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class TProfile: public TH1D


  Profile histograms are used to display the mean
  value of Y and its RMS for each bin in X. Profile histograms are in many cases an
  elegant replacement of two-dimensional histograms : the inter-relation of two
  measured quantities X and Y can always be visualized by a two-dimensional
  histogram or scatter-plot; its representation on the line-printer is not particularly
  satisfactory, except for sparse data. If Y is an unknown (but single-valued)
  approximate function of X, this function is displayed by a profile histogram with
  much better precision than by a scatter-plot.

  The following formulae show the cumulated contents (capital letters) and the values
  displayed by the printing or plotting routines (small letters) of the elements for bin J.

                                                    2
      H(J)  =  sum Y                  E(J)  =  sum Y
      l(J)  =  sum l                  L(J)  =  sum l
      h(J)  =  H(J)/L(J)              s(J)  =  sqrt(E(J)/L(J)- h(J)**2)
      e(J)  =  s(J)/sqrt(L(J))

  In the special case where s(J) is zero (eg, case of 1 entry only in one bin)
  e(J) is computed from the average of the s(J) for all bins if the static function
  TProfile::Approximate has been called.
  This simple/crude approximation was suggested in order to keep the bin
  during a fit operation. But note that this approximation is not the default behaviour.

           Example of a profile histogram with its graphics output
{
  TCanvas *c1 = new TCanvas("c1","Profile histogram example",200,10,700,500);
  hprof  = new TProfile("hprof","Profile of pz versus px",100,-4,4,0,20);
  Float_t px, py, pz;
  for ( Int_t i=0; i<25000; i++) {
     gRandom->Rannor(px,py);
     pz = px*px + py*py;
     hprof->Fill(px,pz,1);
  }
  hprof->Draw();
}

/* */

Function Members (Methods)

public:
TProfile()
TProfile(const TProfile& profile)
TProfile(const char* name, const char* title, Int_t nbinsx, const Float_t* xbins, Option_t* option = "")
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Option_t* option = "")
TProfile(const char* name, const char* title, Int_t nbinsx, Double_t xlow, Double_t xup, Option_t* option = "")
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Double_t ylow, Double_t yup, Option_t* option = "")
TProfile(const char* name, const char* title, Int_t nbinsx, Double_t xlow, Double_t xup, Double_t ylow, Double_t yup, Option_t* option = "")
virtual~TProfile()
voidTObject::AbstractMethod(const char* method) const
virtual voidAdd(const TH1* h1, Double_t c1 = 1)
virtual voidAdd(TF1* h1, Double_t c1 = 1, Option_t* option = "")
virtual voidAdd(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1)MENU
voidTArrayD::AddAt(Double_t c, Int_t i)
virtual voidTH1D::AddBinContent(Int_t bin)
virtual voidTH1D::AddBinContent(Int_t bin, Double_t w)
static voidTH1::AddDirectory(Bool_t add = kTRUE)
static Bool_tTH1::AddDirectoryStatus()
voidTArrayD::Adopt(Int_t n, Double_t* array)
virtual voidTObject::AppendPad(Option_t* option = "")
static voidApproximate(Bool_t approx = kTRUE)
Double_tTArrayD::At(Int_t i) const
virtual voidTH1::Browse(TBrowser* b)
virtual Int_tBufferEmpty(Int_t action = 0)
voidBuildOptions(Double_t ymin, Double_t ymax, Option_t* option)
