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Advanced 1-dimensional spectra fitting functions.

Author
Miroslav Morhac

Class for fitting 1D spectra using AWMI (algorithm without matrix inversion) and conjugate gradient algorithms for symmetrical matrices (Stiefel-Hestens method). AWMI method allows to fit simultaneously 100s up to 1000s peaks. Stiefel method is very stable, it converges faster, but is more time consuming

The algorithms in this class have been published in the following references:

  1. M. Morhac et al.: Efficient fitting algorithms applied to analysis of coincidence gamma-ray spectra. Computer Physics Communications, Vol 172/1 (2005) pp. 19-41.
  2. M. Morhac et al.: Study of fitting algorithms applied to simultaneous analysis of large number of peaks in gamma-ray spectra. Applied Spectroscopy, Vol. 57, No. 7, pp. 753-760, 2003.

Definition at line 18 of file TSpectrumFit.h.

Public Types

enum  {
  kFitOptimChiCounts =0, kFitOptimChiFuncValues =1, kFitOptimMaxLikelihood =2, kFitAlphaHalving =0,
  kFitAlphaOptimal =1, kFitPower2 =2, kFitPower4 =4, kFitPower6 =6,
  kFitPower8 =8, kFitPower10 =10, kFitPower12 =12, kFitTaylorOrderFirst =0,
  kFitTaylorOrderSecond =1, kFitNumRegulCycles =100
}
 
- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5),
  kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 

Public Member Functions

 TSpectrumFit (void)
 Default constructor. More...
 
 TSpectrumFit (Int_t numberPeaks)
 numberPeaks: number of fitted peaks (must be greater than zero) More...
 
virtual ~TSpectrumFit ()
 Destructor. More...
 
void FitAwmi (Double_t *source)
 This function fits the source spectrum. More...
 
void FitStiefel (Double_t *source)
 This function fits the source spectrum. More...
 
Double_tGetAmplitudes () const
 
Double_tGetAmplitudesErrors () const
 
Double_tGetAreas () const
 
Double_tGetAreasErrors () const
 
void GetBackgroundParameters (Double_t &a0, Double_t &a0Err, Double_t &a1, Double_t &a1Err, Double_t &a2, Double_t &a2Err)
 This function gets the background parameters and their errors. More...
 
Double_t GetChi () const
 
Double_tGetPositions () const
 
Double_tGetPositionsErrors () const
 
void GetSigma (Double_t &sigma, Double_t &sigmaErr)
 This function gets the sigma parameter and its error. More...
 
void GetTailParameters (Double_t &t, Double_t &tErr, Double_t &b, Double_t &bErr, Double_t &s, Double_t &sErr)
 This function gets the tail parameters and their errors. More...
 
void SetBackgroundParameters (Double_t a0Init, Bool_t fixA0, Double_t a1Init, Bool_t fixA1, Double_t a2Init, Bool_t fixA2)
 This function sets the following fitting parameters of background: More...
 
void SetFitParameters (Int_t xmin, Int_t xmax, Int_t numberIterations, Double_t alpha, Int_t statisticType, Int_t alphaOptim, Int_t power, Int_t fitTaylor)
 This function sets the following fitting parameters: More...
 
void SetPeakParameters (Double_t sigma, Bool_t fixSigma, const Double_t *positionInit, const Bool_t *fixPosition, const Double_t *ampInit, const Bool_t *fixAmp)
 This function sets the following fitting parameters of peaks: More...
 
void SetTailParameters (Double_t tInit, Bool_t fixT, Double_t bInit, Bool_t fixB, Double_t sInit, Bool_t fixS)
 This function sets the following fitting parameters of tails of peaks. More...
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TString &name, const TString &title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor. More...
 
virtual ~TNamed ()
 TNamed destructor. More...
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings (""). More...
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects. More...
 
virtual void Copy (TObject &named) const
 Copy this to obj. More...
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer. More...
 
virtual const char * GetName () const
 Returns name of object. More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title. More...
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator. More...
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title. More...
 
virtual void SetName (const char *name)
 Set the name of the TNamed. More...
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title). More...
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed. More...
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject. More...
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor. More...
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
ULong_t CheckedHash ()
 Checked and record whether for this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad). More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
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. More...
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
void InvertBit (UInt_t f)
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
void SetBit (UInt_t f)
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
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. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 

Protected Member Functions

Double_t Area (Double_t a, Double_t sigma, Double_t t, Double_t b)
 This function calculates area of a peak Function parameters: More...
 
Double_t Dera1 (Double_t i)
 Derivative of background according to a1. More...
 
Double_t Dera2 (Double_t i)
 Derivative of background according to a2. More...
 
Double_t Deramp (Double_t i, Double_t i0, Double_t sigma, Double_t t, Double_t s, Double_t b)
 This function calculates derivative of peak shape function (see manual) according to amplitude of peak. More...
 
Double_t Derb (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma, Double_t t, Double_t b)
 This function calculates derivative of peaks shape function (see manual) according to slope b. More...
 
Double_t Derderi0 (Double_t i, Double_t amp, Double_t i0, Double_t sigma)
 This function calculates second derivative of peak shape function (see manual) according to peak position. More...
 
Double_t Derdersigma (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma)
 This function calculates second derivative of peaks shape function (see manual) according to sigma of peaks. More...
 
Double_t Derfc (Double_t x)
 This function calculates derivative of error function of x. More...
 
Double_t Deri0 (Double_t i, Double_t amp, Double_t i0, Double_t sigma, Double_t t, Double_t s, Double_t b)
 This function calculates derivative of peak shape function (see manual) according to peak position. More...
 
