73 template <
class FitObject>
76 template <
class FitObject>
79 template <
class FitObject>
89 Error(
"Fit",
"function may not be null pointer");
93 Error(
"Fit",
"function is zombie");
99 Error(
"Fit",
"function %s has illegal number of parameters = %d", f1->
GetName(), npar);
105 Error(
"Fit",
"function %s dimension, %d, is greater than fit object dimension, %d",
110 Error(
"Fit",
"function %s dimension, %d, is smaller than fit object dimension -1, %d",
122 Double_t fxmin, fymin, fzmin, fxmax, fymax, fzmax;
123 f1.
GetRange(fxmin, fymin, fzmin, fxmax, fymax, fzmax);
132 template<
class FitObject>
145 if (iret != 0)
return iret;
151 if (fitOption.
Integral)
Info(
"Fit",
"Ignore Integral option. Model function dimension is less than the data object dimension");
152 if (fitOption.
Like)
Info(
"Fit",
"Ignore Likelihood option. Model function dimension is less than the data object dimension");
160 if (special==299+npar) linear =
kTRUE;
166 std::shared_ptr<TFitResult> tfr(
new TFitResult() );
168 std::shared_ptr<ROOT::Fit::Fitter> fitter(
new ROOT::Fit::Fitter(std::static_pointer_cast<ROOT::Fit::FitResult>(tfr) ) );
197 printf(
" range in x = [%f,%f] \n",x1,x2);
204 if (fitdata->Size() == 0 ) {
205 Warning(
"Fit",
"Fit data is empty ");
210 printf(
"HFit:: data size is %d \n",fitdata->Size());
211 for (
unsigned int i = 0; i < fitdata->Size(); ++i) {
212 if (fitdata->NDim() == 1)
printf(
" x[%d] = %f - value = %f \n", i,*(fitdata->Coords(i)),fitdata->Value(i) );
222 if (special != 0 && !fitOption.
Bound && !linear) {
235 if ( (linear || fitOption.
Gradient) )
243 if (
int(fitdata->NDim()) == hdim -1 ) fitConfig.
SetNormErrors(
true);
251 for (
int i = 0; i < npar; ++i) {
257 if (plow*pup != 0 && plow >= pup) {
260 else if (plow < pup ) {
275 double step = 0.1 * (pup - plow);
277 if ( parSettings.
Value() < pup && pup - parSettings.
Value() < 2 * step )
278 step = (pup - parSettings.
Value() ) / 2;
279 else if ( parSettings.
Value() > plow && parSettings.
Value() - plow < 2 * step )
280 step = (parSettings.
Value() - plow ) / 2;
309 std::string
type =
"Robust";
335 if (fitOption.
Like)
printf(
"do likelihood fit...\n");
336 if (linear)
printf(
"do linear fit...\n");
337 printf(
"do now fit...\n");
352 if (fitOption.
User && userFcn)
353 fitok = fitter->FitFCN( userFcn );
354 else if (fitOption.
Like) {
356 bool weight = ((fitOption.
Like & 2) == 2);
358 bool extended = ((fitOption.
Like & 4 ) != 4 );
360 fitok = fitter->LikelihoodFit(*fitdata, extended);
363 fitok = fitter->Fit(*fitdata);
366 if ( !fitok && !fitOption.
Quiet )
367 Warning(
"Fit",
"Abnormal termination of minimization.");
373 iret = fitResult.
Status();
397 if (!fitOption.
Quiet) {
398 if (fitter->GetMinimizer() && fitConfig.
MinimizerType() ==
"Minuit" &&
400 fitter->GetMinimizer()->PrintResults();
405 fitResult.
Print(std::cout);
418 bcfitter->
SetFCN(userFcn);
439 name = name + h1->GetName() +
"-" + f1->
GetName();
441 title += h1->GetTitle();
443 tfr->SetTitle(title);
458 if (range.
Size(0) == 0) {
469 if (range.
Size(1) == 0) {
480 if (range.
Size(2) == 0) {
491 std::cout <<
"xmin,xmax" << xmin <<
" " <<
xmax << std::endl;
510 else if (range.