virtual Double_tTH1::Chi2Test(const TH1* h2, Option_t* option = "UU", Double_t* res = 0) const
virtual Double_tTH1::Chi2TestX(const TH1* h2, Double_t& chi2, Int_t& ndf, Int_t& igood, Option_t* option = "UU", Double_t* res = 0) const
static TClass*Class()
virtual const char*TObject::ClassName() const
virtual voidTNamed::Clear(Option_t* option = "")
virtual TObject*TNamed::Clone(const char* newname = "") const
virtual Int_tTNamed::Compare(const TObject* obj) const
virtual Double_tTH1::ComputeIntegral()
virtual voidCopy(TObject& hnew) const
virtual voidTObject::Delete(Option_t* option = "")MENU
virtual voidTH1::DirectoryAutoAdd(TDirectory*)
Int_tTAttLine::DistancetoLine(Int_t px, Int_t py, Double_t xp1, Double_t yp1, Double_t xp2, Double_t yp2)
virtual Int_tTH1::DistancetoPrimitive(Int_t px, Int_t py)
virtual voidDivide(const TH1* h1)
virtual voidDivide(TF1* h1, Double_t c1 = 1)
virtual voidDivide(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option = "")MENU
virtual voidTH1::Draw(Option_t* option = "")
virtual voidTObject::DrawClass() constMENU
virtual TObject*TObject::DrawClone(Option_t* option = "") constMENU
virtual TH1*DrawCopy(Option_t* option = "") const
virtual TH1*TH1::DrawNormalized(Option_t* option = "", Double_t norm = 1) const
virtual voidTH1::DrawPanel()MENU
virtual voidTObject::Dump() constMENU
virtual voidTObject::Error(const char* method, const char* msgfmt) const
virtual voidTH1::Eval(TF1* f1, Option_t* option = "")
virtual voidTObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual voidTObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual voidTH1::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual TH1*TH1::FFT(TH1* h_output, Option_t* option)
virtual Int_tFill(Double_t x, Double_t y)
virtual Int_tFill(const char* namex, Double_t y)
virtual Int_tFill(Double_t x, Double_t y, Double_t w)
virtual Int_tFill(const char* namex, Double_t y, Double_t w)
virtual voidTNamed::FillBuffer(char*& buffer)
virtual voidFillN(Int_t ntimes, const Double_t* x, const Double_t* y, const Double_t* w, Int_t stride = 1)
virtual voidTH1::FillRandom(const char* fname, Int_t ntimes = 5000)
virtual voidTH1::FillRandom(TH1* h, Int_t ntimes = 5000)
virtual Int_tTH1::FindBin(Double_t x, Double_t y = 0, Double_t z = 0)
virtual Int_tTH1::FindFirstBinAbove(Double_t threshold = 0, Int_t axis = 1) const
virtual Int_tTH1::FindFixBin(Double_t x, Double_t y = 0, Double_t z = 0) const
virtual Int_tTH1::FindLastBinAbove(Double_t threshold = 0, Int_t axis = 1) const
virtual TObject*TH1::FindObject(const char* name) const
virtual TObject*TH1::FindObject(const TObject* obj) const
virtual TFitResultPtrTH1::Fit(const char* formula, Option_t* option = "", Option_t* goption = "", Double_t xmin = 0, Double_t xmax = 0)MENU
virtual TFitResultPtrTH1::Fit(TF1* f1, Option_t* option = "", Option_t* goption = "", Double_t xmin = 0, Double_t xmax = 0)
static Int_tTH1::FitOptionsMake(Option_t* option, Foption_t& Foption)
virtual voidTH1::FitPanel()MENU
const Double_t*TArrayD::GetArray() const
Double_t*TArrayD::GetArray()
TH1*TH1::GetAsymmetry(TH1* h2, Double_t c2 = 1, Double_t dc2 = 0)
virtual Double_tTArrayD::GetAt(Int_t i) const
virtual Color_tTH1::GetAxisColor(Option_t* axis = "X") const
virtual Float_tTH1::GetBarOffset() const
virtual Float_tTH1::GetBarWidth() const
virtual Int_tTH1::GetBin(Int_t binx, Int_t biny = 0, Int_t binz = 0) const
