/usr/include/root/TSVDUnfold.h is in libroot-hist-dev 5.34.19+dfsg-1.2.
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/**********************************************************************************
* *
* Project: TSVDUnfold - data unfolding based on Singular Value Decomposition *
* Package: ROOT *
* Class : TSVDUnfold *
* *
* Description: *
* Single class implementation of SVD data unfolding based on: *
* A. Hoecker, V. Kartvelishvili, *
* "SVD approach to data unfolding" *
* NIM A372, 469 (1996) [hep-ph/9509307] *
* *
* Authors: *
* Kerstin Tackmann <Kerstin.Tackmann@cern.ch> - CERN, Switzerland *
* Andreas Hoecker <Andreas.Hoecker@cern.ch> - CERN, Switzerland *
* Heiko Lacker <lacker@physik.hu-berlin.de> - Humboldt U, Germany *
* *
* Copyright (c) 2010: *
* CERN, Switzerland *
* Humboldt University, Germany *
* *
**********************************************************************************/
//////////////////////////////////////////////////////////////////////////
// //
// TSVDUnfold //
// //
// Data unfolding using Singular Value Decomposition (hep-ph/9509307) //
// Authors: Kerstin Tackmann, Andreas Hoecker, Heiko Lacker //
// //
//////////////////////////////////////////////////////////////////////////
#ifndef TSVDUNFOLD_H
#define TSVDUNFOLD_H
#ifndef ROOT_TObject
#include "TObject.h"
#endif
#ifndef ROOT_TMatrixD
#include "TMatrixD.h"
#endif
#ifndef ROOT_TVectorD
#include "TVectorD.h"
#endif
#ifndef ROOT_TMatrixDSym
#include "TMatrixDSym.h"
#endif
class TH1D;
class TH2D;
class TSVDUnfold : public TObject {
public:
// Constructor
// Initialisation of unfolding
// "bdat" - measured data distribution (number of events)
// "Bcov" - covariance matrix for measured data distribution
// "bini" - reconstructed MC distribution (number of events)
// "xini" - truth MC distribution (number of events)
// "Adet" - detector response matrix (number of events)
TSVDUnfold( const TH1D* bdat, const TH1D* bini, const TH1D* xini, const TH2D* Adet );
TSVDUnfold( const TH1D* bdat, TH2D* Bcov, const TH1D* bini, const TH1D* xini, const TH2D* Adet );
TSVDUnfold( const TSVDUnfold& other );
// Destructor
virtual ~TSVDUnfold();
// Set option to normalize unfolded spectrum to unit area
// "normalize" - switch
void SetNormalize ( Bool_t normalize ) { fNormalize = normalize; }
// Do the unfolding
// "kreg" - number of singular values used (regularisation)
TH1D* Unfold ( Int_t kreg );
// Determine for given input error matrix covariance matrix of unfolded
// spectrum from toy simulation
// "cov" - covariance matrix on the measured spectrum, to be propagated
// "ntoys" - number of pseudo experiments used for the propagation
// "seed" - seed for pseudo experiments
TH2D* GetUnfoldCovMatrix( const TH2D* cov, Int_t ntoys, Int_t seed = 1 );
// Determine covariance matrix of unfolded spectrum from finite statistics in
// response matrix
// "ntoys" - number of pseudo experiments used for the propagation
// "seed" - seed for pseudo experiments
TH2D* GetAdetCovMatrix( Int_t ntoys, Int_t seed=1 );
// Regularisation parameter
Int_t GetKReg() const { return fKReg; }
// Obtain the distribution of |d| (for determining the regularization)
TH1D* GetD() const;
// Obtain the distribution of singular values
TH1D* GetSV() const;
// Obtain the computed regularized covariance matrix
TH2D* GetXtau() const;
// Obtain the computed inverse of the covariance matrix
TH2D* GetXinv() const;
//Obtain the covariance matrix on the data
TH2D* GetBCov() const;
// Helper functions
Double_t ComputeChiSquared( const TH1D& truspec, const TH1D& unfspec );
private:
// Helper functions for vector and matrix operations
void FillCurvatureMatrix( TMatrixD& tCurv, TMatrixD& tC ) const;
static Double_t GetCurvature ( const TVectorD& vec, const TMatrixD& curv );
void InitHistos ( );
// Helper functions
static void H2V ( const TH1D* histo, TVectorD& vec );
static void H2Verr ( const TH1D* histo, TVectorD& vec );
static void V2H ( const TVectorD& vec, TH1D& histo );
static void H2M ( const TH2D* histo, TMatrixD& mat );
static void M2H ( const TMatrixD& mat, TH2D& histo );
static TMatrixD MatDivVec( const TMatrixD& mat, const TVectorD& vec, Int_t zero=0 );
static TVectorD CompProd ( const TVectorD& vec1, const TVectorD& vec2 );
static TVectorD VecDiv ( const TVectorD& vec1, const TVectorD& vec2, Int_t zero = 0 );
static void RegularisedSymMatInvert( TMatrixDSym& mat, Double_t eps = 1e-3 );
// 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
TH1D* fDHist; //! Distribution of d (for checking regularization)
TH1D* fSVHist; //! Distribution of singular values
TH2D* fXtau; //! Computed regularized covariance matrix
TH2D* fXinv; //! Computed inverse of covariance matrix
// Input histos
const TH1D* fBdat; // measured distribution (data)
TH2D* fBcov; // covariance matrix of measured distribution (data)
const TH1D* fBini; // reconstructed distribution (MC)
const TH1D* fXini; // truth distribution (MC)
const TH2D* fAdet; // Detector response matrix
// Evaluation of covariance matrices
TH1D* fToyhisto; //! Toy MC histogram
TH2D* fToymat; //! 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
ClassDef( TSVDUnfold, 0 ) // Data unfolding using Singular Value Decomposition (hep-ph/9509307)
};
#endif
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