Size(0) == 0) {
517 double x1 = 0,
x2 = 0, y1 = 0, y2 = 0;
518 g->ComputeRange(x1,y1,
x2,y2);
519 if (x1 < xmin) xmin =
x1;
520 if (
x2 > xmax) xmax =
x2;
532 if (range.
Size(0) == 0) {
537 if (range.
Size(1) == 0) {
550 for (
int i = 0; i < ndim; ++i ) {
551 if ( range.
Size(i) == 0 ) {
558 template<
class FitObject>
564 std::cout <<
"draw and store fit function " << f1->
GetName() << std::endl;
576 std::cout <<
"draw and store fit function " << f1->
GetName()
577 <<
" Range in x = [ " << xmin <<
" , " <<
xmax <<
" ]" << std::endl;
580 TList * funcList = h1->GetListOfFunctions();
582 Error(
"StoreAndDrawFitFunction",
"Function list has not been created - cannot store the fitted function");
590 bool reuseOldFunction =
false;
591 if (delOldFunction) {
594 while ((obj =
next())) {
601 reuseOldFunction =
true;
613 if (!reuseOldFunction) {
614 fnew1 = (
TF1*)f1->IsA()->New();
617 funcList->
Add(fnew1);
627 }
else if (ndim < 3) {
628 if (!reuseOldFunction) {
629 fnew2 = (
TF2*)f1->IsA()->New();
632 funcList->
Add(fnew2);
635 fnew2 =
dynamic_cast<TF2*
>(
f1);
644 if (!reuseOldFunction) {
645 fnew3 = (
TF3*)f1->IsA()->New();
648 funcList->
Add(fnew3);
651 fnew2 =
dynamic_cast<TF3*
>(
f1);
662 if (drawFunction && ndim < 3 && h1->InheritsFrom(
TH1::Class() ) ) {
665 if (!
gPad || (
gPad &&
gPad->GetListOfPrimitives()->FindObject(h1) ==
NULL ) )
678 if (option == 0)
return;
679 if (!option[0])
return;
704 else if (type ==
kGraph) {
713 int numpos = start + strlen(
"H=0.");
716 while( (numpos+numlen<len) && isdigit(opt[numpos+numlen]) ) numlen++;
717 TString num = opt(numpos,numlen);
718 opt.
Remove(start+strlen(
"H"),strlen(
"=0.")+numlen);
719 h = atof(num.
Data());
737 if (fitOption.
Like == 1) {
741 if (fitOption.
Like == 2) fitOption.
Like = 6;
742 else fitOption.
Like = 4;
747 if (fitOption.
Chi2 == 1 || fitOption.
PChi2 == 1)
748 Warning(
"Fit",
"Cannot use P or X option in combination of L. Ignore the chi2 option and perform a likelihood fit");
772 Info(
"CheckGraphFitOptions",
"L (Log Likelihood fit) is an invalid option when fitting a graph. It is ignored");
776 Info(
"CheckGraphFitOptions",
"I (use function integral) is an invalid option when fitting a graph. It is ignored");
788 std::shared_ptr<ROOT::Fit::UnBinData> fitdata(data);
791 printf(
"tree data size is %d \n",fitdata->Size());
792 for (
unsigned int i = 0; i < fitdata->Size(); ++i) {
793 if (fitdata->NDim() == 1)
printf(
" x[%d] = %f \n", i,*(fitdata->Coords(i) ) );
796 if (fitdata->Size() == 0 ) {
797 Warning(
"Fit",
"Fit data is empty ");
802 std::shared_ptr<TFitResult> tfr(
new TFitResult() );
808 unsigned int dim = fitdata->NDim();
823 for (
int i = 0; i < npar; ++i) {
828 if (plow*pup != 0 && plow >= pup) {
831 else if (plow < pup ) {
846 double step = 0.1 * (pup - plow);
848 if ( parSettings.
Value() < pup && pup - parSettings.
Value() < 2 * step )
849 step = (pup - parSettings.
Value() ) / 2;
850 else if ( parSettings.
Value() > plow && parSettings.
Value() - plow < 2 * step )
851 step = (parSettings.