Double_t Derpa (Double_t sigma, Double_t t, Double_t b)
 This function calculates derivative of the area of peak according to its amplitude. More...
 
Double_t Derpb (Double_t a, Double_t sigma, Double_t t, Double_t b)
 This function calculates derivative of the area of peak according to b parameter. More...
 
Double_t Derpsigma (Double_t a, Double_t t, Double_t b)
 This function calculates derivative of the area of peak according to sigma of peaks. More...
 
Double_t Derpt (Double_t a, Double_t sigma, Double_t b)
 This function calculates derivative of the area of peak according to t parameter. More...
 
Double_t Ders (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma)
 This function calculates derivative of peaks shape function (see manual) according to relative amplitude s. More...
 
Double_t Dersigma (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma, Double_t t, Double_t s, Double_t b)
 This function calculates derivative of peaks shape function (see manual) according to sigma of peaks. More...
 
Double_t Dert (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma, Double_t b)
 This function calculates derivative of peaks shape function (see manual) according to relative amplitude t. More...
 
Double_t Erfc (Double_t x)
 
Double_t Ourpowl (Double_t a, Int_t pw)
 Power function. More...
 
Double_t Shape (Int_t num_of_fitted_peaks, Double_t i, const Double_t *parameter, Double_t sigma, Double_t t, Double_t s, Double_t b, Double_t a0, Double_t a1, Double_t a2)
 This function calculates peaks shape function (see manual) Function parameters: More...
 
void StiefelInversion (Double_t **a, Int_t rozmer)
 This function calculates solution of the system of linear equations. More...
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 
void MakeZombie ()
 

Protected Attributes

Double_t fA0Calc
 calculated value of background a0 parameter More...
 
Double_t fA0Err
 error value of background a0 parameter More...
 
Double_t fA0Init
 initial value of background a0 parameter(backgroud is estimated as a0+a1*x+a2*x*x) More...
 
Double_t fA1Calc
 calculated value of background a1 parameter More...
 
Double_t fA1Err
 error value of background a1 parameter More...
 
Double_t fA1Init
 initial value of background a1 parameter(backgroud is estimated as a0+a1*x+a2*x*x) More...
 
Double_t fA2Calc
 calculated value of background a2 parameter More...
 
Double_t fA2Err
 error value of background a2 parameter More...
 
Double_t fA2Init
 initial value of background a2 parameter(backgroud is estimated as a0+a1*x+a2*x*x) More...
 
Double_t fAlpha
 convergence coefficient, input parameter, it should be positive number and <=1, for details see references More...
 
Int_t fAlphaOptim
 optimization of convergence algorithm, possible values kFitAlphaHalving, kFitAlphaOptimal More...
 
Double_tfAmpCalc
 [fNPeaks] array of calculated values of fitted amplitudes, output parameters More...
 
Double_tfAmpErr
 [fNPeaks] array of amplitude errors More...
 
Double_tfAmpInit
 [fNPeaks] array of initial values of peaks amplitudes, input parameters More...
 
Double_tfArea
 [fNPeaks] array of calculated areas of peaks More...
 
Double_tfAreaErr
 [fNPeaks] array of errors of peak areas More...
 
Double_t fBCalc
 calculated value of b parameter More...
 
Double_t fBErr
 error value of b parameter More...
 
Double_t fBInit
 initial value of b parameter (slope), for details see html manual and references More...
 
Double_t fChi
 here the fitting functions return resulting chi square More...
 
Int_t fFitTaylor
 order of Taylor expansion, possible values kFitTaylorOrderFirst, kFitTaylorOrderSecond. It applies only for Awmi fitting function. More...
 
Bool_t fFixA0
 logical value of a0 parameter, which allows to fix the parameter (not to fit). More...
 
Bool_t fFixA1
 logical value of a1 parameter, which allows to fix the parameter (not to fit). More...
 
Bool_t fFixA2
 logical value of a2 parameter, which allows to fix the parameter (not to fit). More...
 
Bool_tfFixAmp
 [fNPeaks] array of logical values which allow to fix appropriate amplitudes (not fit). However they are present in the estimated functional More...
 
Bool_t fFixB
 logical value of b parameter, which allows to fix the parameter (not to fit). More...
 
Bool_tfFixPosition
 [fNPeaks] array of logical values which allow to fix appropriate positions (not fit). However they are present in the estimated functional More...
 
Bool_t fFixS
 logical value of s parameter, which allows to fix the parameter (not to fit). More...
 
Bool_t fFixSigma
 logical value of sigma parameter, which allows to fix the parameter (not to fit). More...
 
Bool_t fFixT
 logical value of t parameter, which allows to fix the parameter (not to fit). More...
 
Int_t fNPeaks
 number of peaks present in fit, input parameter, it should be > 0 More...
 
Int_t fNumberIterations
 number of iterations in fitting procedure, input parameter, it should be > 0 More...
 
Double_tfPositionCalc
 [fNPeaks] array of calculated values of fitted positions, output parameters More...
 
Double_tfPositionErr
 [fNPeaks] array of position errors More...
 
Double_tfPositionInit
 [fNPeaks] array of initial values of peaks positions, input parameters More...
 
Int_t fPower
 possible values kFitPower2,4,6,8,10,12, for details see references. It applies only for Awmi fitting function. More...
 
Double_t fSCalc
 calculated value of s parameter More...
 
Double_t fSErr
 error value of s parameter More...
 
Double_t fSigmaCalc
 calculated value of sigma parameter More...
 
Double_t fSigmaErr
 error value of sigma parameter More...
 
Double_t fSigmaInit
 initial value of sigma parameter More...
 
