i0, Double_t f0, Int_t i1 = -1, Double_t f1 = 0., Int_t i2 = -1, Double_t f2 = 0. )

protectedinherited

add a row of regularisation conditions to the matrix L

Parameters

[in]	i0	truth histogram bin number
[in]	f0	entry in the matrix L, column i0
[in]	i1	truth histogram bin number
[in]	f1	entry in the matrix L, column i1
[in]	i2	truth histogram bin number
[in]	f2	entry in the matrix L, column i2

the arguments are used to form one row (k) of the matrix L, where
L_k,i0=f0 and L_k,i1=f1 and L_k,i2=f2
negative indexes i0,i1,i2 are ignored

Definition at line 1917 of file TUnfold.cxx.

AddRegularisationCondition() [2/2]

Bool_t TUnfold::AddRegularisationCondition ( Int_t nEle, const Int_t * indices, const Double_t * rowData )

protectedinherited

add a row of regularisation conditions to the matrix L

Parameters

[in]	nEle	number of valid entries in indeces and rowData
[in]	indices	column numbers of L to fill
[in]	rowData	data to fill into the new row of L

returns true if a row was added, false otherwise
A new row k is added to the matrix L, its dimension is expanded. The new elements L_ki are filled from the array rowData[] where the indices i which are taken from the array indices[].

Definition at line 1954 of file TUnfold.cxx.

AddSysError()

void TUnfoldSys::AddSysError ( const TH2 * sysError, const char * name, EHistMap histmap, ESysErrMode mode )

inherited

Specify a correlated systematic uncertainty.

Parameters

[in]	sysError	alternative matrix or matrix of absolute/relative shifts
[in]	name	identifier of the error source
[in]	histmap	mapping of the histogram axes
[in]	mode	format of the error source

sysError corresponds to a one-sigma variation. If may be given in various forms, specified by mode

• mode=kSysErrModeMatrix the histogram sysError corresponds to an alternative response matrix.
• mode=kSysErrModeShift the content of the histogram sysError are the absolute shifts of the response matrix
• mode=kSysErrModeRelative the content of the histogram sysError specifies the relative uncertainties

Internally, all three cases are transformed to the case mode=kSysErrModeMatrix.

Definition at line 291 of file TUnfoldSys.cxx.

AddToTObjectTable()

void TObject::AddToTObjectTable ( TObject * op )

staticprivateinherited

Private helper function which will dispatch to TObjectTable::AddObj.

Included here to avoid circular dependency between header files.

Definition at line 195 of file TObject.cxx.

AppendPad()

void TObject::AppendPad ( Option_t * option = "" )

virtualinherited

Append graphics object to current pad.

In case no current pad is set yet, create a default canvas with the name "c1".

Definition at line 204 of file TObject.cxx.

Browse()

void TObject::Browse ( TBrowser * b )

virtualinherited

Browse object. May be overridden for another default action.

Reimplemented in RooPlot, ROOT::Experimental::XRooFit::xRooNode, ROOT::Internal::THnBaseBrowsable, TApplicationRemote, TASImage, TAxis3D, TBaseClass, TBranch, TBranchClones, TBranchElement, TBranchObject, TBranchSTL, TBrowserObject, TCanvas, TChain, TClass, TCollection, TCollectionPropertyBrowsable, TDatabasePDG, TDirectory, TDirectoryFile, TEfficiency, TF1, TFolder, TGenerator, TGeoManager, TGeometry, TGeoNode, TGeoOverlap, TGeoTrack, TGeoVolume, TGraph2D, TGraph, TH1, THbookBranch, THbookFile, THbookKey, THnBase, THStack, TKey, TKeyMapFile, TLeaf, TMacro, TMapFile, TMultiDimFit, TMultiGraph, TNode, TNtuple, TNtupleD, TPad, TPair, TParticleClassPDG, TPrincipal, TRecorder, TRemoteObject, TROOT, TRootIconList, TSPlot, TStyle, TSystemDirectory, TSystemFile, TTask, TTree, TTreePerfStats, and TVirtualBranchBrowsable.

Definition at line 218 of file TObject.cxx.

CheckedHash()

ULong_t TObject::CheckedHash ( )

inlineinherited

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

The intent is for this routine to be called instead of directly calling the function Hash during "insert" operations. See TObject::HasInconsistenTObjectHash();

(*) The setup is consistent when all classes in the class hierarchy that overload TObject::Hash do call ROOT::CallRecursiveRemoveIfNeeded in their destructor. i.e. it is safe to call the Hash virtual function during the RecursiveRemove operation.

Definition at line 332 of file TObject.h.

Class()

TClass * TUnfoldDensity::Class ( )

static

Returns

TClass describing this class

Class_Name()

const char * TUnfoldDensity::Class_Name ( )

static

Returns

Name of this class

Class_Version()

constexpr Version_t TUnfoldDensity::Class_Version ( )

inlinestaticconstexpr

Returns

Version of this class

Definition at line 205 of file TUnfoldDensity.h.

ClassName()

const char * TObject::ClassName ( ) const

virtualinherited

Returns name of class to which the object belongs.

Definition at line 227 of file TObject.cxx.

Clear()

virtual void TObject::Clear ( Option_t * = "" )

inlinevirtualinherited

Reimplemented in JetEvent, RooLinkedList, ROOT::TSchemaRule, ROOT::v5::TFormula, TBackCompFitter, TBits, TBranchRef, TBtree, TCanvas, TClonesArray, TCollection, TDictAttributeMap, TDirectory, TEventList, TFitter, TFolder, TFormula, TFumili, TGeoCombiTrans, TGeoGenTrans, TGeoHMatrix, TGeoRotation, TGHtml, TGraph2D, TGTextEdit, TGTextEntry, TGTextView, TGView, THashList, THashTable, TLegend, TLinearFitter, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TMap, TMatrixT< Element >, TMatrixT< AReal >, TMatrixT< Double_t >, TMatrixT< Float_t >, TMatrixTBase< Element >, TMatrixTBase< Double_t >, TMatrixTBase< Float_t >, TMatrixTSparse< Element >, TMatrixTSparse< Double_t >, TMatrixTSparse< Float_t >, TMatrixTSym< Element >, TMatrixTSym< Double_t >, TMatrixTSym< Float_t >, TMrbSubevent_Caen, TMultiDimFit, TMVA::MinuitWrapper, TMVA::ResultsClassification, TMVA::ResultsMulticlass, TMVA::ResultsRegression, TNamed, TNotifyLinkBase, TObjArray, TOrdCollection, TPad, TPaveText, TPrincipal, TProcessID, TRefArray, TRefTable, TStreamerInfo, TTask, TUsrHitBuffer, TVectorT< Element >, TVectorT< Double_t >, TVectorT< Float_t >, TViewPubDataMembers, TViewPubFunctions, TVirtualFitter, TVirtualPad, and TVirtualStreamerInfo.

Definition at line 127 of file TObject.h.

ClearHistogram()

void TUnfold::ClearHistogram ( TH1 * h, Double_t x = 0. ) const

protectedinherited

Initialize bin contents and bin errors for a given histogram.

Parameters

[out]	h	histogram
[in]	x	new histogram content

all histgram errors are set to zero, all contents are set to x

Definition at line 3680 of file TUnfold.cxx.

ClearResults()

void TUnfoldSys::ClearResults ( void )

overrideprotectedvirtualinherited

Clear all data members which depend on the unfolding results.

Reimplemented from TUnfold.

Definition at line 649 of file TUnfoldSys.cxx.

Clone()

TObject * TObject::Clone ( const char * newname = "" ) const

virtualinherited

Make a clone of an object using the Streamer facility.

If the object derives from TNamed, this function is called by TNamed::Clone. TNamed::Clone uses the optional argument to set a new name to the newly created object.

If the object class has a DirectoryAutoAdd function, it will be called at the end of the function with the parameter gDirectory. This usually means that the object will be appended to the current ROOT directory.

Reimplemented in RooAbsArg, RooAbsBinning, RooAbsCollection, RooAbsStudy, RooCatType, RooCmdArg, RooDataHist, RooDataSet, RooFitResult, RooLinkedList, RooStats::HypoTestResult, RooStats::ModelConfig, RooStudyPackage, RooTemplateProxy< T >, RooTemplateProxy< const RooHistFunc >, RooTemplateProxy< RooAbsCategory >, RooTemplateProxy< RooAbsPdf >, RooTemplateProxy< RooAbsReal >, RooTemplateProxy< RooAbsRealLValue >, RooTemplateProxy< RooMultiCategory >, RooTemplateProxy< RooRealVar >, RooWorkspace, TASImage, TChainIndex, TClass, TCollection, TF1, TFunction, TFunctionTemplate, TH1, TImage, TMethod, TMethodCall, TMinuit, TMVA::MinuitWrapper, TNamed, TStreamerInfo, and TTreeIndex.

Definition at line 243 of file TObject.cxx.

Compare()

Int_t TObject::Compare ( const TObject * obj ) const

virtualinherited

Compare abstract method.

Must be overridden if a class wants to be able to compare itself with other objects. Must return -1 if this is smaller than obj, 0 if objects are equal and 1 if this is larger than obj.

Reimplemented in RooAbsArg, RooDouble, TCollection, TEnvRec, TFileInfo, TGeoBranchArray, TGeoOverlap, TGFSFrameElement, TGLBFrameElement, TNamed, TObjString, TParameter< AParamType >, TParameter< Long64_t >, TStructNode, TStructNodeProperty, and TUrl.

Definition at line 258 of file TObject.cxx.

Copy()

void TObject::Copy ( TObject & object ) const

virtualinherited

Copy this to obj.

Reimplemented in ROOT::v5::TFormula, TArc, TArrow, TAxis3D, TAxis, TBox, TColor, TCrown, TDirectory, TDirectoryFile, TEllipse, TF12, TF1, TF1AbsComposition, TF1Convolution, TF1NormSum, TF2, TF3, TFile, TFolder, TFormula, TFrame, TGTextEdit, TGTextView, TH1, TH1C, TH1D, TH1F, TH1I, TH1L, TH1S, TH2, TH2C, TH2D, TH2F, TH2I, TH2L, TH2Poly, TH2S, TH3, TH3C, TH3D, TH3F, TH3I, TH3L, TH3S, THelix, TLatex, TLegend, TLegendEntry, TLine, TMarker, TMathText, TNamed, TPaletteAxis, TPave, TPaveClass, TPaveLabel, TPieSlice, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TProfile2D, TProfile3D, TProfile, TStyle, TSystemDirectory, TSystemFile, TText, TWbox, and TXTRU.

Definition at line 159 of file TObject.cxx.

CreateSparseMatrix()

TMatrixDSparse * TUnfold::CreateSparseMatrix ( Int_t nrow, Int_t ncol, Int_t nel, Int_t * row, Int_t * col, Double_t * data ) const

protectedinherited

create a sparse matrix, given the nonzero elements

Parameters

[in]	nrow	number of rows
[in]	ncol	number of columns
[in]	nel	number of non-zero elements
[in]	row	row indexes of non-zero elements
[in]	col	column indexes of non-zero elements
[in]	data	non-zero elements data

return pointer to a new sparse matrix

shortcut to new TMatrixDSparse() followed by SetMatrixArray()

Definition at line 578 of file TUnfold.cxx.

DeclFileName()

const char * TUnfoldDensity::DeclFileName ( )

inlinestatic

Returns

Name of the file containing the class declaration

Definition at line 205 of file TUnfoldDensity.h.

Delete()

void TObject::Delete ( Option_t * option = "" )

virtualinherited

Delete this object.

Typically called as a command via the interpreter. Normally use "delete" operator when object has been allocated on the heap.

Reimplemented in RooLinkedList, TAxis, TBtree, TCanvas, TClonesArray, TCollection, TDirectory, TDirectoryFile, TExMap, TFile, TGFrame, TGItemContext, TGTextEdit, THashList, THashTable, TKey, TKeySQL, TKeyXML, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TMap, TMVA::Results, TObjArray, TObjectTable, TOrdCollection, TProtoClass, TQCommand, TRefArray, TSystemDirectory, TSystemFile, TThread, TTree, TTreeViewer, TViewPubDataMembers, and TViewPubFunctions.

Definition at line 268 of file TObject.cxx.

DeleteMatrix() [1/2]

void TUnfold::DeleteMatrix ( TMatrixD ** m )

staticprotectedinherited

delete matrix and invalidate pointer

Parameters

[in,out]

m

pointer to a matrix-pointer

if the matrix pointer os non-zero, thematrix id deleted. The matrox pointer is set to zero.

Definition at line 188 of file TUnfold.cxx.

DeleteMatrix() [2/2]

void TUnfold::DeleteMatrix ( TMatrixDSparse ** m )

staticprotectedinherited

delete sparse matrix and invalidate pointer

Parameters

[in,out]

m

pointer to a matrix-pointer

if the matrix pointer os non-zero, thematrix id deleted. The matrox pointer is set to zero.

Definition at line 200 of file TUnfold.cxx.

DistancetoPrimitive()

Int_t TObject::DistancetoPrimitive ( Int_t px, Int_t py )

virtualinherited

Computes distance from point (px,py) to the object.

This member function must be implemented for each graphics primitive. This default function returns a big number (999999).

Reimplemented in TASImage, TAxis3D, TAxis, TBox, TBRIK, TColorWheel, TCrown, TCurlyArc, TCurlyLine, TDiamond, TEfficiency, TEllipse, TF1, TF2, TF3, TFileDrawMap, TGenerator, TGeoBBox, TGeoCompositeShape, TGeoCone, TGeoConeSeg, TGeoEltu, TGeoHalfSpace, TGeoHype, TGeoNode, TGeoOverlap, TGeoParaboloid, TGeoPcon, TGeoPgon, TGeoScaledShape, TGeoShape, TGeoShapeAssembly, TGeoSphere, TGeoTessellated, TGeoTorus, TGeoTrack, TGeoTube, TGeoTubeSeg, TGeoVGShape, TGeoVolume, TGeoXtru, TGL5DDataSet, TGLHistPainter, TGLParametricEquation, TGLScenePad, TGLTH3Composition, TGLViewer, TGraph2D, TGraph, TGraphEdge, TGraphNode, TGraphPolargram, TH1, THistPainter, THStack, TLine, TMarker3DBox, TMarker, TMultiGraph, TNode, TPad, TPaletteAxis, TParallelCoord, TParallelCoordRange, TParallelCoordVar, TParticle, TPave, TPCON, TPie, TPieSlice, TPoints3DABC, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TPrimary, TScatter2D, TScatter, TSPHE, TSpider, TSpline, TStyle, TText, TTreePerfStats, TTUBE, TTUBS, TVirtualHistPainter, and TXTRU.

Definition at line 284 of file TObject.cxx.

DoBackgroundSubtraction()

void TUnfoldSys::DoBackgroundSubtraction ( void )

protectedinherited

perform background subtraction

This prepares the data members for the base class TUnfold, such that the background is properly taken into account.

Definition at line 376 of file TUnfoldSys.cxx.

DoError()

void TObject::DoError ( int level, const char * location, const char * fmt, va_list va ) const

protectedvirtualinherited

Interface to ErrorHandler (protected).

Reimplemented in TThread, and TTreeViewer.

Definition at line 1059 of file TObject.cxx.