Value() - plow ) / 2;
873 if ( (fitOption.
Like & 2) == 2)
876 bool extended = (fitOption.
Like & 1) == 1;
879 fitok = fitter->LikelihoodFit(fitdata, extended);
880 if ( !fitok && !fitOption.
Quiet )
881 Warning(
"UnBinFit",
"Abnormal termination of minimization.");
885 int iret = fitResult.
Status();
908 if (lastFitter)
delete lastFitter;
922 name = name +
"UnBinData-" + fitfunc->
GetName();
926 tfr->SetTitle(title);
941 Warning(
"HFit::FitObject",
"A weighted likelihood fit is requested but histogram is not weighted - do a standard Likelihood fit");
945 return HFit::Fit(h1,f1,foption,moption,goption,range);
952 return HFit::Fit(gr,f1,foption,moption,goption,range);
959 return HFit::Fit(gr,f1,foption,moption,goption,range);
966 return HFit::Fit(gr,f1,foption,moption,goption,range);
971 return HFit::Fit(s1,f1,foption,moption,goption,range);
998 template<
class FitObject>
1009 if (data.
Size() == 0 ) {
1010 Warning(
"Chisquare",
"data set is empty - return -1");
Int_t GetFirst() const
Return first bin on the axis i.e.
const std::string & MinimizerType() const
return type of minimizer package
virtual void SetParameters(const Double_t *params)
void PrintCovMatrix(std::ostream &os) const
print error matrix and correlations
void SetPrintLevel(int level)
set print level
void SetTolerance(double tol)
set the tolerance
virtual Bool_t InheritsFrom(const char *classname) const
Returns kTRUE if object inherits from class "classname".
ClassImp(TSeqCollection) Int_t TSeqCollection TIter next(this)
Return index of object in collection.
TList * GetListOfGraphs() const
const std::vector< double > & Errors() const
parameter errors (return st::vector)
virtual void Save(Double_t xmin, Double_t xmax, Double_t ymin, Double_t ymax, Double_t zmin, Double_t zmax)
Save values of function in array fSave.
virtual void SetMethodCall(TMethodCall *m)
Class to Wrap a ROOT Function class (like TF1) in a IParamMultiFunction interface of multi-dimensions...
TString & ReplaceAll(const TString &s1, const TString &s2)
Double_t GetXmax() const
Returns the X maximum.
Class, describing value, limits and step size of the parameters Provides functionality also to set/re...
virtual void SetUserFunc(TObject *userfunc)
virtual Int_t GetDimension() const
unsigned int Ndf() const
Number of degree of freedom.
A TMultiGraph is a collection of TGraph (or derived) objects.
Double_t GetYmax() const
Returns the Y maximum.
virtual void SetRange(Double_t xmin, Double_t xmax)
Initialize the upper and lower bounds to draw the function.
void ToUpper()
Change string to upper case.
virtual void Save(Double_t xmin, Double_t xmax, Double_t ymin, Double_t ymax, Double_t zmin, Double_t zmax)
Save values of function in array fSave.
virtual Double_t GetBinLowEdge(Int_t bin) const
Return low edge of bin.
void(* FCNFunc_t)(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag)
virtual void SetNumberFitPoints(Int_t npfits)
virtual void SetFCN(void(*fcn)(Int_t &, Double_t *, Double_t &f, Double_t *, Int_t))
Override setFCN to use the Adapter to Minuit2 FCN interface To set the address of the minimization fu...
Class describing the unbinned data sets (just x coordinates values) of any dimensions.
Backward compatible implementation of TVirtualFitter.
virtual Double_t GetParError(Int_t ipar) const
Return value of parameter number ipar.
virtual Double_t GetBinWidth(Int_t bin) const
Return bin width.
TH1F * GetHistogram() const
Returns a pointer to the histogram used to draw the axis Takes into account the two following cases...