virtual Double_tTH1::GetBinCenter(Int_t bin) const
virtual Double_tGetBinContent(Int_t bin) const
virtual Double_tGetBinContent(Int_t bin, Int_t) const
virtual Double_tGetBinContent(Int_t bin, Int_t, Int_t) const
virtual Double_tGetBinEffectiveEntries(Int_t bin) const
virtual Double_tGetBinEntries(Int_t bin) const
virtual Double_tGetBinError(Int_t bin) const
virtual Double_tGetBinError(Int_t bin, Int_t) const
virtual Double_tGetBinError(Int_t bin, Int_t, Int_t) const
virtual Double_tTH1::GetBinLowEdge(Int_t bin) const
virtual TArrayD*GetBinSumw2()
virtual const TArrayD*GetBinSumw2() const
virtual Double_tTH1::GetBinWidth(Int_t bin) const
virtual Double_tTH1::GetBinWithContent(Double_t c, Int_t& binx, Int_t firstx = 0, Int_t lastx = 0, Double_t maxdiff = 0) const
virtual voidTH1::GetBinXYZ(Int_t binglobal, Int_t& binx, Int_t& biny, Int_t& binz) const
const Double_t*TH1::GetBuffer() const
Int_tTH1::GetBufferLength() const
Int_tTH1::GetBufferSize() const
virtual Double_tTH1::GetCellContent(Int_t binx, Int_t biny) const
virtual Double_tTH1::GetCellError(Int_t binx, Int_t biny) const
virtual voidTH1::GetCenter(Double_t* center) const
virtual Int_tTH1::GetContour(Double_t* levels = 0)
virtual Double_tTH1::GetContourLevel(Int_t level) const
virtual Double_tTH1::GetContourLevelPad(Int_t level) const
static Int_tTH1::GetDefaultBufferSize()
static Bool_tTH1::GetDefaultSumw2()
virtual Int_tTH1::GetDimension() const
TDirectory*TH1::GetDirectory() const
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
virtual Double_tTH1::GetEffectiveEntries() const
virtual Double_tTH1::GetEntries() const
Option_t*GetErrorOption() const
virtual Color_tTAttFill::GetFillColor() const
virtual Style_tTAttFill::GetFillStyle() const
virtual TF1*TH1::GetFunction(const char* name) const
virtual const char*TObject::GetIconName() const
virtual Double_t*TH1::GetIntegral()
virtual Double_tTH1::GetKurtosis(Int_t axis = 1) const
virtual Color_tTH1::GetLabelColor(Option_t* axis = "X") const
virtual Style_tTH1::GetLabelFont(Option_t* axis = "X") const
virtual Float_tTH1::GetLabelOffset(Option_t* axis = "X") const
virtual Float_tTH1::GetLabelSize(Option_t* axis = "X") const
virtual Color_tTAttLine::GetLineColor() const
virtual Style_tTAttLine::GetLineStyle() const
virtual Width_tTAttLine::GetLineWidth() const
TList*TH1::GetListOfFunctions() const
virtual voidTH1::GetLowEdge(Double_t* edge) const
virtual Color_tTAttMarker::GetMarkerColor() const
virtual Size_tTAttMarker::GetMarkerSize() const
virtual Style_tTAttMarker::GetMarkerStyle() const
virtual Double_tTH1::GetMaximum(Double_t maxval = FLT_MAX) const
virtual Int_tTH1::GetMaximumBin() const
virtual Int_tTH1::GetMaximumBin(Int_t& locmax, Int_t& locmay, Int_t& locmaz) const
virtual Double_tTH1::GetMaximumStored() const
virtual Double_tTH1::GetMean(Int_t axis = 1) const
virtual Double_tTH1::GetMeanError(Int_t axis = 1) const
virtual Double_tTH1::GetMinimum(Double_t minval = -FLT_MAX) const
virtual Int_tTH1::GetMinimumBin() const
virtual Int_tTH1::GetMinimumBin(Int_t& locmix, Int_t& locmiy, Int_t& locmiz) const
virtual Double_tTH1::GetMinimumStored() const
virtual const char*TNamed::GetName() const
virtual Int_tTH1::GetNbinsX() const
virtual Int_tTH1::GetNbinsY() const
virtual Int_tTH1::GetNbinsZ() const
virtual Int_tTH1::GetNdivisions(Option_t* axis = "X") const