DoUnfold() [1/3]

Double_t TUnfold::DoUnfold ( Double_t tau )

virtualinherited

perform the unfolding for a given regularisation parameter tau

Parameters

[in]

tau

regularisation parameter

this method sets tau and then calls the core unfolding algorithm

Definition at line 2491 of file TUnfold.cxx.

DoUnfold() [2/3]

Double_t TUnfold::DoUnfold ( Double_t tau_reg, const TH1 * input, Double_t scaleBias = 0.0 )

inherited

perform the unfolding for a given input and regularisation

Parameters

[in]	tau_reg	regularisation parameter
[in]	input	input distribution with uncertainties
[in]	scaleBias	(default=0.0) scale factor applied to the bias

This is a shortcut for { SetInput(input,scaleBias); DoUnfold(tau); }

Definition at line 2235 of file TUnfold.cxx.

DoUnfold() [3/3]

Double_t TUnfold::DoUnfold ( void )

protectedvirtualinherited

core unfolding algorithm

Definition at line 246 of file TUnfold.cxx.

Draw()

void TObject::Draw ( Option_t * option = "" )

virtualinherited

Default Draw method for all objects.

Reimplemented in RooAbsData, RooPlot, RooStats::HypoTestInverterPlot, RooStats::SamplingDistPlot, ROOT::Experimental::XRooFit::xRooNLLVar::xRooHypoPoint, ROOT::Experimental::XRooFit::xRooNLLVar::xRooHypoSpace, ROOT::Experimental::XRooFit::xRooNode, ROOT::RGeoPainter, TArrow, TASImage, TBox, TBrowser, TButton, TCanvas, TChain, TClass, TClassTree, TCollection, TColorWheel, TDiamond, TDirectory, TEfficiency, TEllipse, TEveGeoNode, TEveGeoTopNode, TF1, TF2, TF3, TFile, TFITSHDU, TFrame, TGenerator, TGeoBatemanSol, TGeometry, TGeoNode, TGeoOverlap, TGeoPainter, TGeoParallelWorld, TGeoPhysicalNode, TGeoPolygon, TGeoShape, TGeoTrack, TGeoVGShape, TGeoVolume, TGItemContext, TGListTree, TGPicture, TGraph2D, TGraph, TGraphPolar, TGraphPolargram, TGraphStruct, TGraphTime, TH1, THelix, THStack, TLegend, TMarker, TMatrixTBase< Element >, TMatrixTBase< Double_t >, TMatrixTBase< Float_t >, TMultiDimFit, TMultiGraph, TMultiLayerPerceptron, TNode, TNodeDiv, TPad, TParallelCoord, TParallelCoordRange, TParallelCoordVar, TPave, TPaveLabel, TPavesText, TPaveText, TPie, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TRatioPlot, TSpider, TSpline, TStructViewer, TStructViewerGUI, TTree, TTreePerfStats, TVectorT< Element >, TVectorT< Double_t >, TVectorT< Float_t >, TVirtualPad, and TWbox.

Definition at line 293 of file TObject.cxx.

DrawClass()

void TObject::DrawClass ( ) const

virtualinherited

Draw class inheritance tree of the class to which this object belongs.

If a class B inherits from a class A, description of B is drawn on the right side of description of A. Member functions overridden by B are shown in class A with a blue line crossing-out the corresponding member function. The following picture is the class inheritance tree of class TPaveLabel:

Reimplemented in TGFrame, TSystemDirectory, and TSystemFile.

Definition at line 308 of file TObject.cxx.

DrawClone()

TObject * TObject::DrawClone ( Option_t * option = "" ) const

virtualinherited

Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1).

If pad was not selected - gPad will be used.

Note

For histograms, use the more specialised TH1::DrawCopy().

Reimplemented in TAxis, TCanvas, TGFrame, TSystemDirectory, and TSystemFile.

Definition at line 319 of file TObject.cxx.

Dump()

void TObject::Dump ( ) const

virtualinherited

Dump contents of object on stdout.

Using the information in the object dictionary (class TClass) each data member is interpreted. If a data member is a pointer, the pointer value is printed

The following output is the Dump of a TArrow object:

fAngle                   0           Arrow opening angle (degrees)
fArrowSize               0.2         Arrow Size
fOption.*fData
fX1                      0.1         X of 1st point
fY1                      0.15        Y of 1st point
fX2                      0.67        X of 2nd point
fY2                      0.83        Y of 2nd point
fUniqueID                0           object unique identifier
fBits                    50331648    bit field status word
fLineColor               1           line color
fLineStyle               1           line style
fLineWidth               1           line width
fFillColor               19          fill area color
fFillStyle               1001        fill area style

Reimplemented in TClass, TCollection, TGFrame, TGPack, and TSystemFile.

Definition at line 367 of file TObject.cxx.

Error()

void TObject::Error ( const char * location, const char * fmt, ... ) const

virtualinherited

Issue error message.

Use "location" to specify the method where the error occurred. Accepts standard printf formatting arguments.

Reimplemented in TFitResult.

Definition at line 1098 of file TObject.cxx.

ErrorMatrixToHist()

void TUnfold::ErrorMatrixToHist ( TH2 * ematrix, const TMatrixDSparse * emat, const Int_t * binMap, Bool_t doClear ) const

protectedinherited

add up an error matrix, also respecting the bin mapping

Parameters

[in,out]	ematrix	error matrix histogram
[in]	emat	error matrix stored with internal mapping (member fXToHist)
[in]	binMap	mapping of histogram bins
[in]	doClear	if true, ematrix is cleared prior to adding elements of emat to it.

the array binMap is explained with the method GetOutput(). The matrix emat must have dimension NxN where N=fXToHist.size() The flag doClear may be used to add covariance matrices from several uncertainty sources.

Definition at line 3379 of file TUnfold.cxx.

Execute() [1/2]

void TObject::Execute ( const char * method, const char * params, Int_t * error = nullptr )

virtualinherited

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

"3.14,1,\"text\"".

Reimplemented in ROOT::R::TRInterface, TCling, TContextMenu, TInterpreter, and TMethodCall.

Definition at line 378 of file TObject.cxx.

Execute() [2/2]

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

virtualinherited

Execute method on this object with parameters stored in the TObjArray.

The TObjArray should contain an argv vector like:

argv[0] ... argv[n] = the list of TObjString parameters

Reimplemented in ROOT::R::TRInterface, TCling, TContextMenu, TInterpreter, and TMethodCall.

Definition at line 398 of file TObject.cxx.

ExecuteEvent()

void TObject::ExecuteEvent ( Int_t event, Int_t px, Int_t py )

virtualinherited

Execute action corresponding to an event at (px,py).

This method must be overridden if an object can react to graphics events.

Reimplemented in TASImage, TASPaletteEditor::LimitLine, TAxis3D, TAxis, TBox, TButton, TCanvas, TCrown, TCurlyArc, TCurlyLine, TDiamond, TEfficiency, TEllipse, TF1, TF2, TF3, TFrame, TGenerator, TGeoManager, TGeoNode, TGeoOverlap, TGeoShape, TGeoTrack, TGeoVolume, TGL5DDataSet, TGLEventHandler, TGLHistPainter, TGLParametricEquation, TGLScenePad, TGLTH3Composition, TGLViewer, TGraph2D, TGraph, TGraphEdge, TGraphNode, TGraphPolargram, TGroupButton, TH1, THistPainter, TLine, TLink, TMarker3DBox, TMarker, TNode, TPad, TPaletteAxis, TParallelCoord, TParallelCoordRange, TParallelCoordVar, TParticle, TPave, TPie, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TPrimary, TScatter2D, TScatter, TSliderBox, TSpider, TSpline, TText, TTreePerfStats, TView3D, TView, TVirtualHistPainter, and TWbox.

Definition at line 415 of file TObject.cxx.

Fatal()

void TObject::Fatal ( const char * location, const char * fmt, ... ) const

virtualinherited

Issue fatal error message.

Use "location" to specify the method where the fatal error occurred. Accepts standard printf formatting arguments.

Definition at line 1126 of file TObject.cxx.

FindObject() [1/2]

TObject * TObject::FindObject ( const char * name ) const

virtualinherited

Must be redefined in derived classes.

This function is typically used with TCollections, but can also be used to find an object by name inside this object.

Reimplemented in RooAbsCollection, RooLinkedList, TBtree, TCollection, TDirectory, TFolder, TGeometry, TGraph2D, TGraph, TH1, THashList, THashTable, THbookFile, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TListOfTypes, TMap, TObjArray, TPad, TROOT, TViewPubDataMembers, and TViewPubFunctions.

Definition at line 425 of file TObject.cxx.

FindObject() [2/2]

TObject * TObject::FindObject ( const TObject * obj ) const

virtualinherited

Must be redefined in derived classes.

This function is typically used with TCollections, but can also be used to find an object inside this object.

Reimplemented in RooAbsCollection, RooLinkedList, TBtree, TCollection, TDirectory, TFolder, TGeometry, TGraph2D, TGraph, TH1, THashList, THashTable, THbookFile, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TListOfTypes, TMap, TObjArray, TPad, TROOT, TViewPubDataMembers, and TViewPubFunctions.

Definition at line 435 of file TObject.cxx.

GetAx()

const TMatrixDSparse * TUnfold::GetAx ( void ) const

inlineprotectedinherited

vector of folded-back result

Definition at line 248 of file TUnfold.h.

GetBackground() [1/2]

TH1 * TUnfoldDensity::GetBackground	(	const char *	histogramName,
		const char *	bgrSource = nullptr,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE,
		Int_t	includeError = 3 ) const

retreive a background source in a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	bgrSource	the background source to retreive
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels
[in]	includeError	(default=3) type of background errors to be included (+1 uncorrelated bgr errors, +2 correlated bgr errors)

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 751 of file TUnfoldDensity.cxx.

GetBackground() [2/2]

void TUnfoldSys::GetBackground ( TH1 * bgrHist, const char * bgrSource = nullptr, const Int_t * binMap = nullptr, Int_t includeError = 3, Bool_t clearHist = kTRUE ) const

inherited

get background into a histogram

Parameters

[in,out]	bgrHist	target histogram, content and errors will be altered
[in]	bgrSource	(default=nullptr) name of backgrond source or zero to add all sources of background
[in]	binMap	(default=nullptr) remap histogram bins
[in]	includeError	(default=3) include uncorrelated(1), correlated (2) or both (3) sources of uncertainty in the histogram errors
[in]	clearHist	(default=true) reset histogram before adding up the specified background sources

the array binMap is explained with the method GetOutput(). The flag clearHist may be used to add background from several sources in successive calls to GetBackground().

Definition at line 564 of file TUnfoldSys.cxx.

GetBgrSources()

TSortedList * TUnfoldSys::GetBgrSources ( void ) const

inherited

Get a new list of all background sources.

The user is responsible for deleting the list get list of name of background sources

Definition at line 1527 of file TUnfoldSys.cxx.

GetBias() [1/2]

void TUnfold::GetBias ( TH1 * out, const Int_t * binMap = nullptr ) const

inherited

get bias vector including bias scale

Parameters

[out]	out	histogram to store the scaled bias vector. The bin contents are overwritten
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

This method returns the bias vector times scaling factor, f*x₀

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 2935 of file TUnfold.cxx.

GetBias() [2/2]

TH1 * TUnfoldDensity::GetBias	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE ) const

retreive bias vector as a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 685 of file TUnfoldDensity.cxx.

GetBinFromRow()

Int_t TUnfold::GetBinFromRow ( int ix ) const

inlineprotectedinherited

converts matrix row to truth histogram bin number

Definition at line 236 of file TUnfold.h.

GetChi2A()

Double_t TUnfold::GetChi2A ( void ) const

inlineinherited

get χ²_A contribution determined in recent unfolding

Definition at line 329 of file TUnfold.h.

GetChi2L()

Double_t TUnfold::GetChi2L ( void ) const

inherited

get χ²_L contribution determined in recent unfolding

Definition at line 3231 of file TUnfold.cxx.

GetChi2Sys()

Double_t TUnfoldSys::GetChi2Sys ( void )

inherited

calculate total chi**2 including all systematic errors

Definition at line 1365 of file TUnfoldSys.cxx.

GetDeltaSysBackgroundScale() [1/2]

TH1 * TUnfoldDensity::GetDeltaSysBackgroundScale	(	const char *	bgrSource,
		const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive systematic 1-sigma shift corresponding to a background scale uncertainty

Parameters

[in]	bgrSource	identifier of the background
[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 944 of file TUnfoldDensity.cxx.

GetDeltaSysBackgroundScale() [2/2]

Bool_t TUnfoldSys::GetDeltaSysBackgroundScale ( TH1 * hist_delta, const char * source, const Int_t * binMap = nullptr )

inherited

correlated one-sigma shifts from background normalisation uncertainty

Parameters

[out]	hist_delta	histogram to store shifts
[in]	source	identifier of the background source
[in]	binMap	(default=nullptr) remapping of histogram bins

returns true if the background source was found.
This method returns the shifts of the unfolding result induced by varying the normalisation of the identified background by one sigma.
the array binMap is explained with the method GetOutput().

Definition at line 1053 of file TUnfoldSys.cxx.

GetDeltaSysSource() [1/2]

TH1 * TUnfoldDensity::GetDeltaSysSource	(	const char *	source,
		const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive a correlated systematic 1-sigma shift

Parameters

[in]	source	identifier of the systematic uncertainty source
[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 911 of file TUnfoldDensity.cxx.

GetDeltaSysSource() [2/2]

Bool_t TUnfoldSys::GetDeltaSysSource ( TH1 * hist_delta, const char * name, const Int_t * binMap = nullptr )

inherited

correlated one-sigma shifts correspinding to a given systematic uncertainty

Parameters

[out]	hist_delta	histogram to store shifts
[in]	name	identifier of the background source
[in]	binMap	(default=nullptr) remapping of histogram bins

returns true if the error source was found.
This method returns the shifts of the unfolding result induced by varying the identified systematic source by one sigma.
the array binMap is explained with the method GetOutput().

Definition at line 1026 of file TUnfoldSys.cxx.

GetDeltaSysTau() [1/2]

TH1 * TUnfoldDensity::GetDeltaSysTau	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive1-sigma shift corresponding to the previously specified uncertainty on tau

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 976 of file TUnfoldDensity.cxx.

GetDeltaSysTau() [2/2]

Bool_t TUnfoldSys::GetDeltaSysTau ( TH1 * hist_delta, const Int_t * binMap = nullptr )

inherited

correlated one-sigma shifts from shifting tau

Parameters

[out]	hist_delta	histogram to store shifts
[in]	source	identifier of the background source
[in]	binMap	(default=nullptr) remapping of histogram bins

returns true if the background source was found.
This method returns the shifts of the unfolding result induced by varying the normalisation of the identified background by one sigma.
the array binMap is explained with the method GetOutput().

Definition at line 1085 of file TUnfoldSys.cxx.

GetDensityFactor()

Double_t TUnfoldDensity::GetDensityFactor ( EDensityMode densityMode, Int_t iBin ) const

protected

density correction factor for a given bin

Parameters

[in]	densityMode	type of factor to calculate
[in]	iBin	bin number

return a multiplicative factor, for scaling the regularisation conditions from this bin.
For densityMode=kDensityModeNone the factor is set to unity. For densityMode=kDensityModeBinWidth the factor is set to 1/binArea where the binArea is the product of the bin widths in all dimensions. If the width of a bin is zero or can not be determined, the factor is set to zero. For densityMode=kDensityModeUser the factor is determined from the method TUnfoldBinning::GetBinFactor(). For densityMode=kDensityModeBinWidthAndUser, the results of kDensityModeBinWidth and kDensityModeUser are multiplied.