Double_t fSInit
 initial value of s parameter (relative amplitude of step), for details see html manual and references More...
 
Int_t fStatisticType
 type of statistics, possible values kFitOptimChiCounts (chi square statistics with counts as weighting coefficients), kFitOptimChiFuncValues (chi square statistics with function values as weighting coefficients),kFitOptimMaxLikelihood More...
 
Double_t fTCalc
 calculated value of t parameter More...
 
Double_t fTErr
 error value of t parameter More...
 
Double_t fTInit
 initial value of t parameter (relative amplitude of tail), for details see html manual and references More...
 
Int_t fXmax
 last fitted channel More...
 
Int_t fXmin
 first fitted channel More...
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

Additional Inherited Members

- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 

#include <TSpectrumFit.h>

Inheritance diagram for TSpectrumFit:
[legend]

Member Enumeration Documentation

◆ anonymous enum

anonymous enum
Enumerator
kFitOptimChiCounts 
kFitOptimChiFuncValues 
kFitOptimMaxLikelihood 
kFitAlphaHalving 
kFitAlphaOptimal 
kFitPower2 
kFitPower4 
kFitPower6 
kFitPower8 
kFitPower10 
kFitPower12 
kFitTaylorOrderFirst 
kFitTaylorOrderSecond 
kFitNumRegulCycles 

Definition at line 70 of file TSpectrumFit.h.

Constructor & Destructor Documentation

◆ TSpectrumFit() [1/2]

TSpectrumFit::TSpectrumFit ( void  )

Default constructor.

Definition at line 35 of file TSpectrumFit.cxx.

◆ TSpectrumFit() [2/2]

TSpectrumFit::TSpectrumFit ( Int_t  numberPeaks)

numberPeaks: number of fitted peaks (must be greater than zero)

the constructor allocates arrays for all fitted parameters (peak positions, amplitudes etc) and sets the member variables to their default values. One can change these variables by member functions (setters) of TSpectrumFit class.

Shape function of the fitted peaks is

spectrumfit_constructor_image001.gif

where a represents vector of fitted parameters (positions p(j), amplitudes A(j), sigma, relative amplitudes T, S and slope B).

Definition at line 101 of file TSpectrumFit.cxx.

◆ ~TSpectrumFit()

TSpectrumFit::~TSpectrumFit ( )
virtual

Destructor.

Definition at line 160 of file TSpectrumFit.cxx.

Member Function Documentation

◆ Area()

Double_t TSpectrumFit::Area ( Double_t  a,
Double_t  sigma,
Double_t  t,
Double_t  b 
)
protected

This function calculates area of a peak Function parameters:

  • a-amplitude of the peak
  • sigma-sigma of peak
  • t-relative amplitude
  • b-slope

Definition at line 569 of file TSpectrumFit.cxx.

◆ Dera1()

Double_t TSpectrumFit::Dera1 ( Double_t  i)
protected

Derivative of background according to a1.

Definition at line 492 of file TSpectrumFit.cxx.

◆ Dera2()

Double_t TSpectrumFit::Dera2 ( Double_t  i)
protected

Derivative of background according to a2.

Definition at line 500 of file TSpectrumFit.cxx.

◆ Deramp()

Double_t TSpectrumFit::Deramp ( Double_t  i,
Double_t  i0,
Double_t  sigma,
Double_t  t,
Double_t  s,
Double_t  b 
)
protected

This function calculates derivative of peak shape function (see manual) according to amplitude of peak.

Function parameters:

  • i-channel
  • i0-position of peak
  • sigma-sigma of peak
  • t, s-relative amplitudes
  • b-slope

Definition at line 229 of file TSpectrumFit.cxx.

◆ Derb()

Double_t TSpectrumFit::Derb ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma,
Double_t  t,
Double_t  b 
)
protected

This function calculates derivative of peaks shape function (see manual) according to slope b.

Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak
  • t-relative amplitude
  • b-slope

Definition at line 463 of file TSpectrumFit.cxx.

◆ Derderi0()

Double_t TSpectrumFit::Derderi0 ( Double_t  i,
Double_t  amp,
Double_t  i0,
Double_t  sigma 
)
protected

This function calculates second derivative of peak shape function (see manual) according to peak position.

Function parameters:

  • i-channel
  • amp-amplitude of peak
  • i0-position of peak
  • sigma-width of peak

Definition at line 303 of file TSpectrumFit.cxx.

◆ Derdersigma()

Double_t TSpectrumFit::Derdersigma ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma 
)
protected

This function calculates second derivative of peaks shape function (see manual) according to sigma of peaks.

Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak

Definition at line 376 of file TSpectrumFit.cxx.

◆ Derfc()

Double_t TSpectrumFit::Derfc ( Double_t  x)
protected

This function calculates derivative of error function of x.

Definition at line 200 of file TSpectrumFit.cxx.

◆ Deri0()

Double_t TSpectrumFit::Deri0 ( Double_t  i,
Double_t  amp,
Double_t  i0,
Double_t  sigma,
Double_t  t,
Double_t  s,
Double_t  b 
)
protected

This function calculates derivative of peak shape function (see manual) according to peak position.

Function parameters:

  • i-channel
  • amp-amplitude of peak
  • i0-position of peak
  • sigma-sigma of peak
  • t, s-relative amplitudes
  • b-slope

Definition at line 266 of file TSpectrumFit.cxx.

◆ Derpa()

Double_t TSpectrumFit::Derpa ( Double_t  sigma,
Double_t  t,
Double_t  b 
)
protected

This function calculates derivative of the area of peak according to its amplitude.

Function parameters:

  • sigma-sigma of peak
  • t-relative amplitudes
  • b-slope

Definition at line 592 of file TSpectrumFit.cxx.