virtual Double_tTH1::GetNormFactor() const
virtual char*GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Option_t*TH1::GetOption() const
TVirtualHistPainter*TH1::GetPainter(Option_t* option = "")
virtual Int_tTH1::GetQuantiles(Int_t nprobSum, Double_t* q, const Double_t* probSum = 0)
virtual Double_tTH1::GetRandom() const
virtual Double_tTH1::GetRMS(Int_t axis = 1) const
virtual Double_tTH1::GetRMSError(Int_t axis = 1) const
Int_tTArray::GetSize() const
virtual Double_tTH1::GetSkewness(Int_t axis = 1) const
virtual voidGetStats(Double_t* stats) const
Stat_tTArrayD::GetSum() const
virtual Double_tTH1::GetSumOfWeights() const
virtual TArrayD*TH1::GetSumw2()
virtual const TArrayD*TH1::GetSumw2() const
virtual Int_tTH1::GetSumw2N() const
virtual Float_tTH1::GetTickLength(Option_t* axis = "X") const
virtual const char*TNamed::GetTitle() const
virtual Style_tTH1::GetTitleFont(Option_t* axis = "X") const
virtual Float_tTH1::GetTitleOffset(Option_t* axis = "X") const
virtual Float_tTH1::GetTitleSize(Option_t* axis = "X") const
virtual UInt_tTObject::GetUniqueID() const
TAxis*TH1::GetXaxis() const
TAxis*TH1::GetYaxis() const
virtual Double_tGetYmax() const
virtual Double_tGetYmin() const
TAxis*TH1::GetZaxis() const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
virtual ULong_tTNamed::Hash() const
virtual voidTObject::Info(const char* method, const char* msgfmt) const
virtual Bool_tTObject::InheritsFrom(const char* classname) const
virtual Bool_tTObject::InheritsFrom(const TClass* cl) const
virtual voidTObject::Inspect() constMENU
virtual Double_tTH1::Integral(Option_t* option = "") const
virtual Double_tTH1::Integral(Int_t binx1, Int_t binx2, Option_t* option = "") const
virtual Double_tTH1::IntegralAndError(Int_t binx1, Int_t binx2, Double_t& err, Option_t* option = "") const
virtual Double_tTH1::Interpolate(Double_t x)
virtual Double_tTH1::Interpolate(Double_t x, Double_t y)
virtual Double_tTH1::Interpolate(Double_t x, Double_t y, Double_t z)
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
Bool_tTH1::IsBinOverflow(Int_t bin) const
Bool_tTH1::IsBinUnderflow(Int_t bin) const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
Bool_tTObject::IsOnHeap() const
virtual Bool_tTNamed::IsSortable() const
virtual Bool_tTAttFill::IsTransparent() const
Bool_tTObject::IsZombie() const
virtual Double_tTH1::KolmogorovTest(const TH1* h2, Option_t* option = "") const
virtual voidLabelsDeflate(Option_t* axis = "X")
virtual voidLabelsInflate(Option_t* axis = "X")
virtual voidLabelsOption(Option_t* option = "h", Option_t* axis = "X")
virtual voidTNamed::ls(Option_t* option = "") const
voidTObject::MayNotUse(const char* method) const
virtual Long64_tMerge(TCollection* list)
virtual voidTAttLine::Modify()
virtual voidMultiply(const TH1* h1)
virtual voidMultiply(TF1* h1, Double_t c1 = 1)
virtual voidMultiply(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option = "")MENU
virtual Bool_tTObject::Notify()
voidTObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
static voidTObject::operator delete(void* ptr)
static voidTObject::operator delete(void* ptr, void* vp)
static voidTObject::operator delete[](void* ptr)
static voidTObject::operator delete[](void* ptr, void* vp)
void*TObject::operator new(size_t sz)
void*TObject::operator new(size_t sz, void* vp)
void*TObject::operator new[](size_t sz)