Definition at line 335 of file TUnfoldDensity.cxx.

GetDF()

double TUnfold::GetDF ( void ) const

inherited

return the effecive number of degrees of freedom See e.g.

arXiv:1612.09415 and the references therein

Here, DF is calculated using the dependence of the unfolding result x on the data y

This calculation is done assuming a CONSTANT data variance. I.e. the uncertainties reported to TUnfold in "SetInput()" ought to be independent of the measurements. This is NOT true for standard Poisson-distributed data. In practice the impact is expected to be small

Definition at line 3749 of file TUnfold.cxx.

GetDrawOption()

Option_t * TObject::GetDrawOption ( ) const

virtualinherited

Get option used by the graphics system to draw this object.

Note that before calling object.GetDrawOption(), you must have called object.Draw(..) before in the current pad.

Reimplemented in TBrowser, TFitEditor, TGedFrame, TGFileBrowser, TRootBrowser, and TRootBrowserLite.

Definition at line 445 of file TObject.cxx.

GetDtorOnly()

Longptr_t TObject::GetDtorOnly ( )

staticinherited

Return destructor only flag.

Definition at line 1196 of file TObject.cxx.

GetDXDAM()

const TMatrixDSparse * TUnfold::GetDXDAM ( int i ) const

inlineprotectedinherited

matrix contributions of the derivative dx/dA

Definition at line 252 of file TUnfold.h.

GetDXDAZ()

const TMatrixDSparse * TUnfold::GetDXDAZ ( int i ) const

inlineprotectedinherited

vector contributions of the derivative dx/dA

Definition at line 254 of file TUnfold.h.

GetDXDtauSquared()

const TMatrixDSparse * TUnfold::GetDXDtauSquared ( void ) const

inlineprotectedinherited

vector of derivative dx/dtauSquared, using internal bin counting

Definition at line 265 of file TUnfold.h.

GetDXDY() [1/3]

void TUnfold::GetDXDY ( TH2 * dxdy ) const

inherited

get matrix connecting input and output changes

get matrix describing gow the result changes with the input data

Parameters

[out]

dxdy

two-dimensional histogram to store the matrix connecting the output and input data. The bin contents are overwritten for those bins where dxdy is non-zero.

Definition at line 3038 of file TUnfold.cxx.

GetDXDY() [2/3]

const TMatrixDSparse * TUnfold::GetDXDY ( void ) const

inlineprotectedinherited

matrix of derivatives dx/dy

Definition at line 250 of file TUnfold.h.

GetDXDY() [3/3]

TH2 * TUnfoldDensity::GetDXDY	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		bool	useAxisBinning = true ) const

get matrix DX/DY in a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. if histogramTitle is null, choose a title automatically.

Definition at line 1166 of file TUnfoldDensity.cxx.

GetE()

const TMatrixDSparse * TUnfold::GetE ( void ) const

inlineprotectedinherited

matrix E, using internal bin counting

Definition at line 258 of file TUnfold.h.

GetEinv()

const TMatrixDSparse * TUnfold::GetEinv ( void ) const

inlineprotectedinherited

matrix E^-1, using internal bin counting

Definition at line 256 of file TUnfold.h.

GetEmatrix()

void TUnfold::GetEmatrix ( TH2 * ematrix, const Int_t * binMap = nullptr ) const

inherited

get output covariance matrix, possibly cumulated over several bins

Parameters

[out]	ematrix	histogram to store the covariance. The bin contents are overwritten.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 3446 of file TUnfold.cxx.

GetEmatrixFromVyy()

void TUnfoldSys::GetEmatrixFromVyy ( const TMatrixDSparse * vyy, TH2 * ematrix, const Int_t * binMap, Bool_t clearEmat )

protectedinherited

propagate an error matrix on the input vector to the unfolding result

Parameters

[in]	vyy	input error matrix
[in,out]	ematrix	histogram to be updated
[in]	binMap	mapping of histogram bins
[in]	clearEmat	if set, clear histogram before adding this covariance contribution

Definition at line 1249 of file TUnfoldSys.cxx.

GetEmatrixInput() [1/2]

TH2 * TUnfoldDensity::GetEmatrixInput	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

get covariance contribution from the input uncertainties (data statistical uncertainties)

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 1119 of file TUnfoldDensity.cxx.

GetEmatrixInput() [2/2]

void TUnfoldSys::GetEmatrixInput ( TH2 * ematrix, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

covariance matrix contribution from input measurement uncertainties

Parameters

[in,out]	ematrix	output histogram
[in]	binMap	(default=nullptr) remapping of histogram bins
[in]	clearEmat	(default=true) if true, clear the histogram

this method returns the covariance contributions to the unfolding result from the uncertainties or covariance of the input data. In many cases, these are the "statistical uncertainties".
The array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 1206 of file TUnfoldSys.cxx.

GetEmatrixSysBackgroundScale()

void TUnfoldSys::GetEmatrixSysBackgroundScale ( TH2 * ematrix, const char * name, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

covariance contribution from background normalisation uncertainty

Parameters

[in,out]	ematrix	output histogram
[in]	source	identifier of the background source
[in]	binMap	(default=nullptr) remapping of histogram bins
[in]	clearEmat	(default=true) if true, clear the histogram prior to adding the covariance matrix contribution

this method returns the uncertainties on the unfolding result arising from the background source source and its normalisation uncertainty. See method SubtractBackground() how to set the normalisation uncertainty
the array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 1143 of file TUnfoldSys.cxx.

GetEmatrixSysBackgroundUncorr() [1/2]

TH2 * TUnfoldDensity::GetEmatrixSysBackgroundUncorr	(	const char *	bgrSource,
		const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive covariance contribution from uncorrelated background uncertainties

Parameters

[in]	bgrSource	identifier of the background
[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 1088 of file TUnfoldDensity.cxx.

GetEmatrixSysBackgroundUncorr() [2/2]

void TUnfoldSys::GetEmatrixSysBackgroundUncorr ( TH2 * ematrix, const char * source, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

covariance contribution from background uncorrelated uncertainty

Parameters

[in]	ematrix	output histogram
[in]	source	identifier of the background source
[in]	binMap	(default=nullptr) remapping of histogram bins
[in]	clearEmat	(default=true) if true, clear the histogram

this method returns the covariance contributions to the unfolding result arising from the background source source and the uncorrelated (background histogram uncertainties). Also see method SubtractBackground()
the array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 1228 of file TUnfoldSys.cxx.

GetEmatrixSysSource()

void TUnfoldSys::GetEmatrixSysSource ( TH2 * ematrix, const char * name, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

covariance contribution from a systematic variation of the response matrix

Parameters

[in,out]	ematrix	covariance matrix histogram
[in]	name	identifier of the systematic variation
[in]	binMap	(default=nullptr) remapping of histogram bins
[in]	clearEmat	(default=true) if true, clear the histogram prior to adding the covariance matrix contribution

Returns the covariance matrix contribution from shifting the given uncertainty source within one sigma
the array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 1112 of file TUnfoldSys.cxx.

GetEmatrixSysTau()

void TUnfoldSys::GetEmatrixSysTau ( TH2 * ematrix, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

covariance matrix contribution from error on regularisation parameter

Parameters

[in,out]	ematrix	output histogram
[in]	binMap	(default=nullptr) remapping of histogram bins
[in]	clearEmat	(default=true) if true, clear the histogram

this method returns the covariance contributions to the unfolding result from the assigned uncertainty on the parameter tau, see method SetTauError().
the array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 1175 of file TUnfoldSys.cxx.

GetEmatrixSysUncorr() [1/2]

TH2 * TUnfoldDensity::GetEmatrixSysUncorr	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive covaraince contribution from uncorrelated (statistical) uncertainties of the response matrix

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 1058 of file TUnfoldDensity.cxx.

GetEmatrixSysUncorr() [2/2]

void TUnfoldSys::GetEmatrixSysUncorr ( TH2 * ematrix, const Int_t * binMap = nullptr, Bool_t clearEmat = kTRUE )

inherited

Covariance contribution from uncorrelated uncertainties of the response matrix.

Parameters

[in,out]	ematrix	covariance matrix histogram
[in]	binMap	mapping of histogram bins
[in]	clearEmat	if true, ematrix is cleared prior to adding this covariance matrix contribution

This method propagates the uncertainties of the response matrix histogram, specified with the constructor, to the unfolding result. It is assumed that the entries of that histogram are bin-to-bin uncorrelated. In many cases this corresponds to the "Monte Carlo statistical uncertainties".
The array binMap is explained with the method GetOutput(). The flag clearEmat may be used to add covariance matrices from several uncertainty sources.

Definition at line 759 of file TUnfoldSys.cxx.

GetEmatrixTotal() [1/2]

TH2 * TUnfoldDensity::GetEmatrixTotal	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

get covariance matrix including all contributions

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 1191 of file TUnfoldDensity.cxx.

GetEmatrixTotal() [2/2]

void TUnfoldSys::GetEmatrixTotal ( TH2 * ematrix, const Int_t * binMap = nullptr )

inherited

Get total error matrix, summing up all contributions.

Parameters

[out]	ematrix	histogram which will be filled
[in]	binMap	(default=nullptr) remapping of histogram bins

the array binMap is explained with the method GetOutput().

Definition at line 1275 of file TUnfoldSys.cxx.

GetEpsMatrix()

Double_t TUnfold::GetEpsMatrix ( void ) const

inlineinherited

get numerical accuracy for Eigenvalue analysis when inverting matrices with rank problems

Definition at line 352 of file TUnfold.h.

GetFoldedOutput() [1/2]

void TUnfold::GetFoldedOutput ( TH1 * out, const Int_t * binMap = nullptr ) const

inherited

get unfolding result on detector level

Parameters

[out]	out	histogram to store the correlation coefficiencts. The bin contents and errors are overwritten.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

This method returns the unfolding output folded by the response matrix, i.e. the vector Ax.

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 2962 of file TUnfold.cxx.

GetFoldedOutput() [2/2]

TH1 * TUnfoldDensity::GetFoldedOutput	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE,
		Bool_t	addBgr = kFALSE ) const

retreive unfolding result folded back as a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels
[in]	addBgr	(default=false) if true, include the background contribution (useful for direct comparison to data)

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 716 of file TUnfoldDensity.cxx.

GetIconName()

const char * TObject::GetIconName ( ) const

virtualinherited

Returns mime type name of object.

Used by the TBrowser (via TGMimeTypes class). Override for class of which you would like to have different icons for objects of the same class.

Reimplemented in ROOT::Experimental::XRooFit::xRooNode, TASImage, TBranch, TBranchElement, TGeoVolume, TGMainFrame, TKey, TMethodBrowsable, TSystemFile, and TVirtualBranchBrowsable.

Definition at line 472 of file TObject.cxx.

GetInput() [1/2]

void TUnfold::GetInput ( TH1 * out, const Int_t * binMap = nullptr ) const

inherited

Input vector of measurements.

Parameters

[out]	out	histogram to store the measurements. Bin content and bin errors are overwritte.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

Bins which had an uncertainty of zero in the call to SetInput() maye acquire bin contents or bin errors different from the original settings in SetInput().

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 3069 of file TUnfold.cxx.

GetInput() [2/2]

TH1 * TUnfoldDensity::GetInput	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE ) const

retreive input distribution in a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 781 of file TUnfoldDensity.cxx.

GetInputBinning()

const TUnfoldBinning * TUnfoldDensity::GetInputBinning

(

const char *

distributionName = nullptr

)

const

locate a binning node for the input (measured) quantities

Parameters

[in]

distributionName

(default=nullptr) distribution to look for. if zero, return the root node

returns: pointer to a TUnfoldBinning object or zero if not found

Definition at line 1293 of file TUnfoldDensity.cxx.

GetInputInverseEmatrix()

void TUnfold::GetInputInverseEmatrix ( TH2 * out )

inherited

get inverse of the measurement's covariance matrix

Parameters

[out]

out

histogram to store the inverted covariance

Definition at line 3098 of file TUnfold.cxx.

GetL() [1/2]

void TUnfold::GetL ( TH2 * out ) const

inherited

get matrix of regularisation conditions

Parameters

[out]

out

histogram to store the regularisation conditions. the bincontents are overwritten

The histogram should have dimension nr (y-axis) times nx (x-axis). nr corresponds to the number of regularisation conditions, it can be obtained using the method GetNr(). nx corresponds to the number of histogram bins in the response matrix along the truth axis.

Definition at line 3191 of file TUnfold.cxx.

GetL() [2/2]

TH2 * TUnfoldDensity::GetL	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		Bool_t	useAxisBinning = kTRUE )

access matrix of regularisation conditions in a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. if histogramTitle is null, choose a title automatically.

Definition at line 1218 of file TUnfoldDensity.cxx.

GetLBinning()

TUnfoldBinning * TUnfoldDensity::GetLBinning ( void ) const

inline

return binning scheme for regularisation conditions (matrix L)

Definition at line 203 of file TUnfoldDensity.h.

GetLcurveX()

Double_t TUnfold::GetLcurveX ( void ) const

virtualinherited

get value on x-axis of L-curve determined in recent unfolding

x=log₁₀(GetChi2A())

Definition at line 3251 of file TUnfold.cxx.

GetLcurveY()

Double_t TUnfold::GetLcurveY ( void ) const

virtualinherited

get value on y-axis of L-curve determined in recent unfolding

y=log₁₀(GetChi2L())

Definition at line 3260 of file TUnfold.cxx.

GetLsquared()

void TUnfold::GetLsquared ( TH2 * out ) const

inherited

get matrix of regularisation conditions squared

Parameters

[out]

out

histogram to store the squared matrix of regularisation conditions. the bin contents are overwritten

This returns the square matrix L^TL as a histogram

The histogram should have dimension nx times nx, where nx corresponds to the number of histogram bins in the response matrix along the truth axis.

Definition at line 3151 of file TUnfold.cxx.

GetLxMinusBias()

TH1 * TUnfoldDensity::GetLxMinusBias	(	const char *	histogramName,
		const char *	histogramTitle = nullptr )

get regularisation conditions multiplied by result vector minus bias L(x-biasScale*biasVector)

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram

returns a new histogram. This is a measure of the level of regulartisation required per regularisation condition. If there are (negative or positive) spikes, these regularisation conditions dominate over the other regularisation conditions and may introduce the largest biases.

Definition at line 1255 of file TUnfoldDensity.cxx.

GetName()

const char * TObject::GetName ( ) const

virtualinherited

Returns name of object.

This default method returns the class name. Classes that give objects a name should override this method.

Reimplemented in RooAbsCollection, RooCatType, RooLinkedList, TArchiveMember, TCollection, TEnvRec, TEveGeoNode, TGaxis, TGeoDecayChannel, TGeoShape, TGeoVGShape, TGLEmbeddedViewer, TGLPShapeObj, TGLSAViewer, TGMenuEntry, TGMenuTitle, TGPicture, TGWindow, TIconBoxThumb, TMapFile, TMVA::DataSetInfo, TMVA::FitterBase, TMVA::MethodBase, TMVA::OptionBase, TMVA::PDF, TMVA::Reader, TMVA::VariableTransformBase, TNamed, TObjString, TPad, TPair, TParameter< AParamType >, TParameter< Long64_t >, TParticle, TPave, TPolyMarker3D, TPrimary, TQCommand, TQConnection, TQSlot, TRealData, TSQLClassColumnInfo, TSQLClassInfo, TSQLColumnData, TStatistic, TStructNode, TTreePerfStats, TTVRecord, TTVSession, TVirtualGeoTrack, TVirtualPad, and TXMLAttr.