◆ Derpb()

Double_t TSpectrumFit::Derpb ( Double_t  a,
Double_t  sigma,
Double_t  t,
Double_t  b 
)
protected

This function calculates derivative of the area of peak according to b parameter.

Function parameters:

  • sigma-sigma of peak
  • t-relative amplitudes
  • b-slope

Definition at line 658 of file TSpectrumFit.cxx.

◆ Derpsigma()

Double_t TSpectrumFit::Derpsigma ( Double_t  a,
Double_t  t,
Double_t  b 
)
protected

This function calculates derivative of the area of peak according to sigma of peaks.

Function parameters:

  • a-amplitude of peak
  • t-relative amplitudes
  • b-slope

Definition at line 614 of file TSpectrumFit.cxx.

◆ Derpt()

Double_t TSpectrumFit::Derpt ( Double_t  a,
Double_t  sigma,
Double_t  b 
)
protected

This function calculates derivative of the area of peak according to t parameter.

Function parameters:

  • sigma-sigma of peak
  • t-relative amplitudes
  • b-slope

Definition at line 636 of file TSpectrumFit.cxx.

◆ Ders()

Double_t TSpectrumFit::Ders ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma 
)
protected

This function calculates derivative of peaks shape function (see manual) according to relative amplitude s.

Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak

Definition at line 437 of file TSpectrumFit.cxx.

◆ Dersigma()

Double_t TSpectrumFit::Dersigma ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma,
Double_t  t,
Double_t  s,
Double_t  b 
)
protected

This function calculates derivative of peaks shape function (see manual) according to sigma of peaks.

Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak
  • t, s-relative amplitudes
  • b-slope

Definition at line 331 of file TSpectrumFit.cxx.

◆ Dert()

Double_t TSpectrumFit::Dert ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma,
Double_t  b 
)
protected

This function calculates derivative of peaks shape function (see manual) according to relative amplitude t.

Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak
  • b-slope

Definition at line 409 of file TSpectrumFit.cxx.

◆ Erfc()

Double_t TSpectrumFit::Erfc ( Double_t  x)
protected

Definition at line 177 of file TSpectrumFit.cxx.

◆ FitAwmi()

void TSpectrumFit::FitAwmi ( Double_t source)

This function fits the source spectrum.

The calling program should fill in input parameters of the TSpectrumFit class The fitted parameters are written into TSpectrumFit class output parameters and fitted data are written into source spectrum.

Function parameters:

  • source-pointer to the vector of source spectrum

Fitting

Goal: to estimate simultaneously peak shape parameters in spectra with large number of peaks

  • peaks can be fitted separately, each peak (or multiplets) in a region or together all peaks in a spectrum. To fit separately each peak one needs to determine the fitted region. However it can happen that the regions of neighbouring peaks are overlapping. Then the results of fitting are very poor. On the other hand, when fitting together all peaks found in a spectrum, one needs to have a method that is stable (converges) and fast enough to carry out fitting in reasonable time
  • we have implemented the non-symmetrical semi-empirical peak shape function [1]
  • it contains the symmetrical Gaussian as well as non-symmetrical terms.
spectrumfit_awmi_image001.gif

where T and S are relative amplitudes and B is slope.

  • algorithm without matrix inversion (AWMI) allows fitting tens, hundreds of peaks simultaneously that represent sometimes thousands of parameters [2], [5].

References:

[1] Phillps G.W., Marlow K.W., NIM 137 (1976) 525.

[2] I. A. Slavic: Nonlinear least-squares fitting without matrix inversion applied to complex Gaussian spectra analysis. NIM 134 (1976) 285-289.

[3] T. Awaya: A new method for curve fitting to the data with low statistics not using chi-square method. NIM 165 (1979) 317-323.

[4] T. Hauschild, M. Jentschel: Comparison of maximum likelihood estimation and chi-square statistics applied to counting experiments. NIM A 457 (2001) 384-401.

[5] M. Morhac, J. Kliman, M. Jandel, L. Krupa, V. Matouoek: Study of fitting algorithms applied to simultaneous analysis of large number of peaks in -ray spectra. Applied Spectroscopy, Vol. 57, No. 7, pp. 753-760, 2003

Example - script FitAwmi.c:

spectrumfit_awmi_image002.jpg
Fig. 1 Original spectrum (black line) and fitted spectrum using AWMI algorithm (red line) and number of iteration steps = 1000. Positions of fitted peaks are denoted by markers

Script:

Example to illustrate fitting function using AWMI algorithm. To execute this example, do:

root > .x FitAwmi.C

void FitAwmi() {
Int_t i,nfound=0,bin;
Int_t nbins = 256;
Int_t xmin = 0;
Int_t xmax = nbins;
Double_t * source = new Double_t[nbins];
Double_t * dest = new Double_t[nbins];
TH1F *h = new TH1F("h","Fitting using AWMI algorithm",nbins,xmin,xmax);
TH1F *d = new TH1F("d","",nbins,xmin,xmax);
TFile *f = new TFile("TSpectrum.root");
h=(TH1F*) f->Get("fit;1");
for (i = 0; i < nbins; i++) source[i]=h->GetBinContent(i + 1);
TCanvas *Fit1 = gROOT->GetListOfCanvases()->FindObject("Fit1");
if (!Fit1) Fit1 = new TCanvas("Fit1","Fit1",10,10,1000,700);
h->Draw("L");
TSpectrum *s = new TSpectrum();
//searching for candidate peaks positions
nfound = s->SearchHighRes(source, dest, nbins, 2, 0.1, kFALSE, 10000, kFALSE, 0);
Bool_t *FixPos =new Bool_t[nfound];
Bool_t *FixAmp = new Bool_t[nfound];
for(i = 0; i< nfound ; i++){
FixPos[i] = kFALSE;
FixAmp[i] = kFALSE;
}
//filling in the
initial estimates of the input parameters
Double_t *PosX = new Double_t[nfound];
Double_t *PosY = new Double_t[nfound];
PosX = s->GetPositionX();
for (i = 0; i < nfound; i++) {
a=PosX[i];
bin = 1 + Int_t(a + 0.5);
PosY[i] = h->GetBinContent(bin);
}
TSpectrumFit *pfit=new TSpectrumFit(nfound);
pfit->SetFitParameters(xmin, xmax-1, 1000, 0.1, pfit->kFitOptimChiCounts,
pfit->SetPeakParameters(2, kFALSE, PosX, (Bool_t *) FixPos, PosY, (Bool_t *) FixAmp);
pfit->FitAwmi(source);
Double_t *CalcPositions = new Double_t[nfound];
Double_t *CalcAmplitudes = new Double_t[nfound];
CalcPositions=pfit->GetPositions();
CalcAmplitudes=pfit->GetAmplitudes();
for (i = 0; i < nbins; i++) d->SetBinContent(i + 1,source[i]);
d->Draw("SAME L");
for (i = 0; i < nfound; i++) {
a=CalcPositions[i];
bin = 1 + Int_t(a + 0.5);
PosX[i] = d->GetBinCenter(bin);
PosY[i] = d->GetBinContent(bin);
}
TPolyMarker * pm = (TPolyMarker*)h->GetListOfFunctions()->FindObject("TPolyMarker");
if (pm) {
delete pm;
}
pm = new TPolyMarker(nfound, PosX, PosY);
pm->SetMarkerStyle(23);
pm->SetMarkerSize(1);
}

Definition at line 820 of file TSpectrumFit.cxx.

◆ FitStiefel()

void TSpectrumFit::FitStiefel ( Double_t source)

This function fits the source spectrum.

The calling program should fill in input parameters The fitted parameters are written into output parameters and fitted data are written into source spectrum.

Function parameters:

  • source-pointer to the vector of source spectrum

Example - script FitStiefel.c:

spectrumfit_stiefel_image001.jpg
Fig. 2 Original spectrum (black line) and fitted spectrum using Stiefel-Hestens method (red line) and number of iteration steps = 100. Positions of fitted peaks are denoted by markers

Script:

Example to illustrate fitting function using Stiefel-Hestens method. To execute this example, do:

root > .x FitStiefel.C

void FitStiefel() {
Int_t i,nfound=0,bin;
Int_t nbins = 256;
Int_t xmin = 0;
Int_t xmax = nbins;
Double_t * source = new Double_t[nbins];
Double_t * dest = new Double_t[nbins];
TH1F *h = new TH1F("h","Fitting using AWMI algorithm",nbins,xmin,xmax);
TH1F *d = new TH1F("d","",nbins,xmin,xmax);
TFile *f = new TFile("TSpectrum.root");
h=(TH1F*) f->Get("fit;1");
for (i = 0; i < nbins;i++) source[i]=h->GetBinContent(i + 1);
TCanvas *Fit1 = gROOT->GetListOfCanvases()->FindObject("Fit1");
if (!Fit1) Fit1 = new TCanvas("Fit1","Fit1",10,10,1000,700);
h->Draw("L");
TSpectrum *s = new TSpectrum();
//searching for candidate peaks positions
nfound = s->SearchHighRes(source, dest, nbins, 2, 0.1, kFALSE, 10000, kFALSE, 0);
Bool_t *FixPos = new Bool_t[nfound];
Bool_t *FixAmp = new Bool_t[nfound];
for(i = 0; i< nfound ; i++){
FixPos[i] = kFALSE;
FixAmp[i] = kFALSE;
}
//filling in the initial estimates of the input parameters
Double_t *PosX = new Double_t[nfound];
Double_t *PosY = new Double_t[nfound];
PosX = s->GetPositionX();
for (i = 0; i < nfound; i++) {
a=PosX[i];
bin = 1 + Int_t(a + 0.5);
PosY[i] = h->GetBinContent(bin);
}
TSpectrumFit *pfit = new TSpectrumFit(nfound);
pfit->SetFitParameters(xmin, xmax-1, 1000, 0.1, pfit->kFitOptimChiCounts,
pfit->SetPeakParameters(2, kFALSE, PosX, (Bool_t *) FixPos, PosY, (Bool_t *) FixAmp);
pfit->FitStiefel(source);
Double_t *CalcPositions = new Double_t[nfound];
Double_t *CalcAmplitudes = new Double_t[nfound];
CalcPositions=pfit->GetPositions();
CalcAmplitudes=pfit->GetAmplitudes();
for (i = 0; i < nbins; i++) d->SetBinContent(i + 1,source[i]);
d->Draw("SAMEL");
for (i = 0; i < nfound; i++) {
a=CalcPositions[i];
bin = 1 + Int_t(a + 0.5);
PosX[i] = d->GetBinCenter(bin);
PosY[i] = d->GetBinContent(bin);
}
TPolyMarker * pm = (TPolyMarker*)h->GetListOfFunctions()->FindObject("TPolyMarker");
if (pm) {
delete pm;
}
pm = new TPolyMarker(nfound, PosX, PosY);
pm->SetMarkerStyle(23);
pm->SetMarkerSize(1);
}

Definition at line 1857 of file TSpectrumFit.cxx.