void*TObject::operator new[](size_t sz, void* vp)
TH1D&TH1D::operator=(const TH1D& h1)
Double_t&TArrayD::operator[](Int_t i)
Double_tTArrayD::operator[](Int_t i) const
virtual voidTH1::Paint(Option_t* option = "")
virtual voidTObject::Pop()
virtual voidTH1::Print(Option_t* option = "") const
TH1D*ProjectionX(const char* name = "_px", Option_t* option = "e") const
virtual voidPutStats(Double_t* stats)
virtual Int_tTObject::Read(const char* name)
static TArray*TArray::ReadArray(TBuffer& b, const TClass* clReq)
virtual TH1*Rebin(Int_t ngroup = 2, const char* newname = "", const Double_t* xbins = 0)
virtual voidRebinAxis(Double_t x, TAxis* axis)
virtual voidTH1::Rebuild(Option_t* option = "")
virtual voidTH1::RecursiveRemove(TObject* obj)
virtual voidReset(Option_t* option = "")
virtual voidTAttFill::ResetAttFill(Option_t* option = "")
virtual voidTAttLine::ResetAttLine(Option_t* option = "")
virtual voidTAttMarker::ResetAttMarker(Option_t* toption = "")
voidTObject::ResetBit(UInt_t f)
virtual voidTH1::ResetStats()
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual voidTAttFill::SaveFillAttributes(ostream& out, const char* name, Int_t coldef = 1, Int_t stydef = 1001)
virtual voidTAttLine::SaveLineAttributes(ostream& out, const char* name, Int_t coldef = 1, Int_t stydef = 1, Int_t widdef = 1)
virtual voidTAttMarker::SaveMarkerAttributes(ostream& out, const char* name, Int_t coldef = 1, Int_t stydef = 1, Int_t sizdef = 1)
virtual voidSavePrimitive(ostream& out, Option_t* option = "")
virtual voidScale(Double_t c1 = 1, Option_t* option = "")
virtual voidTArrayD::Set(Int_t n)
voidTArrayD::Set(Int_t n, const Double_t* array)
virtual voidTArrayD::SetAt(Double_t v, Int_t i)
virtual voidTH1::SetAxisColor(Color_t color = 1, Option_t* axis = "X")
virtual voidTH1::SetAxisRange(Double_t xmin, Double_t xmax, Option_t* axis = "X")
virtual voidTH1::SetBarOffset(Float_t offset = 0.25)
virtual voidTH1::SetBarWidth(Float_t width = 0.5)
virtual voidTH1D::SetBinContent(Int_t bin, Double_t content)
virtual voidTH1D::SetBinContent(Int_t bin, Int_t, Double_t content)
virtual voidTH1D::SetBinContent(Int_t bin, Int_t, Int_t, Double_t content)
virtual voidSetBinEntries(Int_t bin, Double_t w)
virtual voidTH1::SetBinError(Int_t bin, Double_t error)
virtual voidTH1::SetBinError(Int_t binx, Int_t biny, Double_t error)
virtual voidTH1::SetBinError(Int_t binx, Int_t biny, Int_t binz, Double_t error)
virtual voidSetBins(Int_t nx, const Double_t* xbins)
virtual voidSetBins(Int_t nbins, Double_t xmin, Double_t xmax)
virtual voidTH1D::SetBinsLength(Int_t n = -1)
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
virtual voidSetBuffer(Int_t buffersize, Option_t* option = "")
virtual voidTH1::SetCellContent(Int_t binx, Int_t biny, Double_t content)
virtual voidTH1::SetCellError(Int_t binx, Int_t biny, Double_t content)
virtual voidTH1::SetContent(const Double_t* content)
virtual voidTH1::SetContour(Int_t nlevels, const Double_t* levels = 0)
virtual voidTH1::SetContourLevel(Int_t level, Double_t value)
static voidTH1::SetDefaultBufferSize(Int_t buffersize = 1000)
static voidTH1::SetDefaultSumw2(Bool_t sumw2 = kTRUE)
virtual voidTH1::SetDirectory(TDirectory* dir)
virtual voidTObject::SetDrawOption(Option_t* option = "")MENU
static voidTObject::SetDtorOnly(void* obj)
virtual voidTH1::SetEntries(Double_t n)