Definition at line 462 of file TObject.cxx.

GetNdf()

Int_t TUnfold::GetNdf ( void ) const

inlineinherited

get number of degrees of freedom determined in recent unfolding

This returns the number of valid measurements minus the number of unfolded truth bins. If the area constraint is active, one further degree of freedom is subtracted

Definition at line 339 of file TUnfold.h.

GetNormalisationVector()

void TUnfold::GetNormalisationVector ( TH1 * out, const Int_t * binMap = nullptr ) const

inherited

histogram of truth bins, determined from suming over the response matrix

Parameters

[out]	out	histogram to store the truth bins. The bin contents are overwritten
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

This vector is also used to initialize the bias x₀. However, the bias vector may be changed using the SetBias() method.

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 2910 of file TUnfold.cxx.

GetNpar()

Int_t TUnfold::GetNpar ( void ) const

inherited

get number of truth parameters determined in recent unfolding

empty bins of the response matrix or bins which can not be unfolded due to rank deficits are not counted

Definition at line 3242 of file TUnfold.cxx.

GetNr()

Int_t TUnfold::GetNr ( void ) const

inherited

get number of regularisation conditions

Ths returns the number of regularisation conditions, useful for booking a histogram for a subsequent call of GetL().

Definition at line 3176 of file TUnfold.cxx.

GetNx()

Int_t TUnfold::GetNx ( void ) const

inlineprotectedinherited

returns internal number of output (truth) matrix rows

Definition at line 230 of file TUnfold.h.

GetNy()

Int_t TUnfold::GetNy ( void ) const

inlineprotectedinherited

returns the number of measurement bins

Definition at line 238 of file TUnfold.h.

GetObjectInfo()

char * TObject::GetObjectInfo ( Int_t px, Int_t py ) const

virtualinherited

Returns string containing info about the object at position (px,py).

This method is typically overridden by classes of which the objects can report peculiarities for different positions. Returned string will be re-used (lock in MT environment).

Reimplemented in TASImage, TAxis3D, TColorWheel, TF1, TF2, TFileDrawMap, TGeoNode, TGeoTrack, TGeoVolume, TGL5DDataSet, TGLHistPainter, TGLParametricEquation, TGLTH3Composition, TGraph, TH1, THistPainter, TNode, TPaletteAxis, TParallelCoordVar, and TVirtualHistPainter.

Definition at line 491 of file TObject.cxx.

GetObjectStat()

Bool_t TObject::GetObjectStat ( )

staticinherited

Get status of object stat flag.

Definition at line 1181 of file TObject.cxx.

GetOption()

virtual Option_t * TObject::GetOption ( ) const

inlinevirtualinherited

Reimplemented in TArrow, TAxis3D, TFile, TGaxis, TGeoVolume, TH1, THelix, TLegendEntry, TMapFile, TNode, TPave, TPoints3DABC, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TPSocket, TSelector, TSocket, and TUDPSocket.

Definition at line 147 of file TObject.h.

GetOutput() [1/2]

void TUnfold::GetOutput ( TH1 * output, const Int_t * binMap = nullptr ) const

inherited

get output distribution, possibly cumulated over several bins

Parameters

[out]	output	existing output histogram. content and errors will be updated.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

If nonzero, the array binMap must have dimension n+2, where n corresponds to the number of bins on the truth axis of the response matrix (the histogram specified with the TUnfold constructor). The indexes of binMap correspond to the truth bins (including underflow and overflow) of the response matrix. The element binMap[i] specifies the histogram number in output where the corresponding truth bin will be stored. It is possible to specify the same output bin number for multiple indexes, in which case these bins are added. Set binMap[i]=-1 to ignore an unfolded truth bin. The uncertainties are calculated from the corresponding parts of the covariance matrix, properly taking care of added truth bins.
If the pointer binMap is zero, the bins are mapped one-to-one. Truth bin zero (underflow) is stored in the output underflow, truth bin 1 is stored in bin number 1, etc.

Definition at line 3289 of file TUnfold.cxx.

GetOutput() [2/2]

TH1 * TUnfoldDensity::GetOutput	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE ) const

retreive unfolding result as a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

return value: pointer to a new histogram. If useAxisBinning is set and if the selected distribution fits into a root histogram (1,2,3 dimensions) then return a histogram with the proper binning on each axis. Otherwise, return a 1D histogram with equidistant binning. If the histogram title is zero, a title is assigned automatically.

The axisSteering is defines as follows: "axis[mode];axis[mode];..." where:

• axis = name of an axis or *
• mode = any combination of the letters CUO0123456789
  • C collapse axis into one bin (add up results). If any of the numbers 0-9 are given in addition, only these bins are added up. Here bins are counted from zero, whereas in root, bins are counted from 1. Obviously, this only works for up to 10 bins.
  • U discarde underflow bin
  • O discarde overflow bin

examples: imagine the binning has two axis, named x and y.

• "*[UO]" exclude underflow and overflow bins for all axis. So here a TH2 is returned but all undeflow and overflow bins are empty
• "x[UOC123]" integrate over the variable x but only using the bins 1,2,3 and not the underflow and overflow in x. Here a TH1 is returned, the axis is labelled "y" and the underflow and overflow (in y) are filled. However only the x-bins 1,2,3 are used to determine the content.
• "x[C];y[UO]" integrate over the variable x, including underflow and overflow but exclude underflow and overflow in y. Here a TH1 is returned, the axis is labelled "y". The underflow and overflow in y are empty.

Definition at line 654 of file TUnfoldDensity.cxx.

GetOutputBinName()

TString TUnfoldDensity::GetOutputBinName ( Int_t iBinX ) const

overrideprotectedvirtual

Get bin name of an outpt bin.

Parameters

[in]

iBinX

bin number

Return value: name of the bin. The name is constructed from the entries in the binning scheme and includes information about the bin borders etc.

Reimplemented from TUnfold.

Definition at line 311 of file TUnfoldDensity.cxx.

GetOutputBinning()

const TUnfoldBinning * TUnfoldDensity::GetOutputBinning

(

const char *

distributionName = nullptr

)

const

locate a binning node for the unfolded (truth level) quantities

Parameters

[in]

distributionName

(default=nullptr) distribution to look for. if zero, return the root node

returns: pointer to a TUnfoldBinning object or zero if not found

Definition at line 1309 of file TUnfoldDensity.cxx.

GetProbabilityMatrix() [1/2]

void TUnfold::GetProbabilityMatrix ( TH2 * A, EHistMap histmap ) const

inherited

get matrix of probabilities

Parameters

[out]	A	two-dimensional histogram to store the probabilities (normalized response matrix). The bin contents are overwritten for those bins where A is nonzero
[in]	histmap	specify axis along which the truth bins are oriented

Definition at line 3010 of file TUnfold.cxx.

GetProbabilityMatrix() [2/2]

TH2 * TUnfoldDensity::GetProbabilityMatrix	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		Bool_t	useAxisBinning = kTRUE ) const

get matrix of probabilities in a new histogram

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. if histogramTitle is null, choose a title automatically.

Definition at line 1145 of file TUnfoldDensity.cxx.

GetRhoAvg()

Double_t TUnfold::GetRhoAvg ( void ) const

inlineinherited

get average global correlation determined in recent unfolding

Definition at line 327 of file TUnfold.h.

GetRhoI()

Double_t TUnfold::GetRhoI ( TH1 * rhoi, const Int_t * binMap = nullptr, TH2 * invEmat = nullptr ) const

inherited

get global correlation coefficiencts, possibly cumulated over several bins

Parameters

[out]	rhoi	histogram to store the global correlation coefficients. The bin contents are overwritten.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins
[out]	invEmat	(default=nullptr) histogram to store the inverted covariance matrix

for a given bin, the global correlation coefficient is defined as
ρ_i=sqrt(1-1/(V_ii*V^-1_ii))
such that the calculation of global correlation coefficients possibly involves the inversion of a covariance matrix.

return value: maximum global correlation coefficient

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 3504 of file TUnfold.cxx.

GetRhoIFromMatrix()

Double_t TUnfold::GetRhoIFromMatrix ( TH1 * rhoi, const TMatrixDSparse * eOrig, const Int_t * binMap, TH2 * invEmat ) const

protectedinherited

Definition at line 3553 of file TUnfold.cxx.

GetRhoIJ()

void TUnfold::GetRhoIJ ( TH2 * rhoij, const Int_t * binMap = nullptr ) const

inherited

get correlation coefficiencts, possibly cumulated over several bins

Parameters

[out]	rhoij	histogram to store the correlation coefficiencts. The bin contents are overwritten.
[in]	binMap	(default=nullptr) array for mapping truth bins to histogram bins

The use of binMap is explained with the documentation of the GetOutput() method

Definition at line 3461 of file TUnfold.cxx.

GetRhoIJtotal()

TH2 * TUnfoldDensity::GetRhoIJtotal	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE )

retreive correlation coefficients, including all uncertainties

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels

returns a new histogram. See method GetOutput() for a detailed description of the arguments

Definition at line 1007 of file TUnfoldDensity.cxx.

GetRhoIstatbgr()

TH1 * TUnfoldDensity::GetRhoIstatbgr	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE,
		TH2 **	ematInv = nullptr )

retreive global correlation coefficients including input (statistical) and background uncertainties

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels
[out]	ematInv	(default=nullptr) to return the inverse covariance matrix

returns a new histogram. See method GetOutput() for a detailed description of the arguments. The inverse of the covariance matrix is stored in a new histogram returned by ematInv if that pointer is non-zero.

Definition at line 863 of file TUnfoldDensity.cxx.

GetRhoItotal() [1/2]

TH1 * TUnfoldDensity::GetRhoItotal	(	const char *	histogramName,
		const char *	histogramTitle = nullptr,
		const char *	distributionName = nullptr,
		const char *	axisSteering = nullptr,
		Bool_t	useAxisBinning = kTRUE,
		TH2 **	ematInv = nullptr )

retreive global correlation coefficients including all uncertainty sources

Parameters

[in]	histogramName	name of the histogram
[in]	histogramTitle	(default=nullptr) title of the histogram
[in]	distributionName	(default=nullptr) identifier of the distribution to be extracted
[in]	axisSteering	(default=nullptr) detailed steering within the extracted distribution
[in]	useAxisBinning	(default=true) if set to true, try to extract a histogram with proper binning and axis labels
[out]	ematInv	(default=nullptr) to return the inverse covariance matrix

returns a new histogram. See method GetOutput() for a detailed description of the arguments. The inverse of the covariance matrix is stored in a new histogram returned by ematInv if that pointer is non-zero.

Definition at line 813 of file TUnfoldDensity.cxx.

GetRhoItotal() [2/2]

void TUnfoldSys::GetRhoItotal ( TH1 * rhoi, const Int_t * binMap = nullptr, TH2 * invEmat = nullptr )

inherited

Get global correlatiocn coefficients, summing up all contributions.

Parameters

[out]	rhoi	histogram which will be filled
[in]	binMap	(default=nullptr) remapping of histogram bins
[out]	invEmat	(default=nullptr) inverse of error matrix

return the global correlation coefficients, including all error sources. If invEmat is nonzero, the inverse of the error matrix is returned in that histogram
the array binMap is explained with the method GetOutput().

Definition at line 1400 of file TUnfoldSys.cxx.

GetRhoMax()

Double_t TUnfold::GetRhoMax ( void ) const

inlineinherited

get maximum global correlation determined in recent unfolding

Definition at line 325 of file TUnfold.h.

GetRowFromBin()

Int_t TUnfold::GetRowFromBin ( int ix ) const

inlineprotectedinherited

converts truth histogram bin number to matrix row

Definition at line 234 of file TUnfold.h.

GetScanVariable()

Double_t TUnfoldDensity::GetScanVariable ( Int_t mode, const char * distribution, const char * axisSteering )

virtual

calculate the function for ScanTau()

Parameters

[in]	mode	the variable to be calculated
[in]	distribution	distribution for which the variable is to be calculated
[in]	axisSteering	detailed steering for selecting bins on the axes of the distribution (see method GetRhoItotal())

return value: the scan result for the given choice of tau (for which the unfolding was performed prior to calling this method)
In ScanTau() the unfolding is repeated for various choices of tau. For each tau, after unfolding, GetScanVariable() is called to determine the scan result for this choice of tau.
the following modes are implemented

• kEScanTauRhoAvg : average (stat+bgr) global correlation
• kEScanTauRhoSquaredAvg : average (stat+bgr) global correlation squared
• kEScanTauRhoMax : maximum (stat+bgr) global correlation
• kEScanTauRhoAvgSys : average (stat+bgr+sys) global correlation
• kEScanTauRhoAvgSquaredSys : average (stat+bgr+sys) global correlation squared
• kEScanTauRhoMaxSys : maximum (stat+bgr+sys) global correlation

Definition at line 1680 of file TUnfoldDensity.cxx.

GetSqrtEvEmatrix()

TVectorD TUnfold::GetSqrtEvEmatrix ( void ) const

inherited

Definition at line 2509 of file TUnfold.cxx.

GetSummedErrorMatrixXX()

TMatrixDSparse * TUnfoldSys::GetSummedErrorMatrixXX ( void )

protectedinherited

determine total error matrix on the vector x

Definition at line 1330 of file TUnfoldSys.cxx.

GetSummedErrorMatrixYY()

TMatrixDSparse * TUnfoldSys::GetSummedErrorMatrixYY ( void )

protectedinherited

determine total error matrix on the vector Ax

Definition at line 1295 of file TUnfoldSys.cxx.

GetSURE()

double TUnfold::GetSURE ( void ) const

inherited

return Stein's unbiased risk estimator See e.g.

arXiv:1612.09415

A minimum in the SURE variable is a good choice of regularisation strength

NOTE: the calculation of SURE depends on the calculation of DF. See the method GetDF() for caveats with Poisson-distributed data.

Definition at line 3732 of file TUnfold.cxx.

GetSysSources()

TSortedList * TUnfoldSys::GetSysSources ( void ) const

inherited

Get a new list of all systematic uuncertainty sources.

The user is responsible for deleting the list

Definition at line 1511 of file TUnfoldSys.cxx.

GetTau()

Double_t TUnfold::GetTau ( void ) const

inherited

return regularisation parameter

Definition at line 3223 of file TUnfold.cxx.

GetTitle()

const char * TObject::GetTitle ( ) const

virtualinherited

Returns title of object.

This default method returns the class title (i.e. description). Classes that give objects a title should override this method.

Reimplemented in Axis2, TASImage, TAxis, TBaseClass, TClassMenuItem, TEveGeoNode, TEvePointSet, TGaxis, TGGroupFrame, TGLabel, TGLVEntry, TGTextButton, TGTextEntry, TGTextLBEntry, TKey, TMapFile, TNamed, TPad, TPair, TParallelCoordSelect, TParticle, TPaveLabel, TPrimary, TQCommand, TRootIconList, and TVirtualPad.

Definition at line 507 of file TObject.cxx.

GetTUnfoldVersion()

const char * TUnfold::GetTUnfoldVersion ( void )

staticinherited

return a string describing the TUnfold version

The version is reported in the form Vmajor.minor Changes of the minor version number typically correspond to bug-fixes. Changes of the major version may result in adding or removing data attributes, such that the streamer methods are not compatible between different major versions.