◆ GetAmplitudes()

Double_t* TSpectrumFit::GetAmplitudes ( ) const
inline

Definition at line 116 of file TSpectrumFit.h.

◆ GetAmplitudesErrors()

Double_t* TSpectrumFit::GetAmplitudesErrors ( ) const
inline

Definition at line 117 of file TSpectrumFit.h.

◆ GetAreas()

Double_t* TSpectrumFit::GetAreas ( ) const
inline

Definition at line 118 of file TSpectrumFit.h.

◆ GetAreasErrors()

Double_t* TSpectrumFit::GetAreasErrors ( ) const
inline

Definition at line 119 of file TSpectrumFit.h.

◆ GetBackgroundParameters()

void TSpectrumFit::GetBackgroundParameters ( Double_t a0,
Double_t a0Err,
Double_t a1,
Double_t a1Err,
Double_t a2,
Double_t a2Err 
)

This function gets the background parameters and their errors.

  • a0 - gets the fitted value of a0 parameter
  • a0Err - gets error value of a0 parameter
  • a1 - gets the fitted value of a1 parameter
  • a1Err - gets error value of a1 parameter
  • a2 - gets the fitted value of a2 parameter
  • a2Err - gets error value of a2 parameter

Definition at line 2740 of file TSpectrumFit.cxx.

◆ GetChi()

Double_t TSpectrumFit::GetChi ( ) const
inline

Definition at line 121 of file TSpectrumFit.h.

◆ GetPositions()

Double_t* TSpectrumFit::GetPositions ( ) const
inline

Definition at line 122 of file TSpectrumFit.h.

◆ GetPositionsErrors()

Double_t* TSpectrumFit::GetPositionsErrors ( ) const
inline

Definition at line 123 of file TSpectrumFit.h.

◆ GetSigma()

void TSpectrumFit::GetSigma ( Double_t sigma,
Double_t sigmaErr 
)

This function gets the sigma parameter and its error.

  • sigma - gets the fitted value of sigma parameter
  • sigmaErr - gets error value of sigma parameter

Definition at line 2725 of file TSpectrumFit.cxx.

◆ GetTailParameters()

void TSpectrumFit::GetTailParameters ( Double_t t,
Double_t tErr,
Double_t b,
Double_t bErr,
Double_t s,
Double_t sErr 
)

This function gets the tail parameters and their errors.

  • t - gets the fitted value of t parameter
  • tErr - gets error value of t parameter
  • b - gets the fitted value of b parameter
  • bErr - gets error value of b parameter
  • s - gets the fitted value of s parameter
  • sErr - gets error value of s parameter

Definition at line 2760 of file TSpectrumFit.cxx.

◆ Ourpowl()

Double_t TSpectrumFit::Ourpowl ( Double_t  a,
Int_t  pw 
)
protected

Power function.

Definition at line 674 of file TSpectrumFit.cxx.

◆ SetBackgroundParameters()

void TSpectrumFit::SetBackgroundParameters ( Double_t  a0Init,
Bool_t  fixA0,
Double_t  a1Init,
Bool_t  fixA1,
Double_t  a2Init,
Bool_t  fixA2 
)

This function sets the following fitting parameters of background:

  • a0Init - initial value of a0 parameter (background is estimated as a0+a1*x+a2*x*x)
  • fixA0 - logical value of a0 parameter, which allows to fix the parameter (not to fit)
  • a1Init - initial value of a1 parameter
  • fixA1 - logical value of a1 parameter, which allows to fix the parameter (not to fit)
  • a2Init - initial value of a2 parameter
  • fixA2 - logical value of a2 parameter, which allows to fix the parameter (not to fit)

Definition at line 2691 of file TSpectrumFit.cxx.

◆ SetFitParameters()

void TSpectrumFit::SetFitParameters ( Int_t  xmin,
Int_t  xmax,
Int_t  numberIterations,
Double_t  alpha,
Int_t  statisticType,
Int_t  alphaOptim,
Int_t  power,
Int_t  fitTaylor 
)

This function sets the following fitting parameters:

  • xmin, xmax - fitting region
  • numberIterations - # of desired iterations in the fit
  • alpha - convergence coefficient, it should be positive number and <=1, for details see references
  • statisticType - type of statistics, possible values kFitOptimChiCounts (chi square statistics with counts as weighting coefficients), kFitOptimChiFuncValues (chi square statistics with function values as weighting coefficients),kFitOptimMaxLikelihood
  • alphaOptim - optimization of convergence algorithm, possible values kFitAlphaHalving, kFitAlphaOptimal
  • power - possible values kFitPower2,4,6,8,10,12, for details see references. It applies only for Awmi fitting function.
  • fitTaylor - order of Taylor expansion, possible values kFitTaylorOrderFirst, kFitTaylorOrderSecond. It applies only for Awmi fitting function.

Definition at line 2608 of file TSpectrumFit.cxx.

◆ SetPeakParameters()

void TSpectrumFit::SetPeakParameters ( Double_t  sigma,
Bool_t  fixSigma,
const Double_t positionInit,
const Bool_t fixPosition,
const Double_t ampInit,
const Bool_t fixAmp 
)

This function sets the following fitting parameters of peaks:

  • sigma - initial value of sigma parameter
  • fixSigma - logical value of sigma parameter, which allows to fix the parameter (not to fit)
  • positionInit - array of initial values of peaks positions
  • fixPosition - array of logical values which allow to fix appropriate positions (not fit). However they are present in the estimated functional.
  • ampInit - array of initial values of peaks amplitudes
  • fixAmp - array of logical values which allow to fix appropriate amplitudes (not fit). However they are present in the estimated functional

Definition at line 2656 of file TSpectrumFit.cxx.