ROOT::Math::MinimizerOptions & MinimizerOptions()
access to the minimizer control parameter (non const method)
LongDouble_t Power(LongDouble_t x, LongDouble_t y)
void SetBit(UInt_t f, Bool_t set)
Set or unset the user status bits as specified in f.
const std::vector< double > & Parameters() const
parameter values (return std::vector)
Double_t GetXmin() const
Returns the X minimum.
unsigned int Size() const
return number of fit points
TFitResultPtr UnBinFit(ROOT::Fit::UnBinData *data, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption)
fit an unbin data set (from tree or from histogram buffer) using a TF1 pointer and fit options...
const char * Data() const
virtual void SetParent(TObject *p=0)
static const double x2[5]
Int_t GetNdimensions() const
int GetDimension(const TH1 *h1)
Extends the ROOT::Fit::Result class with a TNamed inheritance providing easy possibility for I/O...
virtual void Copy(TObject &f1) const
Copy this F1 to a new F1.
void GetDrawingRange(TH1 *h1, ROOT::Fit::DataRange &range)
if(pyself &&pyself!=Py_None)
void Info(const char *location, const char *msgfmt,...)
void Fix()
fix the parameter
bool NormalizeErrors() const
flag to check if resulting errors are be normalized according to chi2/ndf
virtual Bool_t IsLinear() const
virtual void GetRange(Double_t *xmin, Double_t *xmax) const
Return range of a generic N-D function.
void Error(const char *location, const char *msgfmt,...)
virtual void GetParLimits(Int_t ipar, Double_t &parmin, Double_t &parmax) const
Return limits for parameter ipar.
void SetLowerLimit(double low)
set a single lower limit
static void SetFitter(TVirtualFitter *fitter, Int_t maxpar=25)
Static function to set an alternative fitter.
int GetDimension(const THnBase *s1)
int CheckFitFunction(const TF1 *f1, int hdim)
void SetMinosErrors(bool on=true)
set Minos erros computation to be performed after fitting
Chi2FCN class for binnned fits using the least square methods.
virtual void SetObjectFit(TObject *obj)
unsigned int Size(unsigned int icoord=0) const
return range size for coordinate icoord (starts from zero) Size == 0 indicates no range is present [-...
void InitGaus(const ROOT::Fit::BinData &data, TF1 *f1)
compute initial parameter for gaussian function given the fit data Set the sigma limits for zero top ...
virtual void SetChisquare(Double_t chi2)
void SetMinimizer(const char *type, const char *algo=0)
set minimizer type
void SetStepSize(double err)
set the step size
void FillData(BinData &dv, const TH1 *hist, TF1 *func=0)
fill the data vector from a TH1.
DataOptions : simple structure holding the options on how the data are filled.
Class to manage histogram axis.
TPaveLabel title(3, 27.1, 15, 28.7,"ROOT Environment and Tools")
A 3-Dim function with parameters.
int Status() const
minimizer status code
Fitter class, entry point for performing all type of fits.
virtual TObject * Remove(TObject *obj)
Remove object from the list.
virtual void SetFitOption(Foption_t option)
Provides an indirection to the TFitResult class and with a semantics identical to a TFitResult pointe...
const ParameterSettings & ParSettings(unsigned int i) const
get the parameter settings for the i-th parameter (const method)
Bool_t TestBit(UInt_t f) const
void FitOptionsMake(const char *option, Foption_t &fitOption)
Double_t GetYmin() const
Returns the Y minimum.
virtual Int_t GetNdim() const
static TVirtualFitter * GetFitter()
static: return the current Fitter
virtual const char * GetName() const
Returns name of object.
virtual Int_t GetSumw2N() const
double Chisquare(const TH1 &h1, TF1 &f1, bool useRange)
compute the chi2 value for an histogram given a function (see TH1::Chisquare for the documentation) ...
Class describing the binned data sets : vectors of x coordinates, y values and optionally error on y ...
