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TSVDUnfold Class Reference

SVD Approach to Data Unfolding.

Reference: Nucl. Instrum. Meth. A372, 469 (1996) [hep-ph/9509307]

TSVDUnfold implements the singular value decomposition based unfolding method (see reference). Currently, the unfolding of one-dimensional histograms is supported, with the same number of bins for the measured and the unfolded spectrum.

The unfolding procedure is based on singular value decomposition of the response matrix. The regularisation of the unfolding is implemented via a discrete minimum-curvature condition.

Monte Carlo inputs:

  • xini: true underlying spectrum (TH1D, n bins)
  • bini: reconstructed spectrum (TH1D, n bins)
  • Adet: response matrix (TH2D, nxn bins)

Consider the unfolding of a measured spectrum bdat with covariance matrix Bcov (if not passed explicitly, a diagonal covariance will be built given the errors of bdat). The corresponding spectrum in the Monte Carlo is given by bini, with the true underlying spectrum given by xini. The detector response is described by Adet, with Adet filled with events (not probabilities) with the true observable on the y-axis and the reconstructed observable on the x-axis.

The measured distribution can be unfolded for any combination of resolution, efficiency and acceptance effects, provided an appropriate definition of xini and Adet.

The unfolding can be performed by

TSVDUnfold *tsvdunf = new TSVDUnfold( bdat, Bcov, bini, xini, Adet );
TH1D* unfresult = tsvdunf->Unfold( kreg );
1-D histogram with a double per channel (see TH1 documentation)
Definition TH1.h:664
SVD Approach to Data Unfolding.
Definition TSVDUnfold.h:46
TH1D * Unfold(Int_t kreg)
Perform the unfolding with regularisation parameter kreg.

where kreg determines the regularisation of the unfolding. In general, overregularisation (too small kreg) will bias the unfolded spectrum towards the Monte Carlo input, while underregularisation (too large kreg) will lead to large fluctuations in the unfolded spectrum. The optimal regularisation can be determined following guidelines in Nucl. Instrum. Meth. A372, 469 (1996) [hep-ph/9509307] using the distribution of the |d_i| that can be obtained by tsvdunf->GetD() and/or using pseudo-experiments.

Covariance matrices on the measured spectrum (for either the total uncertainties or individual sources of uncertainties) can be propagated to covariance matrices using the GetUnfoldCovMatrix method, which uses pseudo experiments for the propagation. In addition, GetAdetCovMatrix allows for the propagation of the statistical uncertainties on the response matrix using pseudo experiments. The covariance matrix corresponding to Bcov is also computed as described in Nucl. Instrum. Meth. A372, 469 (1996) [hep-ph/9509307] and can be obtained from tsvdunf->GetXtau() and its (regularisation independent) inverse from tsvdunf->GetXinv(). The distribution of singular values can be retrieved using tsvdunf->GetSV().

See also the tutorial for a toy example.

Definition at line 46 of file TSVDUnfold.h.

Public Member Functions

 TSVDUnfold (const TH1D *bdat, const TH1D *bini, const TH1D *xini, const TH2D *Adet)
 Alternative constructor User provides data and MC test spectra, as well as detector response matrix, diagonal covariance matrix of measured spectrum built from the uncertainties on measured spectrum.
 
 TSVDUnfold (const TH1D *bdat, TH2D *Bcov, const TH1D *bini, const TH1D *xini, const TH2D *Adet)
 Default constructor Initialisation of TSVDUnfold User provides data and MC test spectra, as well as detector response matrix and the covariance matrix of the measured distribution.
 
 TSVDUnfold (const TSVDUnfold &other)
 Copy constructor.
 
 ~TSVDUnfold () override
 Destructor.
 
Double_t ComputeChiSquared (const TH1D &truspec, const TH1D &unfspec)
 Helper routine to compute chi-squared between distributions using the computed inverse of the covariance matrix for the unfolded spectrum as given in paper.
 
TH2DGetAdetCovMatrix (Int_t ntoys, Int_t seed=1)
 Determine covariance matrix of unfolded spectrum from finite statistics in response matrix using pseudo experiments "ntoys" - number of pseudo experiments used for the propagation "seed" - seed for pseudo experiments.
 