Definition at line 3717 of file TUnfold.cxx.

GetUniqueID()

UInt_t TObject::GetUniqueID ( ) const

virtualinherited

Return the unique object id.

Definition at line 480 of file TObject.cxx.

GetVxx()

const TMatrixDSparse * TUnfold::GetVxx ( void ) const

inlineprotectedinherited

covariance matrix of the result

Definition at line 244 of file TUnfold.h.

GetVxxInv()

const TMatrixDSparse * TUnfold::GetVxxInv ( void ) const

inlineprotectedinherited

inverse of covariance matrix of the result

Definition at line 246 of file TUnfold.h.

GetVyyInv()

const TMatrixDSparse * TUnfold::GetVyyInv ( void ) const

inlineprotectedinherited

inverse of covariance matrix of the data y

Definition at line 260 of file TUnfold.h.

GetX()

const TMatrixD * TUnfold::GetX ( void ) const

inlineprotectedinherited

vector of the unfolding result

Definition at line 242 of file TUnfold.h.

HandleTimer()

Bool_t TObject::HandleTimer ( TTimer * timer )

virtualinherited

Execute action in response of a timer timing out.

This method must be overridden if an object has to react to timers.

Reimplemented in TGCommandPlugin, TGDNDManager, TGFileContainer, TGHtml, TGLEventHandler, TGPopupMenu, TGraphTime, TGScrollBar, TGShutter, TGTextEdit, TGTextEditor, TGTextEntry, TGTextView, TGToolTip, TGuiBldDragManager, TGWindow, and TTreeViewer.

Definition at line 516 of file TObject.cxx.

Hash()

ULong_t TObject::Hash ( ) const

virtualinherited

Return hash value for this object.

Note: If this routine is overloaded in a derived class, this derived class should also add

ROOT::CallRecursiveRemoveIfNeeded(*this)

Otherwise, when RecursiveRemove is called (by ~TObject or example) for this type of object, the transversal of THashList and THashTable containers will will have to be done without call Hash (and hence be linear rather than logarithmic complexity). You will also see warnings like

Error in <ROOT::Internal::TCheckHashRecursiveRemoveConsistency::CheckRecursiveRemove>: The class SomeName overrides
TObject::Hash but does not call TROOT::RecursiveRemove in its destructor.

Reimplemented in RooLinkedList, TASImagePlugin, TASPluginGS, TCollection, TEnvRec, TGObject, TGPicture, TIconBoxThumb, TImagePlugin, TNamed, TObjString, TPad, TPair, TParameter< AParamType >, TParameter< Long64_t >, TPave, and TStatistic.

Definition at line 539 of file TObject.cxx.

HasInconsistentHash()

Bool_t TObject::HasInconsistentHash ( ) const

inlineinherited

Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e.

missing call to RecursiveRemove in destructor).

Note: Since the consistency is only tested for during inserts, this routine will return true for object that have never been inserted whether or not they have a consistent setup. This has no negative side-effect as searching for the object with the right or wrong Hash will always yield a not-found answer (Since anyway no hash can be guaranteed unique, there is always a check)

Definition at line 366 of file TObject.h.

Info()

void TObject::Info ( const char * location, const char * fmt, ... ) const

virtualinherited

Issue info message.

Use "location" to specify the method where the warning occurred. Accepts standard printf formatting arguments.

Definition at line 1072 of file TObject.cxx.

InheritsFrom() [1/2]

Bool_t TObject::InheritsFrom ( const char * classname ) const

virtualinherited

Returns kTRUE if object inherits from class "classname".

Reimplemented in TClass.

Definition at line 549 of file TObject.cxx.

InheritsFrom() [2/2]

Bool_t TObject::InheritsFrom ( const TClass * cl ) const

virtualinherited

Returns kTRUE if object inherits from TClass cl.

Reimplemented in TClass.

Definition at line 557 of file TObject.cxx.

InitTUnfold()

void TUnfold::InitTUnfold ( void )

privateinherited

initialize data menbers, for use in constructors

Definition at line 144 of file TUnfold.cxx.

InitTUnfoldSys()

void TUnfoldSys::InitTUnfoldSys ( void )

privateinherited

Definition at line 617 of file TUnfoldSys.cxx.

Inspect()

void TObject::Inspect ( ) const

virtualinherited

Dump contents of this object in a graphics canvas.

Same action as Dump but in a graphical form. In addition pointers to other objects can be followed.

The following picture is the Inspect of a histogram object:

Reimplemented in ROOT::Experimental::XRooFit::xRooNode, TGFrame, TInspectorObject, and TSystemFile.

Definition at line 570 of file TObject.cxx.

InvertBit()

void TObject::InvertBit ( UInt_t f )

inlineinherited

Definition at line 206 of file TObject.h.

InvertMSparseSymmPos()

TMatrixDSparse * TUnfold::InvertMSparseSymmPos ( const TMatrixDSparse * A, Int_t * rankPtr ) const

protectedinherited

get the inverse or pseudo-inverse of a positive, sparse matrix

Parameters

[in]	A	the sparse matrix to be inverted, has to be positive
[in,out]	rankPtr	if zero, suppress calculation of pseudo-inverse otherwise the rank of the matrix is returned in *rankPtr

return value: 0 or a new sparse matrix

• if(rankPtr==nullptr) return the inverse if it exists, or return 0
• else return a (pseudo-)inverse and store the rank of the matrix in *rankPtr

the matrix inversion is optimized in performance for the case where a large submatrix of A is diagonal

Definition at line 992 of file TUnfold.cxx.

IsA()

TClass * TUnfoldDensity::IsA ( ) const

inlineoverridevirtual

Returns

TClass describing current object

Reimplemented from TUnfold.

Definition at line 205 of file TUnfoldDensity.h.

IsDestructed()

Bool_t TObject::IsDestructed ( ) const

inlineinherited

IsDestructed.

Note

This function must be non-virtual as it can be used on destructed (but not yet modified) memory. This is used for example in TClonesArray to record the element that have been destructed but not deleted and thus are ready for re-use (by operator new with placement).

Returns

true if this object's destructor has been run.

Definition at line 186 of file TObject.h.

IsEqual()

Bool_t TObject::IsEqual ( const TObject * obj ) const

virtualinherited

Default equal comparison (objects are equal if they have the same address in memory).

More complicated classes might want to override this function.

Reimplemented in TGObject, TObjString, TPair, and TQCommand.

Definition at line 589 of file TObject.cxx.

IsFolder()

Bool_t TObject::IsFolder ( ) const

virtualinherited

Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).

Reimplemented in ROOT::Experimental::XRooFit::xRooNode, ROOT::Internal::THnBaseBrowsable, TApplicationRemote, TAxis3D, TBaseClass, TBranch, TBranchClones, TBranchElement, TBranchObject, TBranchSTL, TBrowserObject, TCanvas, TClass, TCollection, TDatabasePDG, TDirectory, TFolder, TGeoManager, TGeometry, TGeoNode, TGeoNodeMatrix, TGeoOverlap, TGeoTrack, TGeoVolume, THbookFile, THbookKey, THnBase, TKey, TMapFile, TMultiDimFit, TNode, TPad, TPair, TParticleClassPDG, TPrincipal, TRemoteObject, TROOT, TRootIconList, TSPlot, TSystemDirectory, TTask, TTree, and TVirtualBranchBrowsable.

Definition at line 579 of file TObject.cxx.

IsOnHeap()

Bool_t TObject::IsOnHeap ( ) const

inlineinherited

Definition at line 160 of file TObject.h.

IsSortable()

virtual Bool_t TObject::IsSortable ( ) const

inlinevirtualinherited

Reimplemented in RooAbsArg, RooDouble, TCollection, TFileInfo, TGeoBranchArray, TGeoOverlap, TGFSFrameElement, TGLBFrameElement, TNamed, TObjString, TParameter< AParamType >, TParameter< Long64_t >, TPave, TStructNode, TStructNodeProperty, TUri, and TUrl.

Definition at line 158 of file TObject.h.

IsZombie()

Bool_t TObject::IsZombie ( ) const

inlineinherited

Definition at line 161 of file TObject.h.

ls()

void TObject::ls ( Option_t * option = "" ) const

virtualinherited

The ls function lists the contents of a class on stdout.

Ls output is typically much less verbose then Dump().

Reimplemented in ROOT::Detail::TSchemaRuleSet, ROOT::Experimental::XRooFit::xRooBrowser, ROOT::TSchemaRule, TAnnotation, TApplication, TBox, TCanvas, TChain, TChainElement, TClass, TClassTree, TCollection, TColor, TDirectory, TDirectoryFile, TEllipse, TFile, TFolder, TFree, TFriendElement, TFunction, TGeometry, TGeoNode, TGFrameElement, TGLayoutHints, THbookFile, THStack, TImage, TKey, TLine, TMapFile, TMarker, TNamed, TNode, TPad, TParameter< AParamType >, TParameter< Long64_t >, TPave, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TQCommand, TQConnection, TQConnectionList, TQSlot, TQUndoManager, TROOT, TStatistic, TStreamerBase, TStreamerElement, TStreamerInfo, TStreamerSTL, TTask, TText, TVirtualPad, and TVirtualStreamerInfo.

Definition at line 598 of file TObject.cxx.

MakeZombie()

void TObject::MakeZombie ( )

inlineprotectedinherited

Definition at line 55 of file TObject.h.

MayNotUse()

void TObject::MayNotUse ( const char * method ) const

inherited

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).

Definition at line 1160 of file TObject.cxx.

MultiplyMSparseM()

TMatrixDSparse * TUnfold::MultiplyMSparseM ( const TMatrixDSparse * a, const TMatrixD * b ) const

protectedinherited

multiply sparse matrix and a non-sparse matrix

Parameters

[in]	a	sparse matrix
[in]	b	matrix

returns a new sparse matrix a*b.
A replacement for: new TMatrixDSparse(a,TMatrixDSparse::kMult,b) the root implementation had problems in older versions of root

Definition at line 760 of file TUnfold.cxx.

MultiplyMSparseMSparse()

TMatrixDSparse * TUnfold::MultiplyMSparseMSparse ( const TMatrixDSparse * a, const TMatrixDSparse * b ) const

protectedinherited

multiply two sparse matrices

Parameters

[in]	a	sparse matrix
[in]	b	sparse matrix

returns a new sparse matrix a*b.
A replacement for: new TMatrixDSparse(a,TMatrixDSparse::kMult,b) the root implementation had problems in older versions of root

Definition at line 603 of file TUnfold.cxx.

MultiplyMSparseMSparseTranspVector()

TMatrixDSparse * TUnfold::MultiplyMSparseMSparseTranspVector ( const TMatrixDSparse * m1, const TMatrixDSparse * m2, const TMatrixTBase< Double_t > * v ) const

protectedinherited

calculate a sparse matrix product M1*V*M2^T where the diagonal matrix V is given by a vector

Parameters

[in]	m1	pointer to sparse matrix with dimension I*K
[in]	m2	pointer to sparse matrix with dimension J*K
[in]	v	pointer to vector (matrix) with dimension K*1

returns a sparse matrix R with elements r_ij=Σ_kM1_ikV_kM2_jk

Definition at line 819 of file TUnfold.cxx.

MultiplyMSparseTranspMSparse()

TMatrixDSparse * TUnfold::MultiplyMSparseTranspMSparse ( const TMatrixDSparse * a, const TMatrixDSparse * b ) const

protectedinherited

multiply a transposed Sparse matrix with another Sparse matrix

Parameters

[in]	a	sparse matrix (to be transposed)
[in]	b	sparse matrix

returns a new sparse matrix a^T*b
this is a replacement for the root constructors new TMatrixDSparse(TMatrixDSparse(TMatrixDSparse::kTransposed,*a),TMatrixDSparse::kMult,*b)

Definition at line 677 of file TUnfold.cxx.

Notify()

Bool_t TObject::Notify ( )

virtualinherited

This method must be overridden to handle object notification (the base implementation is no-op).

Different objects in ROOT use the Notify method for different purposes, in coordination with other objects that call this method at the appropriate time.

For example, TLeaf uses it to load class information; TBranchRef to load contents of referenced branches TBranchRef; most notably, based on Notify, TChain implements a callback mechanism to inform interested parties when it switches to a new sub-tree.

Reimplemented in h1analysis, h1analysisTreeReader, TARInterruptHandler, TASInputHandler, TASInterruptHandler, TASLogHandler, TASSigPipeHandler, TBlinkTimer, TBranchElement, TBranchRef, TBreakLineCom, TBrowserTimer, TCollection, TDelCharCom, TDelTextCom, TFileHandler, TGContainerKeyboardTimer, TGContainerScrollTimer, TGInputHandler, TGLRedrawTimer, TGTextEditHist, TGuiBldDragManagerRepeatTimer, TIdleTimer, TInsCharCom, TInsTextCom, TInterruptHandler, TLeafObject, TMessageHandler, TNotifyLink< Type >, TNotifyLink< RNoCleanupNotifierHelper >, TNotifyLink< ROOT::Detail::TBranchProxy >, TNotifyLink< TTreeReader >, TPopupDelayTimer, TProcessEventTimer, TRefTable, TRepeatTimer, TSBRepeatTimer, TSelector, TSelectorDraw, TSelectorEntries, TSignalHandler, TSingleShotCleaner, TSocketHandler, TStdExceptionHandler, TSysEvtHandler, TTermInputHandler, TThreadTimer, TTimeOutTimer, TTimer, TTipDelayTimer, TTree, TTreeFormula, TTreeFormulaManager, TTreeReader, TViewTimer, and TViewUpdateTimer.

Definition at line 618 of file TObject.cxx.

Obsolete()

void TObject::Obsolete ( const char * method, const char * asOfVers, const char * removedFromVers ) const

inherited

Use this method to declare a method obsolete.

Specify as of which version the method is obsolete and as from which version it will be removed.

Definition at line 1169 of file TObject.cxx.

operator delete() [1/3]

void TObject::operator delete ( void * ptr, size_t size )

inherited

Operator delete for sized deallocation.

Definition at line 1234 of file TObject.cxx.

operator delete() [2/3]

void TObject::operator delete ( void * ptr )

inherited

Operator delete.

Definition at line 1212 of file TObject.cxx.

operator delete() [3/3]

void TObject::operator delete ( void * ptr, void * vp )

inherited

Only called by placement new when throwing an exception.

Definition at line 1266 of file TObject.cxx.

operator delete[]() [1/3]

void TObject::operator delete[] ( void * ptr, size_t size )

inherited

Operator delete [] for sized deallocation.

Definition at line 1245 of file TObject.cxx.

operator delete[]() [2/3]

void TObject::operator delete[] ( void * ptr )

inherited

Operator delete [].

Definition at line 1223 of file TObject.cxx.

operator delete[]() [3/3]

void TObject::operator delete[] ( void * ptr, void * vp )

inherited

Only called by placement new[] when throwing an exception.

Definition at line 1274 of file TObject.cxx.

operator new() [1/2]

void * TObject::operator new ( size_t sz )

inlineinherited

Definition at line 189 of file TObject.h.

operator new() [2/2]

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

inlineinherited

Definition at line 191 of file TObject.h.

operator new[]() [1/2]

void * TObject::operator new[] ( size_t sz )

inlineinherited

Definition at line 190 of file TObject.h.

operator new[]() [2/2]

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

inlineinherited

Definition at line 192 of file TObject.h.