TAxis * GetAxis(Int_t dim) const
double ComputeChi2(const FitObject &h1, TF1 &f1, bool useRange)
A 2-Dim function with parameters.
void InitExpo(const ROOT::Fit::BinData &data, TF1 *f1)
compute initial parameter for an exponential function given the fit data Set the constant and slope a...
void Warning(const char *location, const char *msgfmt,...)
virtual void PrintResults(Int_t level, Double_t amin) const
Print the fit result.
void SetMinimizerOptions(const ROOT::Math::MinimizerOptions &minopt)
set all the minimizer options using class MinimizerOptions
TString & Remove(Ssiz_t pos)
void AddRange(unsigned int icoord, double xmin, double xmax)
add a range [xmin,xmax] for the new coordinate icoord Adding a range does not delete existing one...
virtual void SetRange(Double_t xmin, Double_t xmax)
Initialize the upper and lower bounds to draw the function.
class containg the result of the fit and all the related information (fitted parameter values...
void GetFunctionRange(const TF1 &f1, ROOT::Fit::DataRange &range)
static const double x1[5]
class describing the range in the coordinates it supports multiple range in a coordinate.
void Init2DGaus(const ROOT::Fit::BinData &data, TF1 *f1)
compute initial parameter for 2D gaussian function given the fit data Set the sigma limits for zero t...
TFitResultPtr Fit(FitObject *h1, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption, const char *goption, ROOT::Fit::DataRange &range)
ClassImp(TMCParticle) void TMCParticle printf(": p=(%7.3f,%7.3f,%9.3f) ;", fPx, fPy, fPz)
void SetWeightCorrection(bool on=true)
apply the weight correction for error matric computation
void Print(std::ostream &os, bool covmat=false) const
print the result and optionaly covariance matrix and correlations
TH1F * GetHistogram() const
Returns a pointer to the histogram used to draw the axis.
virtual Int_t GetNumber() const
void FitOptionsMake(EFitObjectType type, const char *option, Foption_t &fitOption)
Decode list of options into fitOption.
Abstract Base Class for Fitting.
Int_t GetLast() const
Return last bin on the axis i.e.
Mother of all ROOT objects.
virtual Double_t * GetParameters() const
void StoreAndDrawFitFunction(FitObject *h1, TF1 *f1, const ROOT::Fit::DataRange &range, bool, bool, const char *goption)
std::string ToString(const T &val)
Utility function for conversion to strings.
virtual void SetRange(Double_t xmin, Double_t xmax)
Initialize the upper and lower bounds to draw the function.
virtual void Add(TObject *obj)
virtual void SetParErrors(const Double_t *errors)
Set errors for all active parameters when calling this function, the array errors must have at least ...
double Value() const
copy constructor and assignment operators (leave them to the compiler)
TMethodCall * GetMethodCall() const
virtual Bool_t AddToGlobalList(Bool_t on=kTRUE)
Add to global list of functions (gROOT->GetListOfFunctions() ) return previous status (true of functi...
Bool_t Contains(const char *pat, ECaseCompare cmp=kExact) const
void SetNormErrors(bool on=true)
set the option to normalize the error on the result according to chi2/ndf
void SetUpperLimit(double up)
set a single upper limit
A Graph is a graphics object made of two arrays X and Y with npoints each.
virtual void SetNDF(Int_t ndf)
Set the number of degrees of freedom ndf should be the number of points used in a fit - the number of...
double Chi2() const
Chi2 fit value in case of likelihood must be computed ?
void SetLimits(double low, double up)
set a double side limit, if low == up the parameter is fixed if low > up the limits are removed ...
Multidimensional histogram base.
TFitResultPtr FitObject(TH1 *h1, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption, const char *goption, ROOT::Fit::DataRange &range)
fitting function for a TH1 (called from TH1::Fit)
const Bool_t kIterBackward
void SetParabErrors(bool on=true)
set parabolic erros
Ssiz_t Index(const char *pat, Ssiz_t i=0, ECaseCompare cmp=kExact) const
Graphics object made of three arrays X, Y and Z with the same number of points each.
bool IsEmpty() const
True if a fit result does not exist (even invalid) with parameter values.
void GetRange(unsigned int icoord, double &xmin, double &xmax) const
get the first range for given coordinate.
virtual Int_t GetNpar() const
void CheckGraphFitOptions(Foption_t &fitOption)
Class describing the configuration of the fit, options and parameter settings using the ROOT::Fit::Pa...
virtual void Save(Double_t xmin, Double_t xmax, Double_t ymin, Double_t ymax, Double_t zmin, Double_t zmax)
Save values of function in array fSave.