TH2DGetBCov () const
 Returns the covariance matrix.
 
TH1DGetD () const
 Returns d vector (for choosing appropriate regularisation)
 
Int_t GetKReg () const
 
TH1DGetSV () const
 Returns singular values vector.
 
TH2DGetUnfoldCovMatrix (const TH2D *cov, Int_t ntoys, Int_t seed=1)
 Determine for given input error matrix covariance matrix of unfolded spectrum from toy simulation given the passed covariance matrix on measured spectrum "cov" - covariance matrix on the measured spectrum, to be propagated "ntoys" - number of pseudo experiments used for the propagation "seed" - seed for pseudo experiments Note that this covariance matrix will contain effects of forced normalisation if spectrum is normalised to unit area.
 
TH2DGetXinv () const
 Returns the computed inverse of the covariance matrix.
 
TH2DGetXtau () const
 Returns the computed regularized covariance matrix corresponding to total uncertainties on measured spectrum as passed in the constructor.
 
TClassIsA () const override
 
void SetNormalize (Bool_t normalize)
 
void Streamer (TBuffer &) override
 Stream an object of class TObject.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
TH1DUnfold (Int_t kreg)
 Perform the unfolding with regularisation parameter kreg.
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor.
 
 TObject (const TObject &object)
 TObject copy ctor.
 
virtual ~TObject ()
 TObject destructor.
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract.
 
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 TObjectClone (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 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 TObjectDrawClone (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 TObjectFindObject (const char *name) const
 Must be redefined in derived classes.
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes.
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object.
 
virtual const char * GetIconName () const
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virtual const char * GetName () const
 Returns name of object.
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py).
 
virtual Option_tGetOption () const
 
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)
 
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).
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
virtual Bool_t IsSortable () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
virtual void ls (Option_t *option="") const
 The ls function lists the contents of a class on stdout.
 
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 *ptr)
 Operator delete.
 
void operator delete[] (void *ptr)
 Operator delete [].
 
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)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator.
 
virtual void Paint (Option_t *option="")
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virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list.
 
virtual void Print (Option_t *option="") const
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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.
 
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".
 
void SetBit (UInt_t f)
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f.
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object.
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message.
 
R__ALWAYS_INLINE 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 TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
- Static Public Member Functions inherited from TObject
static TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
static Longptr_t GetDtorOnly ()
 Return destructor only flag.
 
static Bool_t GetObjectStat ()
 Get status of object stat flag.
 
static void SetDtorOnly (void *obj)
 Set destructor only flag.
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable.
 

Private Member Functions

void FillCurvatureMatrix (TMatrixD &tCurv, TMatrixD &tC) const
 
void InitHistos ()
 

Static Private Member Functions

static TVectorD CompProd (const TVectorD &vec1, const TVectorD &vec2)
 Multiply entries of two vectors.
 
static Double_t GetCurvature (const TVectorD &vec, const TMatrixD &curv)
 Compute curvature of vector.
 
static void H2M (const TH2D *histo, TMatrixD &mat)
 Fill 2D histogram into matrix.
 
static void H2V (const TH1D *histo, TVectorD &vec)
 Fill 1D histogram into vector.
 
static void H2Verr (const TH1D *histo, TVectorD &vec)
 Fill 1D histogram errors into vector.
 
static void M2H (const TMatrixD &mat, TH2D &histo)
 Fill 2D histogram into matrix.
 
static TMatrixD MatDivVec (const TMatrixD &mat, const TVectorD &vec, Int_t zero=0)
 Divide matrix entries by vector.
 
static void RegularisedSymMatInvert (TMatrixDSym &mat, Double_t eps=1e-3)
 naive regularised inversion cuts off small elements
 
static void V2H (const TVectorD &vec, TH1D &histo)
 Fill vector into 1D histogram.
 
static TVectorD VecDiv (const TVectorD &vec1, const TVectorD &vec2, Int_t zero=0)
 Divide entries of two vectors.
 