Paint()

void TObject::Paint ( Option_t * option = "" )

virtualinherited

This method must be overridden if a class wants to paint itself.

The difference between Paint() and Draw() is that when a object draws itself it is added to the display list of the pad in which it is drawn (and automatically redrawn whenever the pad is redrawn). While paint just draws the object without adding it to the pad display list.

Reimplemented in ROOT::Experimental::RTreeMapPainter, ROOT::RGeoPainter, TAnnotation, TArrow, TASImage, TASPaletteEditor::LimitLine, TASPaletteEditor::PaintPalette, TAxis3D, TBits, TBox, TButton, TCanvas, TClassTree, TCollection, TColorWheel, TCrown, TDiamond, TDirectory, TEfficiency, TEllipse, TEveArrow, TEveCaloViz, TEveDigitSet, TEveGeoShape, TEveGeoTopNode, TEvePlot3D, TEvePointSet, TEveProjectionAxes, TEveScene, TEveShape, TEveStraightLineSet, TEveText, TEveTriangleSet, TExec, TF1, TF2, TF3, TFile, TFileDrawMap, TFrame, TGaxis, TGenerator, TGeoBoolNode, TGeoIntersection, TGeoNode, TGeoOverlap, TGeoPainter, TGeoPhysicalNode, TGeoShape, TGeoSubtraction, TGeoTrack, TGeoUnion, TGeoVGShape, TGeoVolume, TGL5DDataSet, TGLHistPainter, TGLParametricEquation, TGLTH3Composition, TGraph2D, TGraph2DPainter, TGraph, TGraphEdge, TGraphNode, TGraphPolargram, TGraphTime, TH1, THistPainter, THStack, TLatex, TLegend, TLine, TMacro, TMarker3DBox, TMarker, TMathText, TMultiGraph, TNode, TNodeDiv, TPad, TPaletteAxis, TParallelCoord, TParallelCoordRange, TParallelCoordVar, TParticle, TPave, TPaveLabel, TPaveStats, TPavesText, TPaveText, TPie, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TPrimary, TRatioPlot, TScatter2D, TScatter, TShape, TSpectrum2Painter, TSpider, TSpline, TSQLFile, TStyle, TText, TTreePerfStats, TVirtualGeoPainter, TVirtualGeoTrack, TVirtualHistPainter, TVirtualPad, TWbox, and TXMLFile.

Definition at line 631 of file TObject.cxx.

Pop()

void TObject::Pop ( )

virtualinherited

Pop on object drawn in a pad to the top of the display list.

I.e. it will be drawn last and on top of all other primitives.

Reimplemented in TFrame, TPad, and TVirtualPad.

Definition at line 640 of file TObject.cxx.

PrepareCorrEmat()

TMatrixDSparse * TUnfoldSys::PrepareCorrEmat ( const TMatrixDSparse * m1, const TMatrixDSparse * m2, const TMatrixDSparse * dsys )

protectedvirtualinherited

propagate correlated systematic shift to an output vector

Parameters

[in]	m1	coefficients
[in]	m2	coeffiicients
[in]	dsys	matrix of correlated shifts from this source

Definition at line 976 of file TUnfoldSys.cxx.

PrepareSysError()

void TUnfoldSys::PrepareSysError ( void )

protectedvirtualinherited

Matrix calculations required to propagate systematic errors.

Definition at line 662 of file TUnfoldSys.cxx.

PrepareUncorrEmat()

TMatrixDSparse * TUnfoldSys::PrepareUncorrEmat ( const TMatrixDSparse * m_0, const TMatrixDSparse * m_1 )

protectedvirtualinherited

propagate uncorrelated systematic errors to a covariance matrix

Parameters

[in]	m_0	coefficients for error propagation
[in]	m_1	coefficients for error propagation

returns the covariance matrix

Definition at line 776 of file TUnfoldSys.cxx.

Print()

void TObject::Print ( Option_t * option = "" ) const

virtualinherited

This method must be overridden when a class wants to print itself.

Reimplemented in Roo1DTable, RooAbsArg, RooAbsBinning, RooAbsCollection, RooAbsData, RooAbsDataStore, RooAbsGenContext, RooCatType, RooCmdArg, RooCurve, RooEllipse, RooFitResult, RooGenFitStudy, RooHist, RooLinkedList, RooMsgService, RooNumGenConfig, RooNumIntConfig, RooPlot, RooSharedProperties, RooStats::ModelConfig, ROOT::Experimental::REveTrans, ROOT::Experimental::XRooFit::xRooNLLVar::xRooHypoPoint, ROOT::Experimental::XRooFit::xRooNLLVar::xRooHypoSpace, ROOT::Experimental::XRooFit::xRooNode, ROOT::v5::TFormula, RooWorkspace, TAnnotation, TApplicationRemote, TAttParticle, TBenchmark, TBits, TBox, TBranch, TBranchClones, TBranchElement, TBranchObject, TBranchRef, TBranchSTL, TChain, TClassTable, TCling, TCollection, TColor, TDatabasePDG, TDecompBase, TDecompBK, TDecompChol, TDecompLU, TDecompQRH, TDecompSparse, TDecompSVD, TDirectory, TEllipse, TEnv, TEventList, TEveTrans, TF1, TFile, TFileCacheRead, TFileCacheWrite, TFileCollection, TFileInfo, TFileInfoMeta, TFitResult, TFoamCell, TFoamVect, TFormula, TFunction, TGCompositeFrame, TGDMLMatrix, TGeoBatemanSol, TGeoBorderSurface, TGeoBranchArray, TGeoDecayChannel, TGeoElement, TGeoElementRN, TGeoElementTable, TGeoIsotope, TGeoMatrix, TGeoOpticalSurface, TGeoOverlap, TGeoPhysicalNode, TGeoRegion, TGeoSkinSurface, TGeoTessellated, TGeoTrack, TGeoVolume, TGeoVoxelFinder, TGFont, TGFontPool, TGFrame, TGFrameElement, TGGC, TGGCPool, TGLayoutHints, TGMimeTypes, TGPicture, TGPicturePool, TGraph2D, TGraph2DAsymmErrors, TGraph2DErrors, TGraph, TGraphAsymmErrors, TGraphBentErrors, TGraphErrors, TGraphMultiErrors, TGTextEdit, TGWindow, TH1, THashTable, THbookTree, THelix, THnBase, THStack, TInetAddress, TKey, TLegend, TLegendEntry, TLine, TLorentzVector, TMacro, TMapFile, TMarker, TMatrixTBase< Element >, TMatrixTBase< Double_t >, TMatrixTBase< Float_t >, TMemFile, TMessageHandler, TMultiDimFit, TMultiGraph, TMVA::Event, TMVA::Option< T >, TMVA::Option< T * >, TMVA::OptionBase, TMVA::PDEFoamCell, TMVA::PDEFoamVect, TMVA::TNeuron, TNamed, TObjectTable, TObjString, TPad, TParallelCoordRange, TParallelCoordVar, TParameter< AParamType >, TParameter< Long64_t >, TParticle, TParticleClassPDG, TParticlePDG, TPave, TPaveText, TPluginHandler, TPluginManager, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TPrimary, TPrincipal, TQpDataDens, TQpDataSparse, TQpVar, TQSlot, TQuaternion, TRolke, TRootBrowserHistoryCursor, TScatter2D, TScatter, TSpectrum2, TSpectrum3, TSpectrum, TSQLColumnInfo, TSQLFile, TSQLStructure, TSQLTableInfo, TStatistic, TStopwatch, TStreamerInfoActions::TActionSequence, TText, TTree, TTreeCache, TTreeCacheUnzip, TTreeIndex, TTreePerfStats, TUri, TUrl, TVector2, TVector3, TVectorT< Element >, TVectorT< Double_t >, TVectorT< Float_t >, TVirtualPad, TXMLFile, TXTRU, TZIPFile, and TZIPMember.

Definition at line 661 of file TObject.cxx.

Read()

Int_t TObject::Read ( const char * name )

virtualinherited

Read contents of object with specified name from the current directory.

First the key with the given name is searched in the current directory, next the key buffer is deserialized into the object. The object must have been created before via the default constructor. See TObject::Write().

Reimplemented in TBuffer, TKey, TKeySQL, and TKeyXML.

Definition at line 673 of file TObject.cxx.

RecursiveRemove()

void TObject::RecursiveRemove ( TObject * obj )

virtualinherited

Recursively remove this object from a list.

Typically implemented by classes that can contain multiple references to a same object.

Reimplemented in RooAbsCollection, RooAbsData, RooLinkedList, RooMCStudy, ROOT::Internal::TCheckHashRecursiveRemoveConsistency, ROOT::RBrowserDataCleanup, RooWorkspace, TBrowser, TChain, TCling, TCollection, TDialogCanvas, TDirectory, TEfficiency, TFileMerger, TFitEditor, TFolder, TFriendElement, TGedEditor, TGeometry, TGFileBrowser, TGraph2D, TGraph, TH1, TH1Editor, TH2Editor, THashList, THistPainter, THStack, TInspectCanvas, TLegend, TList, TListOfDataMembers, TListOfEnums, TListOfEnumsWithLock, TListOfFunctions, TListOfFunctionTemplates, TMultiGraph, TNode, TObjArray, TObjectRefSpy, TObjectSpy, TPad, TProcessID, TROOT, TRootBrowser, TRootBrowserHistory, TRootBrowserLite, TRootContextMenu, TTree, TTreePlayer, TViewPubDataMembers, TViewPubFunctions, and TVirtualPad.

Definition at line 684 of file TObject.cxx.

RegularizeBins()

Int_t TUnfold::RegularizeBins ( int start, int step, int nbin, ERegMode regmode )

inherited

add regularisation conditions for a group of bins

Parameters

[in]	start	first bin number
[in]	step	step size
[in]	nbin	number of bins
[in]	regmode	regularisation mode (one of: kRegModeSize, kRegModeDerivative, kRegModeCurvature)

add regularisation conditions for a group of equidistant bins. There are nbin bins, starting with bin start and with a distance of step between bins.

Return value: number of regularisation conditions which could not be added.
Conditions which are not added typically correspond to bin numbers where the truth can not be unfolded (either response matrix is empty or the data do not constrain).

Definition at line 2143 of file TUnfold.cxx.

RegularizeBins2D()

Int_t TUnfold::RegularizeBins2D ( int start_bin, int step1, int nbin1, int step2, int nbin2, ERegMode regmode )

inherited

add regularisation conditions for 2d unfolding

Parameters

[in]	start_bin	first bin number
[in]	step1	step size, 1st dimension
[in]	nbin1	number of bins, 1st dimension
[in]	step2	step size, 2nd dimension
[in]	nbin2	number of bins, 2nd dimension
[in]	regmode	regularisation mode (one of: kRegModeSize, kRegModeDerivative, kRegModeCurvature)

add regularisation conditions for a grid of bins. The start bin is start_bin. Along the first (second) dimension, there are nbin1 (nbin2) bins and adjacent bins are spaced by step1 (step2) units.

Return value: number of regularisation conditions which could not be added. Conditions which are not added typically correspond to bin numbers where the truth can not be unfolded (either response matrix is empty or the data do not constrain).

Definition at line 2204 of file TUnfold.cxx.

RegularizeCurvature()

Int_t TUnfold::RegularizeCurvature ( int left_bin, int center_bin, int right_bin, Double_t scale_left = 1.0, Double_t scale_right = 1.0 )

inherited

add a regularisation condition on the curvature of three truth bin

Parameters

[in]	left_bin	bin number
[in]	center_bin	bin number
[in]	right_bin	bin number
[in]	scale_left	(default=1) scale factor
[in]	scale_right	(default=1) scale factor

this adds one row to L, where the element left_bin takes the value -scale_left, the element right_bin takes the value -scale_right and the element center_bin takes the value scale_left+scale_right

return value: 0 if ok, 1 if the condition has not been added. Conditions which are not added typically correspond to bin numbers where the truth can not be unfolded (either response matrix is empty or the data do not constrain).

The RegularizeXXX() methods can be used to set up a custom matrix of regularisation conditions. In this case, start with an empty matrix L (argument regmode=kRegModeNone in the constructor)

Definition at line 2098 of file TUnfold.cxx.

RegularizeDerivative()

Int_t TUnfold::RegularizeDerivative ( int left_bin, int right_bin, Double_t scale = 1.0 )

inherited

add a regularisation condition on the difference of two truth bin

Parameters

[in]	left_bin	bin number
[in]	right_bin	bin number
[in]	scale	(default=1) scale factor

this adds one row to L, where the element left_bin takes the value -scale and the element right_bin takes the value +scale

return value: 0 if ok, 1 if the condition has not been added. Conditions which are not added typically correspond to bin numbers where the truth can not be unfolded (either response matrix is empty or the data do not constrain).

The RegularizeXXX() methods can be used to set up a custom matrix of regularisation conditions. In this case, start with an empty matrix L (argument regmode=kRegModeNone in the constructor)

Definition at line 2059 of file TUnfold.cxx.

RegularizeDistribution()

void TUnfoldDensity::RegularizeDistribution	(	ERegMode	regmode,
		EDensityMode	densityMode,
		const char *	distribution,
		const char *	axisSteering )

set up regularisation conditions

Parameters

[in]	regmode	basic regularisation mode (see class TUnfold)
[in]	densityMode	how to apply bin-wise factors
[in]	distribution	name of the TUnfoldBinning node for which the regularisation conditions shall be set (zero matches all nodes)
[in]	axisSteering	regularisation fine-tuning

axisSteering is a string with several tokens, separated by a semicolon: "axisName[options];axisName[options];...".

axisName

the name of an axis. The special name * matches all. So the argument distribution selects one (or all) distributions. Witin the selected distribution(s), steering options may be specified for each axis (or for all axes) to define the regularisation conditions.

options

one or several character as follows
u : exclude underflow bin from derivatives along this axis
o : exclude overflow bin from derivatives along this axis
U : exclude underflow bin
O : exclude overflow bin
b : use bin width for derivative calculation
B : same as 'b', in addition normalize to average bin width
N : completely exclude derivatives along this axis
p : axis is periodic (e.g. azimuthal angle), so include derivatives built from combinations involving bins at both ends of the axis "wrap around"

example: axisSteering="*[UOB]" uses bin widths to calculate derivatives but underflow/overflow bins are not regularized

Definition at line 386 of file TUnfoldDensity.cxx.

RegularizeDistributionRecursive()

void TUnfoldDensity::RegularizeDistributionRecursive ( const TUnfoldBinning * binning, ERegMode regmode, EDensityMode densityMode, const char * distribution, const char * axisSteering )

protected

recursively add regularisation conditions for this node and its children

Parameters

[in]	binning	current node
[in]	regmode	regularisation mode
[in]	densityMode	type of regularisation scaling
[in]	distribution	target distribution(s) name
[in]	axisSteering	steering within the target distribution(s)

Definition at line 403 of file TUnfoldDensity.cxx.

RegularizeOneDistribution()

void TUnfoldDensity::RegularizeOneDistribution ( const TUnfoldBinning * binning, ERegMode regmode, EDensityMode densityMode, const char * axisSteering )

protected

regularize the distribution fof the given node

Parameters

[in]	binning	current node
[in]	regmode	regularisation mode
[in]	densityMode	type of regularisation scaling
[in]	axisSteering	detailed steering for the axes of the distribution

Definition at line 424 of file TUnfoldDensity.cxx.