◆ SetTailParameters()

void TSpectrumFit::SetTailParameters ( Double_t  tInit,
Bool_t  fixT,
Double_t  bInit,
Bool_t  fixB,
Double_t  sInit,
Bool_t  fixS 
)

This function sets the following fitting parameters of tails of peaks.

  • tInit - initial value of t parameter
  • fixT - logical value of t parameter, which allows to fix the parameter (not to fit)
  • bInit - initial value of b parameter
  • fixB - logical value of b parameter, which allows to fix the parameter (not to fit)
  • sInit - initial value of s parameter
  • fixS - logical value of s parameter, which allows to fix the parameter (not to fit)

Definition at line 2710 of file TSpectrumFit.cxx.

◆ Shape()

Double_t TSpectrumFit::Shape ( Int_t  num_of_fitted_peaks,
Double_t  i,
const Double_t parameter,
Double_t  sigma,
Double_t  t,
Double_t  s,
Double_t  b,
Double_t  a0,
Double_t  a1,
Double_t  a2 
)
protected

This function calculates peaks shape function (see manual) Function parameters:

  • num_of_fitted_peaks-number of fitted peaks
  • i-channel
  • parameter-array of peaks parameters (amplitudes and positions)
  • sigma-sigma of peak
  • t, s-relative amplitudes
  • b-slope
  • a0, a1, a2- background coefficients

Definition at line 516 of file TSpectrumFit.cxx.

◆ StiefelInversion()

void TSpectrumFit::StiefelInversion ( Double_t **  a,
Int_t  size 
)
protected

This function calculates solution of the system of linear equations.

The matrix a should have a dimension size*(size+4) The calling function should fill in the matrix, the column size should contain vector y (right side of the system of equations). The result is placed into size+1 column of the matrix. according to sigma of peaks.

Function parameters:

  • a-matrix with dimension size*(size+4)
  • size-number of rows of the matrix

Definition at line 1721 of file TSpectrumFit.cxx.

Member Data Documentation

◆ fA0Calc

Double_t TSpectrumFit::fA0Calc
protected

calculated value of background a0 parameter

Definition at line 51 of file TSpectrumFit.h.

◆ fA0Err

Double_t TSpectrumFit::fA0Err
protected

error value of background a0 parameter

Definition at line 52 of file TSpectrumFit.h.

◆ fA0Init

Double_t TSpectrumFit::fA0Init
protected

initial value of background a0 parameter(backgroud is estimated as a0+a1*x+a2*x*x)

Definition at line 50 of file TSpectrumFit.h.

◆ fA1Calc

Double_t TSpectrumFit::fA1Calc
protected

calculated value of background a1 parameter

Definition at line 54 of file TSpectrumFit.h.

◆ fA1Err

Double_t TSpectrumFit::fA1Err
protected

error value of background a1 parameter

Definition at line 55 of file TSpectrumFit.h.

◆ fA1Init

Double_t TSpectrumFit::fA1Init
protected

initial value of background a1 parameter(backgroud is estimated as a0+a1*x+a2*x*x)

Definition at line 53 of file TSpectrumFit.h.

◆ fA2Calc

Double_t TSpectrumFit::fA2Calc
protected

calculated value of background a2 parameter

Definition at line 57 of file TSpectrumFit.h.

◆ fA2Err

Double_t TSpectrumFit::fA2Err
protected

error value of background a2 parameter

Definition at line 58 of file TSpectrumFit.h.

◆ fA2Init

Double_t TSpectrumFit::fA2Init
protected

initial value of background a2 parameter(backgroud is estimated as a0+a1*x+a2*x*x)

Definition at line 56 of file TSpectrumFit.h.

◆ fAlpha

Double_t TSpectrumFit::fAlpha
protected

convergence coefficient, input parameter, it should be positive number and <=1, for details see references

Definition at line 28 of file TSpectrumFit.h.

◆ fAlphaOptim

Int_t TSpectrumFit::fAlphaOptim
protected

optimization of convergence algorithm, possible values kFitAlphaHalving, kFitAlphaOptimal

Definition at line 25 of file TSpectrumFit.h.

◆ fAmpCalc

Double_t* TSpectrumFit::fAmpCalc
protected

[fNPeaks] array of calculated values of fitted amplitudes, output parameters

Definition at line 34 of file TSpectrumFit.h.

◆ fAmpErr

Double_t* TSpectrumFit::fAmpErr
protected

[fNPeaks] array of amplitude errors

Definition at line 35 of file TSpectrumFit.h.

◆ fAmpInit

Double_t* TSpectrumFit::fAmpInit
protected

[fNPeaks] array of initial values of peaks amplitudes, input parameters

Definition at line 33 of file TSpectrumFit.h.

◆ fArea

Double_t* TSpectrumFit::fArea
protected

[fNPeaks] array of calculated areas of peaks

Definition at line 36 of file TSpectrumFit.h.

◆ fAreaErr

Double_t* TSpectrumFit::fAreaErr
protected

[fNPeaks] array of errors of peak areas

Definition at line 37 of file TSpectrumFit.h.

◆ fBCalc

Double_t TSpectrumFit::fBCalc
protected

calculated value of b parameter

Definition at line 45 of file TSpectrumFit.h.

◆ fBErr

Double_t TSpectrumFit::fBErr
protected

error value of b parameter

Definition at line 46 of file TSpectrumFit.h.

◆ fBInit

Double_t TSpectrumFit::fBInit
protected

initial value of b parameter (slope), for details see html manual and references

Definition at line 44 of file TSpectrumFit.h.

◆ fChi

Double_t TSpectrumFit::fChi
protected

here the fitting functions return resulting chi square

Definition at line 29 of file TSpectrumFit.h.