Private Attributes

Class members
Int_t fNdim
 ! Truth and reconstructed dimensions
 
Int_t fDdim
 ! Derivative for curvature matrix
 
Bool_t fNormalize
 ! Normalize unfolded spectrum to 1
 
Int_t fKReg
 ! Regularisation parameter
 
TH1DfDHist
 ! Distribution of d (for checking regularization)
 
TH1DfSVHist
 ! Distribution of singular values
 
TH2DfXtau
 ! Computed regularized covariance matrix
 
TH2DfXinv
 ! Computed inverse of covariance matrix
 
Input histos
const TH1DfBdat
 Measured distribution (data)
 
TH2DfBcov
 Covariance matrix of measured distribution (data)
 
const TH1DfBini
 Reconstructed distribution (MC)
 
const TH1DfXini
 Truth distribution (MC)
 
const TH2DfAdet
 Detector response matrix.
 
Evaluation of covariance matrices
TH1DfToyhisto
 ! Toy MC histogram
 
TH2DfToymat
 ! Toy MC detector response matrix
 
Bool_t fToyMode
 ! Internal switch for covariance matrix propagation
 
Bool_t fMatToyMode
 ! Internal switch for evaluation of statistical uncertainties from response matrix
 

Additional Inherited Members

- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 ,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = (1ULL << ( 0 )) , kOverwrite = (1ULL << ( 1 )) , kWriteDelete = (1ULL << ( 2 )) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }
 
enum  EStatusBits {
  kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) ,
  kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 13 ))
}
 
- Protected Types inherited from TObject
enum  { kOnlyPrepStep = (1ULL << ( 3 )) }
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected).
 
void MakeZombie ()
 

#include <TSVDUnfold.h>

Inheritance diagram for TSVDUnfold:
[legend]

Constructor & Destructor Documentation

◆ TSVDUnfold() [1/3]

TSVDUnfold::TSVDUnfold ( const TH1D bdat,
const TH1D bini,
const TH1D xini,
const TH2D Adet 
)

Alternative constructor User provides data and MC test spectra, as well as detector response matrix, diagonal covariance matrix of measured spectrum built from the uncertainties on measured spectrum.

Definition at line 75 of file TSVDUnfold.cxx.

◆ TSVDUnfold() [2/3]

TSVDUnfold::TSVDUnfold ( const TH1D bdat,
TH2D Bcov,
const TH1D bini,
const TH1D xini,
const TH2D Adet 
)

Default constructor Initialisation of TSVDUnfold User provides data and MC test spectra, as well as detector response matrix and the covariance matrix of the measured distribution.

Definition at line 128 of file TSVDUnfold.cxx.

◆ TSVDUnfold() [3/3]

TSVDUnfold::TSVDUnfold ( const TSVDUnfold other)

Copy constructor.

Definition at line 173 of file TSVDUnfold.cxx.

◆ ~TSVDUnfold()

TSVDUnfold::~TSVDUnfold ( )
override

Destructor.

Definition at line 198 of file TSVDUnfold.cxx.

Member Function Documentation

◆ Class()

static TClass * TSVDUnfold::Class ( )
static
Returns
TClass describing this class

◆ Class_Name()

static const char * TSVDUnfold::Class_Name ( )
static
Returns
Name of this class

◆ Class_Version()

static constexpr Version_t TSVDUnfold::Class_Version ( )
inlinestaticconstexpr
Returns
Version of this class

Definition at line 156 of file TSVDUnfold.h.

◆ CompProd()

TVectorD TSVDUnfold::CompProd ( const TVectorD vec1,
const TVectorD vec2 
)
staticprivate

Multiply entries of two vectors.

Definition at line 704 of file TSVDUnfold.cxx.

◆ ComputeChiSquared()

Double_t TSVDUnfold::ComputeChiSquared ( const TH1D truspec,
const TH1D unfspec 
)

Helper routine to compute chi-squared between distributions using the computed inverse of the covariance matrix for the unfolded spectrum as given in paper.

Definition at line 882 of file TSVDUnfold.cxx.

◆ DeclFileName()

static const char * TSVDUnfold::DeclFileName ( )
inlinestatic
Returns
Name of the file containing the class declaration

Definition at line 156 of file TSVDUnfold.h.

◆ FillCurvatureMatrix()

void TSVDUnfold::FillCurvatureMatrix ( TMatrixD tCurv,
TMatrixD tC 
) const
private

Definition at line 721 of file TSVDUnfold.cxx.