RegularizeSize()

Int_t TUnfold::RegularizeSize ( int bin, Double_t scale = 1.0 )

inherited

add a regularisation condition on the magnitude of a truth bin

Parameters

[in]	bin	bin number
[in]	scale	(default=1) scale factor

this adds one row to L, where the element bin takes the value scale

return value: 0 if ok, 1 if the condition has not been added. Conditions which are not added typically correspond to bin numbers where the truth can not be unfolded (either response matrix is empty or the data do not constrain).

The RegularizeXXX() methods can be used to set up a custom matrix of regularisation conditions. In this case, start with an empty matrix L (argument regmode=kRegModeNone in the constructor)

Definition at line 2025 of file TUnfold.cxx.

ResetBit()

void TObject::ResetBit ( UInt_t f )

inlineinherited

Definition at line 203 of file TObject.h.

SaveAs()

void TObject::SaveAs ( const char * filename = "", Option_t * option = "" ) const

virtualinherited

Save this object in the file specified by filename.

• if "filename" contains ".root" the object is saved in filename as root binary file.
• if "filename" contains ".xml" the object is saved in filename as a xml ascii file.
• if "filename" contains ".cc" the object is saved in filename as C code independent from ROOT. The code is generated via SavePrimitive(). Specific code should be implemented in each object to handle this option. Like in TF1::SavePrimitive().

• otherwise the object is written to filename as a CINT/C++ script. The C++ code to rebuild this object is generated via SavePrimitive(). The "option" parameter is passed to SavePrimitive. By default it is an empty string. It can be used to specify the Draw option in the code generated by SavePrimitive.

  The function is available via the object context menu.

Reimplemented in ROOT::Experimental::XRooFit::xRooNode, TClassTree, TFolder, TGeoVolume, TGObject, TGraph, TH1, TPad, TPaveClass, TSpline3, TSpline5, TSpline, TTreePerfStats, and TVirtualPad.

Definition at line 708 of file TObject.cxx.

SavePrimitive()

void TObject::SavePrimitive ( std::ostream & out, Option_t * option = "" )

virtualinherited

Save a primitive as a C++ statement(s) on output stream "out".

Reimplemented in TAnnotation, TArc, TArrow, TASImage, TAxis3D, TBox, TButton, TCanvas, TChain, TCrown, TCurlyArc, TCurlyLine, TCutG, TDiamond, TEfficiency, TEllipse, TExec, TF12, TF1, TF2, TF3, TFrame, TGaxis, TGButton, TGButtonGroup, TGCanvas, TGCheckButton, TGColorSelect, TGColumnLayout, TGComboBox, TGCompositeFrame, TGContainer, TGDockableFrame, TGDoubleHSlider, TGDoubleVSlider, TGedMarkerSelect, TGedPatternSelect, TGeoArb8, TGeoBBox, TGeoBoolNode, TGeoCombiTrans, TGeoCompositeShape, TGeoCone, TGeoConeSeg, TGeoCtub, TGeoDecayChannel, TGeoElementRN, TGeoEltu, TGeoGtra, TGeoHalfSpace, TGeoHMatrix, TGeoHype, TGeoIdentity, TGeoIntersection, TGeoMaterial, TGeoMedium, TGeoMixture, TGeoPara, TGeoParaboloid, TGeoPatternCylPhi, TGeoPatternCylR, TGeoPatternParaX, TGeoPatternParaY, TGeoPatternParaZ, TGeoPatternSphPhi, TGeoPatternSphR, TGeoPatternSphTheta, TGeoPatternTrapZ, TGeoPatternX, TGeoPatternY, TGeoPatternZ, TGeoPcon, TGeoPgon, TGeoRotation, TGeoScaledShape, TGeoShapeAssembly, TGeoSphere, TGeoSubtraction, TGeoTessellated, TGeoTorus, TGeoTranslation, TGeoTrap, TGeoTrd1, TGeoTrd2, TGeoTube, TGeoTubeSeg, TGeoUnion, TGeoVolume, TGeoXtru, TGFileContainer, TGFont, TGFrame, TGFSComboBox, TGGC, TGGroupFrame, TGHButtonGroup, TGHorizontal3DLine, TGHorizontalFrame, TGHorizontalLayout, TGHProgressBar, TGHScrollBar, TGHSlider, TGHSplitter, TGHtml, TGIcon, TGLabel, TGLayoutHints, TGLineStyleComboBox, TGLineWidthComboBox, TGListBox, TGListDetailsLayout, TGListLayout, TGListTree, TGListView, TGLVContainer, TGMainFrame, TGMatrixLayout, TGMdiFrame, TGMdiMainFrame, TGMdiMenuBar, TGMenuBar, TGMenuTitle, TGNumberEntry, TGNumberEntryField, TGPictureButton, TGPopupMenu, TGProgressBar, TGRadioButton, TGraph2D, TGraph2DAsymmErrors, TGraph2DErrors, TGraph, TGraphAsymmErrors, TGraphBentErrors, TGraphEdge, TGraphErrors, TGraphMultiErrors, TGraphNode, TGraphPolar, TGraphPolargram, TGraphStruct, TGroupButton, TGRowLayout, TGShapedFrame, TGShutter, TGShutterItem, TGSplitFrame, TGStatusBar, TGTab, TGTabLayout, TGTableLayout, TGTableLayoutHints, TGTextButton, TGTextEdit, TGTextEntry, TGTextLBEntry, TGTextView, TGTileLayout, TGToolBar, TGTransientFrame, TGTripleHSlider, TGTripleVSlider, TGVButtonGroup, TGVertical3DLine, TGVerticalFrame, TGVerticalLayout, TGVFileSplitter, TGVProgressBar, TGVScrollBar, TGVSlider, TGVSplitter, TGXYLayout, TGXYLayoutHints, TH1, TH2Poly, THelix, THStack, TLatex, TLegend, TLine, TMacro, TMarker3DBox, TMarker, TMathText, TMultiGraph, TPad, TPaletteAxis, TParallelCoord, TParallelCoordVar, TPave, TPaveClass, TPaveLabel, TPaveStats, TPavesText, TPaveText, TPie, TPieSlice, TPolyLine3D, TPolyLine, TPolyMarker3D, TPolyMarker, TProfile2D, TProfile3D, TProfile, TRootContainer, TRootEmbeddedCanvas, TScatter2D, TScatter, TSlider, TSliderBox, TSpline3, TSpline5, TStyle, TText, TTreePerfStats, and TWbox.

Definition at line 858 of file TObject.cxx.

SavePrimitiveConstructor()

void TObject::SavePrimitiveConstructor ( std::ostream & out, TClass * cl, const char * variable_name, const char * constructor_agrs = "", Bool_t empty_line = kTRUE )

staticprotectedinherited

Save object constructor in the output stream "out".

Can be used as first statement when implementing SavePrimitive() method for the object

Definition at line 777 of file TObject.cxx.

SavePrimitiveDraw()

void TObject::SavePrimitiveDraw ( std::ostream & out, const char * variable_name, Option_t * option = nullptr )

staticprotectedinherited

Save invocation of primitive Draw() method Skipped if option contains "nodraw" string.

Definition at line 845 of file TObject.cxx.

SavePrimitiveVector()

TString TObject::SavePrimitiveVector ( std::ostream & out, const char * prefix, Int_t len, Double_t * arr, Int_t flag = 0 )

staticprotectedinherited

Save array in the output stream "out" as vector.

Create unique variable name based on prefix value Returns name of vector which can be used in constructor or in other places of C++ code If flag === kTRUE, just add empty line If flag === 111, check if array is empty and return nullptr or <vectorname>.data()

Definition at line 796 of file TObject.cxx.

ScaleColumnsByVector()

void TUnfoldSys::ScaleColumnsByVector ( TMatrixDSparse * m, const TMatrixTBase< Double_t > * v ) const

protectedinherited

scale columns of a matrix by the corresponding rows of a vector

[inout] m matrix

[in] v vector

the entries m_ij are multiplied by v_j.

Definition at line 1422 of file TUnfoldSys.cxx.

ScanLcurve()

Int_t TUnfold::ScanLcurve ( Int_t nPoint, Double_t tauMin, Double_t tauMax, TGraph ** lCurve, TSpline ** logTauX = nullptr, TSpline ** logTauY = nullptr, TSpline ** logTauCurvature = nullptr )

virtualinherited

scan the L curve, determine tau and unfold at the final value of tau

Parameters

[in]	nPoint	number of points used for the scan
[in]	tauMin	smallest tau value to study
[in]	tauMax	largest tau value to study. If tauMin=tauMax=nullptr, a scan interval is determined automatically.
[out]	lCurve	if nonzero, a new TGraph is returned, containing the L-curve
[out]	logTauX	if nonzero, a new TSpline is returned, to parameterize the L-curve's x-coordinates as a function of log10(tau)
[out]	logTauY	if nonzero, a new TSpline is returned, to parameterize the L-curve's y-coordinates as a function of log10(tau)
[out]	logTauCurvature	if nonzero, a new TSpline is returned of the L-curve curvature as a function of log10(tau)

return value: the coordinate number in the logTauX,logTauY graphs corresponding to the "final" choice of tau

Recommendation: always check logTauCurvature, it should be a peaked function (similar to a Gaussian), the maximum corresponding to the final choice of tau. Also, check the lCurve it should be approximately L-shaped. If in doubt, adjust tauMin and tauMax until the results are satisfactory.

Definition at line 2558 of file TUnfold.cxx.

ScanSURE()

Int_t TUnfold::ScanSURE ( Int_t nPoint, Double_t tauMin, Double_t tauMax, TGraph ** logTauSURE = nullptr, TGraph ** df_chi2A = nullptr, TGraph ** lCurve = nullptr )

virtualinherited

minimize Stein's unbiased risk estimator "SURE" using successive calls to DoUnfold at various tau.

Optionally, also the L-curve and its curvature are calculated for comparison. See description of GetSURE() See e.g. arXiv:1612.09415 for the definition of SURE

Parameters

[in]	nPoint	: number of points
[in]	tauMin	: lower end of scan-range
[in]	tauMax	: upper end of scan-range
[out]	logTauSURE	: scan result, SURE as a function of log(tau)
[out]	df_chi2A	: parametric plot of DF against chi2A
[out]	lCurve	: parametric plot (lCurve)

return value: index of the "best" point

if tauMin is less than zero of if tauMin is not loer than tauMax, then the scan range is determined automatically if tau=nullptr is included in the scan, then the first x-coordinate

Definition at line 3785 of file TUnfold.cxx.

ScanTau()

Int_t TUnfoldDensity::ScanTau ( Int_t nPoint, Double_t tauMin, Double_t tauMax, TSpline ** scanResult, Int_t mode = kEScanTauRhoAvg, const char * distribution = nullptr, const char * axisSteering = nullptr, TGraph ** lCurvePlot = nullptr, TSpline ** logTauXPlot = nullptr, TSpline ** logTauYPlot = nullptr )

virtual

scan a function wrt tau and determine the minimum

Parameters

[in]	nPoint	number of points to be scanned
[in]	tauMin	smallest tau value to study
[in]	tauMax	largest tau value to study
[out]	scanResult	the scanned function wrt log(tau)
[in]	mode	1st parameter for the scan function
[in]	distribution	2nd parameter for the scan function
[in]	projectionMode	3rd parameter for the scan function
[out]	lCurvePlot	for monitoring, shows the L-curve
[out]	logTauXPlot	for monitoring, L-curve(X) as a function of log(tau)
[out]	logTauYPlot	for monitoring, L-curve(Y) as a function of log(tau)

Return value: the coordinate number on the curve scanResult which corresponds to the minimum
The function is scanned by repeating the following steps nPoint times

1. Choose a value of tau
2. Perform the unfolding for this choice of tau, DoUnfold(tau)
3. Determinethe scan variable GetScanVariable()

The method GetScanVariable() defines scans of correlation coefficients, where mode is chosen from the enum EScanTauMode. In addition one may set distribution and/or projectionMode to refine the calculation of correlations (e.g. restrict the calcuation to the signal distribution and/or exclude underflow and overflow bins). See the documentation of GetScanVariable() for details. Alternative scan variables may be defined by overriding the GetScanVariable() method.
Automatic choice of scan range: if (tauMin,tauMax) do not correspond to a valid tau range (e.g. tauMin=tauMax=0.0) then the tau range is determined automatically. Use with care!

Definition at line 1354 of file TUnfoldDensity.cxx.

SetBias()

void TUnfold::SetBias ( const TH1 * bias )

inherited

set bias vector

Parameters

[in]

bias

histogram with new bias vector

the initial bias vector is determined from the response matrix but may be changed by using this method

Definition at line 1895 of file TUnfold.cxx.

SetBit() [1/2]

void TObject::SetBit ( UInt_t f )

inlineinherited

Definition at line 202 of file TObject.h.

SetBit() [2/2]

void TObject::SetBit ( UInt_t f, Bool_t set )

inherited

Set or unset the user status bits as specified in f.

Definition at line 888 of file TObject.cxx.

SetConstraint()

void TUnfold::SetConstraint ( EConstraint constraint )

inherited

set type of area constraint

results of a previous unfolding are reset

Definition at line 3211 of file TUnfold.cxx.

SetDrawOption()

void TObject::SetDrawOption ( Option_t * option = "" )

virtualinherited

Set drawing option for object.

This option only affects the drawing style and is stored in the option field of the TObjOptLink supporting a TPad's primitive list (TList). Note that it does not make sense to call object.SetDrawOption(option) before having called object.Draw().

Reimplemented in RooPlot, TAxis, TBrowser, TGedFrame, TGFrame, TPad, TPaveStats, TRootBrowserLite, TSystemDirectory, and TSystemFile.

Definition at line 871 of file TObject.cxx.

SetDtorOnly()

void TObject::SetDtorOnly ( void * obj )

staticinherited

Set destructor only flag.

Definition at line 1204 of file TObject.cxx.

SetEpsMatrix()

void TUnfold::SetEpsMatrix ( Double_t eps )

inherited

set numerical accuracy for Eigenvalue analysis when inverting matrices with rank problems

Definition at line 3703 of file TUnfold.cxx.

SetInput()

Int_t TUnfoldSys::SetInput ( const TH1 * input, Double_t scaleBias = 0.0, Double_t oneOverZeroError = 0.0, const TH2 * hist_vyy = nullptr, const TH2 * hist_vyy_inv = nullptr )

overridevirtualinherited

Define input data for subsequent calls to DoUnfold(tau).

Parameters

[in]	input	input distribution with uncertainties
[in]	scaleBias	(default=nullptr) scale factor applied to the bias
[in]	oneOverZeroError	(default=nullptr) for bins with zero error, this number defines 1/error.
[in]	hist_vyy	(default=nullptr) if non-zero, this defines the data covariance matrix
[in]	hist_vyy_inv	(default=nullptr) if non-zero and hist_vyy is set, defines the inverse of the data covariance matrix. This feature can be useful for repeated unfoldings in cases where the inversion of the input covariance matrix is lengthy

Return value: nError1+10000*nError2

• nError1: number of bins where the uncertainty is zero. these bins either are not used for the unfolding (if oneOverZeroError==nullptr) or 1/uncertainty is set to oneOverZeroError.
• nError2: return values>10000 are fatal errors, because the unfolding can not be done. The number nError2 corresponds to the number of truth bins which are not constrained by data points.

Reimplemented from TUnfold.