◆ fFitTaylor

Int_t TSpectrumFit::fFitTaylor
protected

order of Taylor expansion, possible values kFitTaylorOrderFirst, kFitTaylorOrderSecond. It applies only for Awmi fitting function.

Definition at line 27 of file TSpectrumFit.h.

◆ fFixA0

Bool_t TSpectrumFit::fFixA0
protected

logical value of a0 parameter, which allows to fix the parameter (not to fit).

Definition at line 65 of file TSpectrumFit.h.

◆ fFixA1

Bool_t TSpectrumFit::fFixA1
protected

logical value of a1 parameter, which allows to fix the parameter (not to fit).

Definition at line 66 of file TSpectrumFit.h.

◆ fFixA2

Bool_t TSpectrumFit::fFixA2
protected

logical value of a2 parameter, which allows to fix the parameter (not to fit).

Definition at line 67 of file TSpectrumFit.h.

◆ fFixAmp

Bool_t* TSpectrumFit::fFixAmp
protected

[fNPeaks] array of logical values which allow to fix appropriate amplitudes (not fit). However they are present in the estimated functional

Definition at line 60 of file TSpectrumFit.h.

◆ fFixB

Bool_t TSpectrumFit::fFixB
protected

logical value of b parameter, which allows to fix the parameter (not to fit).

Definition at line 63 of file TSpectrumFit.h.

◆ fFixPosition

Bool_t* TSpectrumFit::fFixPosition
protected

[fNPeaks] array of logical values which allow to fix appropriate positions (not fit). However they are present in the estimated functional

Definition at line 59 of file TSpectrumFit.h.

◆ fFixS

Bool_t TSpectrumFit::fFixS
protected

logical value of s parameter, which allows to fix the parameter (not to fit).

Definition at line 64 of file TSpectrumFit.h.

◆ fFixSigma

Bool_t TSpectrumFit::fFixSigma
protected

logical value of sigma parameter, which allows to fix the parameter (not to fit).

Definition at line 61 of file TSpectrumFit.h.

◆ fFixT

Bool_t TSpectrumFit::fFixT
protected

logical value of t parameter, which allows to fix the parameter (not to fit).

Definition at line 62 of file TSpectrumFit.h.

◆ fNPeaks

Int_t TSpectrumFit::fNPeaks
protected

number of peaks present in fit, input parameter, it should be > 0

Definition at line 20 of file TSpectrumFit.h.

◆ fNumberIterations

Int_t TSpectrumFit::fNumberIterations
protected

number of iterations in fitting procedure, input parameter, it should be > 0

Definition at line 21 of file TSpectrumFit.h.

◆ fPositionCalc

Double_t* TSpectrumFit::fPositionCalc
protected

[fNPeaks] array of calculated values of fitted positions, output parameters

Definition at line 31 of file TSpectrumFit.h.

◆ fPositionErr

Double_t* TSpectrumFit::fPositionErr
protected

[fNPeaks] array of position errors

Definition at line 32 of file TSpectrumFit.h.

◆ fPositionInit

Double_t* TSpectrumFit::fPositionInit
protected

[fNPeaks] array of initial values of peaks positions, input parameters

Definition at line 30 of file TSpectrumFit.h.

◆ fPower

Int_t TSpectrumFit::fPower
protected

possible values kFitPower2,4,6,8,10,12, for details see references. It applies only for Awmi fitting function.

Definition at line 26 of file TSpectrumFit.h.

◆ fSCalc

Double_t TSpectrumFit::fSCalc
protected

calculated value of s parameter

Definition at line 48 of file TSpectrumFit.h.

◆ fSErr

Double_t TSpectrumFit::fSErr
protected

error value of s parameter

Definition at line 49 of file TSpectrumFit.h.

◆ fSigmaCalc

Double_t TSpectrumFit::fSigmaCalc
protected

calculated value of sigma parameter

Definition at line 39 of file TSpectrumFit.h.

◆ fSigmaErr

Double_t TSpectrumFit::fSigmaErr
protected

error value of sigma parameter

Definition at line 40 of file TSpectrumFit.h.

◆ fSigmaInit

Double_t TSpectrumFit::fSigmaInit
protected

initial value of sigma parameter

Definition at line 38 of file TSpectrumFit.h.

◆ fSInit

Double_t TSpectrumFit::fSInit
protected

initial value of s parameter (relative amplitude of step), for details see html manual and references

Definition at line 47 of file TSpectrumFit.h.

◆ fStatisticType

Int_t TSpectrumFit::fStatisticType
protected

type of statistics, possible values kFitOptimChiCounts (chi square statistics with counts as weighting coefficients), kFitOptimChiFuncValues (chi square statistics with function values as weighting coefficients),kFitOptimMaxLikelihood

Definition at line 24 of file TSpectrumFit.h.

◆ fTCalc

Double_t TSpectrumFit::fTCalc
protected

calculated value of t parameter

Definition at line 42 of file TSpectrumFit.h.

◆ fTErr

Double_t TSpectrumFit::fTErr
protected

error value of t parameter

Definition at line 43 of file TSpectrumFit.h.

◆ fTInit

Double_t TSpectrumFit::fTInit
protected

initial value of t parameter (relative amplitude of tail), for details see html manual and references

Definition at line 41 of file TSpectrumFit.h.

◆ fXmax

Int_t TSpectrumFit::fXmax
protected

last fitted channel

Definition at line 23 of file TSpectrumFit.h.

◆ fXmin

Int_t TSpectrumFit::fXmin
protected

first fitted channel

Definition at line 22 of file TSpectrumFit.h.

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