◆ GetAdetCovMatrix()

TH2D * TSVDUnfold::GetAdetCovMatrix ( Int_t  ntoys,
Int_t  seed = 1 
)

Determine covariance matrix of unfolded spectrum from finite statistics in response matrix using pseudo experiments "ntoys" - number of pseudo experiments used for the propagation "seed" - seed for pseudo experiments.

Definition at line 513 of file TSVDUnfold.cxx.

◆ GetBCov()

TH2D * TSVDUnfold::GetBCov ( ) const

Returns the covariance matrix.

Definition at line 614 of file TSVDUnfold.cxx.

◆ GetCurvature()

Double_t TSVDUnfold::GetCurvature ( const TVectorD vec,
const TMatrixD curv 
)
staticprivate

Compute curvature of vector.

Definition at line 714 of file TSVDUnfold.cxx.

◆ GetD()

TH1D * TSVDUnfold::GetD ( ) const

Returns d vector (for choosing appropriate regularisation)

Definition at line 578 of file TSVDUnfold.cxx.

◆ GetKReg()

Int_t TSVDUnfold::GetKReg ( ) const
inline

Definition at line 86 of file TSVDUnfold.h.

◆ GetSV()

TH1D * TSVDUnfold::GetSV ( ) const

Returns singular values vector.

Definition at line 589 of file TSVDUnfold.cxx.

◆ GetUnfoldCovMatrix()

TH2D * TSVDUnfold::GetUnfoldCovMatrix ( const TH2D cov,
Int_t  ntoys,
Int_t  seed = 1 
)

Determine for given input error matrix covariance matrix of unfolded spectrum from toy simulation given the passed covariance matrix on measured spectrum "cov" - covariance matrix on the measured spectrum, to be propagated "ntoys" - number of pseudo experiments used for the propagation "seed" - seed for pseudo experiments Note that this covariance matrix will contain effects of forced normalisation if spectrum is normalised to unit area.

Definition at line 407 of file TSVDUnfold.cxx.

◆ GetXinv()

TH2D * TSVDUnfold::GetXinv ( ) const

Returns the computed inverse of the covariance matrix.

Definition at line 606 of file TSVDUnfold.cxx.

◆ GetXtau()

TH2D * TSVDUnfold::GetXtau ( ) const

Returns the computed regularized covariance matrix corresponding to total uncertainties on measured spectrum as passed in the constructor.

Note that this covariance matrix will not contain the effects of forced normalization if spectrum is normalized to unit area.

Definition at line 598 of file TSVDUnfold.cxx.

◆ H2M()

void TSVDUnfold::H2M ( const TH2D histo,
TMatrixD mat 
)
staticprivate

Fill 2D histogram into matrix.

Definition at line 646 of file TSVDUnfold.cxx.

◆ H2V()

void TSVDUnfold::H2V ( const TH1D histo,
TVectorD vec 
)
staticprivate

Fill 1D histogram into vector.

Definition at line 622 of file TSVDUnfold.cxx.

◆ H2Verr()

void TSVDUnfold::H2Verr ( const TH1D histo,
TVectorD vec 
)
staticprivate

Fill 1D histogram errors into vector.

Definition at line 630 of file TSVDUnfold.cxx.

◆ InitHistos()

void TSVDUnfold::InitHistos ( )
private

Definition at line 809 of file TSVDUnfold.cxx.

◆ IsA()

TClass * TSVDUnfold::IsA ( ) const
inlineoverridevirtual
Returns
TClass describing current object

Reimplemented from TObject.

Definition at line 156 of file TSVDUnfold.h.

◆ M2H()

void TSVDUnfold::M2H ( const TMatrixD mat,
TH2D histo 
)
staticprivate

Fill 2D histogram into matrix.

Definition at line 658 of file TSVDUnfold.cxx.

◆ MatDivVec()

TMatrixD TSVDUnfold::MatDivVec ( const TMatrixD mat,
const TVectorD vec,
Int_t  zero = 0 
)
staticprivate

Divide matrix entries by vector.

Definition at line 686 of file TSVDUnfold.cxx.

◆ RegularisedSymMatInvert()

void TSVDUnfold::RegularisedSymMatInvert ( TMatrixDSym mat,
Double_t  eps = 1e-3 
)
staticprivate

naive regularised inversion cuts off small elements

Definition at line 829 of file TSVDUnfold.cxx.