Definition at line 465 of file TUnfoldSys.cxx.

SetObjectStat()

void TObject::SetObjectStat ( Bool_t stat )

staticinherited

Turn on/off tracking of objects in the TObjectTable.

Definition at line 1188 of file TObject.cxx.

SetTauError()

void TUnfoldSys::SetTauError ( Double_t delta_tau )

inherited

Specify an uncertainty on tau.

Parameters

[in]

delta_tau

new uncertainty on tau

The default is to have no uncertyainty on tau.

Definition at line 1006 of file TUnfoldSys.cxx.

SetUniqueID()

void TObject::SetUniqueID ( UInt_t uid )

virtualinherited

Set the unique object id.

Definition at line 899 of file TObject.cxx.

Streamer()

void TUnfoldDensity::Streamer ( TBuffer & R__b )

overridevirtual

Stream an object of class TObject.

Reimplemented from TUnfold.

StreamerNVirtual()

void TUnfoldDensity::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 205 of file TUnfoldDensity.h.

SubtractBackground()

void TUnfoldSys::SubtractBackground ( const TH1 * bgr, const char * name, Double_t scale = 1.0, Double_t scale_error = 0.0 )

inherited

Specify a source of background.

Parameters

[in]	bgr	background distribution with uncorrelated errors
[in]	name	identifier for this background source
[in]	scale	normalisation factor applied to the background
[in]	scaleError	normalisation uncertainty

The contribution scale*bgr is subtracted from the measurement prior to unfolding. The following contributions are added to the input covarianc ematrix

• using the uncorrelated histogram errors dbgr, the contribution (scale*dbgr_i)² is added to the diagonals of the covariance
• using the histogram contents, the background normalisation uncertainty contribution dscale*bgr_i dscale*bgr_j is added to the covariance matrix

Definition at line 514 of file TUnfoldSys.cxx.

SysError()

void TObject::SysError ( const char * location, const char * fmt, ... ) const

virtualinherited

Issue system error message.

Use "location" to specify the method where the system error occurred. Accepts standard printf formatting arguments.

Definition at line 1112 of file TObject.cxx.

TestBit()

Bool_t TObject::TestBit ( UInt_t f ) const

inlineinherited

Definition at line 204 of file TObject.h.

TestBits()

Int_t TObject::TestBits ( UInt_t f ) const

inlineinherited

Definition at line 205 of file TObject.h.

UseCurrentStyle()

void TObject::UseCurrentStyle ( )

virtualinherited

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

Reimplemented in TAxis3D, TCanvas, TFrame, TGraph, TH1, TPad, TPaveStats, TPaveText, and TTree.

Definition at line 909 of file TObject.cxx.

VectorMapToHist()

void TUnfoldSys::VectorMapToHist ( TH1 * hist_delta, const TMatrixDSparse * delta, const Int_t * binMap )

protectedinherited

map delta to hist_delta, possibly summing up bins

Parameters

[out]	hist_delta	result histogram
[in]	delta	vector to be mapped to the histogram
[in]	binMap	mapping of histogram bins

grooups of bins of delta are mapped to bins of hist_delta. The histogram contents are set to the sum over the group of bins. The histogram errors are reset to zero.
The array binMap is explained with the method GetOutput()

Definition at line 1474 of file TUnfoldSys.cxx.

Warning()

void TObject::Warning ( const char * location, const char * fmt, ... ) const

virtualinherited

Issue warning message.

Use "location" to specify the method where the warning occurred. Accepts standard printf formatting arguments.

Definition at line 1084 of file TObject.cxx.

Write() [1/2]

Int_t TObject::Write ( const char * name = nullptr, Int_t option = 0, Int_t bufsize = 0 )

virtualinherited

Write this object to the current directory.

For more see the const version of this method.

Reimplemented in ROOT::TBufferMergerFile, TBuffer, TCollection, TDirectory, TDirectoryFile, TFile, TMap, TParallelMergingFile, TSQLFile, TTree, and TXMLFile.

Definition at line 989 of file TObject.cxx.

Write() [2/2]

Int_t TObject::Write ( const char * name = nullptr, Int_t option = 0, Int_t bufsize = 0 ) const

virtualinherited

Write this object to the current directory.

The data structure corresponding to this object is serialized. The corresponding buffer is written to the current directory with an associated key with name "name".

Writing an object to a file involves the following steps:

• Creation of a support TKey object in the current directory. The TKey object creates a TBuffer object.
• The TBuffer object is filled via the class::Streamer function.
• If the file is compressed (default) a second buffer is created to hold the compressed buffer.
• Reservation of the corresponding space in the file by looking in the TFree list of free blocks of the file.
• The buffer is written to the file.

Bufsize can be given to force a given buffer size to write this object. By default, the buffersize will be taken from the average buffer size of all objects written to the current file so far.

If a name is specified, it will be the name of the key. If name is not given, the name of the key will be the name as returned by GetName().

The option can be a combination of: kSingleKey, kOverwrite or kWriteDelete Using the kOverwrite option a previous key with the same name is overwritten. The previous key is deleted before writing the new object. Using the kWriteDelete option a previous key with the same name is deleted only after the new object has been written. This option is safer than kOverwrite but it is slower. NOTE: Neither kOverwrite nor kWriteDelete reduces the size of a TFile– the space is simply freed up to be overwritten; in the case of a TTree, it is more complicated. If one opens a TTree, appends some entries, then writes it out, the behaviour is effectively the same. If, however, one creates a new TTree and writes it out in this way, only the metadata is replaced, effectively making the old data invisible without deleting it. TTree::Delete() can be used to mark all disk space occupied by a TTree as free before overwriting its metadata this way. The kSingleKey option is only used by TCollection::Write() to write a container with a single key instead of each object in the container with its own key.

An object is read from the file into memory via TKey::Read() or via TObject::Read().

The function returns the total number of bytes written to the file. It returns 0 if the object cannot be written.

Reimplemented in TBuffer, TCollection, TDirectory, TDirectoryFile, TFile, TMap, TParallelMergingFile, TSQLFile, TTree, and TXMLFile.

Definition at line 964 of file TObject.cxx.

Member Data Documentation

fA

TMatrixDSparse* TUnfold::fA

protectedinherited

response matrix A

Definition at line 154 of file TUnfold.h.

fAoutside

TMatrixD* TUnfoldSys::fAoutside

protectedinherited

Input: underflow/overflow bins.

Definition at line 68 of file TUnfoldSys.h.

fAx

TMatrixDSparse* TUnfold::fAx

privateinherited

result x folded back A*x

Definition at line 191 of file TUnfold.h.

fBgrErrScaleIn

TMap* TUnfoldSys::fBgrErrScaleIn

protectedinherited

Input: background sources correlated error.

Definition at line 76 of file TUnfoldSys.h.

fBgrErrUncorrInSq

TMap* TUnfoldSys::fBgrErrUncorrInSq

protectedinherited

Input: uncorr error squared from bgr sources.

Definition at line 74 of file TUnfoldSys.h.

fBgrIn

TMap* TUnfoldSys::fBgrIn

protectedinherited

Input: size of background sources.

Definition at line 72 of file TUnfoldSys.h.

fBiasScale

Double_t TUnfold::fBiasScale

protectedinherited

scale factor for the bias

Definition at line 162 of file TUnfold.h.

fBits

UInt_t TObject::fBits

privateinherited

bit field status word

Definition at line 47 of file TObject.h.

fChi2A

Double_t TUnfold::fChi2A

privateinherited

chi**2 contribution from (y-Ax)Vyy^-1(y-Ax)

Definition at line 193 of file TUnfold.h.

fConstInputBins

const TUnfoldBinning* TUnfoldDensity::fConstInputBins

protected

binning scheme for the input (detector level)

Definition at line 57 of file TUnfoldDensity.h.

fConstOutputBins

const TUnfoldBinning* TUnfoldDensity::fConstOutputBins

protected

binning scheme for the output (truth level)

Definition at line 55 of file TUnfoldDensity.h.

fConstraint

EConstraint TUnfold::fConstraint

protectedinherited

type of constraint to use for the unfolding

Definition at line 174 of file TUnfold.h.

fDAinColRelSq

TMatrixD* TUnfoldSys::fDAinColRelSq

protectedinherited

Input: normalized column err.sq. (inp.matr.).

Definition at line 66 of file TUnfoldSys.h.

fDAinRelSq

TMatrixDSparse* TUnfoldSys::fDAinRelSq

protectedinherited

Input: normalized errors from input matrix.

Definition at line 64 of file TUnfoldSys.h.

fDeltaCorrAx

TMap* TUnfoldSys::fDeltaCorrAx

protectedinherited

Result: syst.shift from fSysIn on fAx.

Definition at line 90 of file TUnfoldSys.h.

fDeltaCorrX

TMap* TUnfoldSys::fDeltaCorrX

protectedinherited

Result: syst.shift from fSysIn on fX.

Definition at line 88 of file TUnfoldSys.h.

fDeltaSysTau

TMatrixDSparse* TUnfoldSys::fDeltaSysTau

protectedinherited

Result: systematic shift from tau.

Definition at line 92 of file TUnfoldSys.h.

fDtau

Double_t TUnfoldSys::fDtau

protectedinherited

Input: error on tau.

Definition at line 78 of file TUnfoldSys.h.

fDXDAM

TMatrixDSparse* TUnfold::fDXDAM[2]

privateinherited

matrix contribution to the of derivative dx_k/dA_ij

Definition at line 203 of file TUnfold.h.

fDXDAZ

TMatrixDSparse* TUnfold::fDXDAZ[2]

privateinherited

vector contribution to the of derivative dx_k/dA_ij

Definition at line 205 of file TUnfold.h.

fDXDtauSquared

TMatrixDSparse* TUnfold::fDXDtauSquared

privateinherited

derivative of the result wrt tau squared

Definition at line 207 of file TUnfold.h.

fDXDY

TMatrixDSparse* TUnfold::fDXDY

privateinherited

derivative of the result wrt dx/dy

Definition at line 209 of file TUnfold.h.

fE

TMatrixDSparse* TUnfold::fE

privateinherited

matrix E

Definition at line 213 of file TUnfold.h.

fEinv

TMatrixDSparse* TUnfold::fEinv

privateinherited

matrix E^(-1)

Definition at line 211 of file TUnfold.h.

fEmatUncorrAx

TMatrixDSparse* TUnfoldSys::fEmatUncorrAx

protectedinherited

Result: syst.error from fDA2 on fAx.

Definition at line 86 of file TUnfoldSys.h.

fEmatUncorrX

TMatrixDSparse* TUnfoldSys::fEmatUncorrX

protectedinherited

Result: syst.error from fDA2 on fX.

Definition at line 84 of file TUnfoldSys.h.

fEpsMatrix

Double_t TUnfold::fEpsMatrix

privateinherited

machine accuracy used to determine matrix rank after eigenvalue analysis

Definition at line 181 of file TUnfold.h.

fgDtorOnly

Longptr_t TObject::fgDtorOnly = 0

staticprivateinherited

object for which to call dtor only (i.e. no delete)

Definition at line 49 of file TObject.h.

fgObjectStat

Bool_t TObject::fgObjectStat = kTRUE

staticprivateinherited

if true keep track of objects in TObjectTable

Definition at line 50 of file TObject.h.

fHistToX

TArrayI TUnfold::fHistToX

protectedinherited

mapping of histogram bins to matrix indices

Definition at line 170 of file TUnfold.h.

fIgnoredBins

Int_t TUnfold::fIgnoredBins

privateinherited

number of input bins which are dropped because they have error=nullptr

Definition at line 179 of file TUnfold.h.

fL

TMatrixDSparse* TUnfold::fL

protectedinherited

regularisation conditions L

Definition at line 156 of file TUnfold.h.

fLXsquared

Double_t TUnfold::fLXsquared

privateinherited

chi**2 contribution from (x-s*x0)^TL^TL(x-s*x0)

Definition at line 195 of file TUnfold.h.

fNdf

Int_t TUnfold::fNdf

privateinherited

number of degrees of freedom

Definition at line 201 of file TUnfold.h.

fOwnedInputBins

TUnfoldBinning* TUnfoldDensity::fOwnedInputBins

protected

pointer to input binning scheme if owned by this class

Definition at line 61 of file TUnfoldDensity.h.

fOwnedOutputBins

TUnfoldBinning* TUnfoldDensity::fOwnedOutputBins

protected

pointer to output binning scheme if owned by this class

Definition at line 59 of file TUnfoldDensity.h.

fRegMode

ERegMode TUnfold::fRegMode

protectedinherited

type of regularisation

Definition at line 176 of file TUnfold.h.

fRegularisationConditions

TUnfoldBinning* TUnfoldDensity::fRegularisationConditions

protected

binning scheme for the regularisation conditions

Definition at line 63 of file TUnfoldDensity.h.

fRhoAvg

Double_t TUnfold::fRhoAvg

privateinherited

average global correlation coefficient

Definition at line 199 of file TUnfold.h.

fRhoMax

Double_t TUnfold::fRhoMax

privateinherited

maximum global correlation coefficient

Definition at line 197 of file TUnfold.h.

fSumOverY

TArrayD TUnfold::fSumOverY

protectedinherited

truth vector calculated from the non-normalized response matrix

Definition at line 172 of file TUnfold.h.

fSysIn

TMap* TUnfoldSys::fSysIn

protectedinherited

Input: correlated errors.

Definition at line 70 of file TUnfoldSys.h.

fTauSquared

Double_t TUnfold::fTauSquared

protectedinherited

regularisation parameter tau squared

Definition at line 166 of file TUnfold.h.

fUniqueID

UInt_t TObject::fUniqueID

privateinherited

object unique identifier

Definition at line 46 of file TObject.h.

fVxx

TMatrixDSparse* TUnfold::fVxx

privateinherited

covariance matrix Vxx

Definition at line 185 of file TUnfold.h.

fVxxInv

TMatrixDSparse* TUnfold::fVxxInv

privateinherited

inverse of covariance matrix Vxx^-1

Definition at line 187 of file TUnfold.h.

fVyy

TMatrixDSparse* TUnfold::fVyy

protectedinherited

covariance matrix Vyy corresponding to y

Definition at line 160 of file TUnfold.h.

fVyyData

TMatrixDSparse* TUnfoldSys::fVyyData

protectedinherited

Input: error on fY prior to bgr subtraction.

Definition at line 82 of file TUnfoldSys.h.

fVyyInv

TMatrixDSparse* TUnfold::fVyyInv

privateinherited

inverse of the input covariance matrix Vyy^-1

Definition at line 189 of file TUnfold.h.

fX

TMatrixD* TUnfold::fX

privateinherited

unfolding result x

Definition at line 183 of file TUnfold.h.

fX0

TMatrixD* TUnfold::fX0

protectedinherited

bias vector x0

Definition at line 164 of file TUnfold.h.

fXToHist

TArrayI TUnfold::fXToHist

protectedinherited

mapping of matrix indices to histogram bins

Definition at line 168 of file TUnfold.h.

fY

TMatrixD* TUnfold::fY

protectedinherited

input (measured) data y

Definition at line 158 of file TUnfold.h.

fYData

TMatrixD* TUnfoldSys::fYData

protectedinherited

Input: fY prior to bgr subtraction.

Definition at line 80 of file TUnfoldSys.h.

---

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

• hist/unfold/inc/TUnfoldDensity.h
• hist/unfold/src/TUnfoldDensity.cxx