◆ SetNormalize()

void TSVDUnfold::SetNormalize ( Bool_t  normalize)
inline

Definition at line 66 of file TSVDUnfold.h.

◆ Streamer()

void TSVDUnfold::Streamer ( TBuffer R__b)
overridevirtual

Stream an object of class TObject.

Reimplemented from TObject.

◆ StreamerNVirtual()

void TSVDUnfold::StreamerNVirtual ( TBuffer ClassDef_StreamerNVirtual_b)
inline

Definition at line 156 of file TSVDUnfold.h.

◆ Unfold()

TH1D * TSVDUnfold::Unfold ( Int_t  kreg)

Perform the unfolding with regularisation parameter kreg.

Definition at line 239 of file TSVDUnfold.cxx.

◆ V2H()

void TSVDUnfold::V2H ( const TVectorD vec,
TH1D histo 
)
staticprivate

Fill vector into 1D histogram.

Definition at line 638 of file TSVDUnfold.cxx.

◆ VecDiv()

TVectorD TSVDUnfold::VecDiv ( const TVectorD vec1,
const TVectorD vec2,
Int_t  zero = 0 
)
staticprivate

Divide entries of two vectors.

Definition at line 670 of file TSVDUnfold.cxx.

Member Data Documentation

◆ fAdet

const TH2D* TSVDUnfold::fAdet
private

Detector response matrix.

Definition at line 144 of file TSVDUnfold.h.

◆ fBcov

TH2D* TSVDUnfold::fBcov
private

Covariance matrix of measured distribution (data)

Definition at line 141 of file TSVDUnfold.h.

◆ fBdat

const TH1D* TSVDUnfold::fBdat
private

Measured distribution (data)

Definition at line 140 of file TSVDUnfold.h.

◆ fBini

const TH1D* TSVDUnfold::fBini
private

Reconstructed distribution (MC)

Definition at line 142 of file TSVDUnfold.h.

◆ fDdim

Int_t TSVDUnfold::fDdim
private

! Derivative for curvature matrix

Definition at line 129 of file TSVDUnfold.h.

◆ fDHist

TH1D* TSVDUnfold::fDHist
private

! Distribution of d (for checking regularization)

Definition at line 132 of file TSVDUnfold.h.

◆ fKReg

Int_t TSVDUnfold::fKReg
private

! Regularisation parameter

Definition at line 131 of file TSVDUnfold.h.

◆ fMatToyMode

Bool_t TSVDUnfold::fMatToyMode
private

! Internal switch for evaluation of statistical uncertainties from response matrix

Definition at line 152 of file TSVDUnfold.h.

◆ fNdim

Int_t TSVDUnfold::fNdim
private

! Truth and reconstructed dimensions

Definition at line 128 of file TSVDUnfold.h.

◆ fNormalize

Bool_t TSVDUnfold::fNormalize
private

! Normalize unfolded spectrum to 1

Definition at line 130 of file TSVDUnfold.h.

◆ fSVHist

TH1D* TSVDUnfold::fSVHist
private

! Distribution of singular values

Definition at line 133 of file TSVDUnfold.h.

◆ fToyhisto

TH1D* TSVDUnfold::fToyhisto
private

! Toy MC histogram

Definition at line 149 of file TSVDUnfold.h.

◆ fToymat

TH2D* TSVDUnfold::fToymat
private

! Toy MC detector response matrix

Definition at line 150 of file TSVDUnfold.h.

◆ fToyMode

Bool_t TSVDUnfold::fToyMode
private

! Internal switch for covariance matrix propagation

Definition at line 151 of file TSVDUnfold.h.

◆ fXini

const TH1D* TSVDUnfold::fXini
private

Truth distribution (MC)

Definition at line 143 of file TSVDUnfold.h.

◆ fXinv

TH2D* TSVDUnfold::fXinv
private

! Computed inverse of covariance matrix

Definition at line 135 of file TSVDUnfold.h.

◆ fXtau

TH2D* TSVDUnfold::fXtau
private

! Computed regularized covariance matrix

Definition at line 134 of file TSVDUnfold.h.

Libraries for TSVDUnfold:

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