virtual voidTH1::SetError(const Double_t* error)
virtual voidSetErrorOption(Option_t* option = "")MENU
virtual voidTAttFill::SetFillAttributes()MENU
virtual voidTAttFill::SetFillColor(Color_t fcolor)
virtual voidTAttFill::SetFillStyle(Style_t fstyle)
virtual voidTH1::SetLabelColor(Color_t color = 1, Option_t* axis = "X")
virtual voidTH1::SetLabelFont(Style_t font = 62, Option_t* axis = "X")
virtual voidTH1::SetLabelOffset(Float_t offset = 0.005, Option_t* axis = "X")
virtual voidTH1::SetLabelSize(Float_t size = 0.02, Option_t* axis = "X")
virtual voidTAttLine::SetLineAttributes()MENU
virtual voidTAttLine::SetLineColor(Color_t lcolor)
virtual voidTAttLine::SetLineStyle(Style_t lstyle)
virtual voidTAttLine::SetLineWidth(Width_t lwidth)
virtual voidTAttMarker::SetMarkerAttributes()MENU
virtual voidTAttMarker::SetMarkerColor(Color_t tcolor = 1)
virtual voidTAttMarker::SetMarkerSize(Size_t msize = 1)
virtual voidTAttMarker::SetMarkerStyle(Style_t mstyle = 1)
virtual voidTH1::SetMaximum(Double_t maximum = -1111)MENU
virtual voidTH1::SetMinimum(Double_t minimum = -1111)MENU
virtual voidTH1::SetName(const char* name)MENU
virtual voidTH1::SetNameTitle(const char* name, const char* title)
virtual voidTH1::SetNdivisions(Int_t n = 510, Option_t* axis = "X")
virtual voidTH1::SetNormFactor(Double_t factor = 1)
static voidTObject::SetObjectStat(Bool_t stat)
virtual voidTH1::SetOption(Option_t* option = " ")
virtual voidTH1::SetStats(Bool_t stats = kTRUE)MENU
virtual voidTH1::SetTickLength(Float_t length = 0.02, Option_t* axis = "X")
virtual voidTH1::SetTitle(const char* title)MENU
virtual voidTH1::SetTitleFont(Style_t font = 62, Option_t* axis = "X")
virtual voidTH1::SetTitleOffset(Float_t offset = 1, Option_t* axis = "X")
virtual voidTH1::SetTitleSize(Float_t size = 0.02, Option_t* axis = "X")
virtual voidTObject::SetUniqueID(UInt_t uid)
virtual voidTH1::SetXTitle(const char* title)
virtual voidTH1::SetYTitle(const char* title)
virtual voidTH1::SetZTitle(const char* title)
virtual TH1*TH1::ShowBackground(Int_t niter = 20, Option_t* option = "same")MENU
virtual voidShowMembers(TMemberInspector& insp)
virtual Int_tTH1::ShowPeaks(Double_t sigma = 2, Option_t* option = "", Double_t threshold = 0.05)MENU
virtual Int_tTNamed::Sizeof() const
virtual voidTH1::Smooth(Int_t ntimes = 1, Option_t* option = "")MENU
static voidTH1::SmoothArray(Int_t NN, Double_t* XX, Int_t ntimes = 1)
static voidTH1::StatOverflows(Bool_t flag = kTRUE)
virtual voidStreamer(TBuffer& b)
voidStreamerNVirtual(TBuffer& b)
virtual voidSumw2()
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
static TH1*TH1::TransformHisto(TVirtualFFT* fft, TH1* h_output, Option_t* option)
virtual voidTH1::UseCurrentStyle()
virtual voidTObject::Warning(const char* method, const char* msgfmt) const
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_tTObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const
static voidTArray::WriteArray(TBuffer& b, const TArray* a)
protected:
Bool_tTArray::BoundsOk(const char* where, Int_t at) const
virtual Int_tBufferFill(Double_t, Double_t)
virtual Int_tBufferFill(Double_t x, Double_t y, Double_t w)
static boolTH1::CheckAxisLimits(const TAxis* a1, const TAxis* a2)
static boolTH1::CheckBinLimits(const TAxis* a1, const TAxis* a2)
static boolTH1::CheckConsistency(const TH1* h1, const TH1* h2)
static boolTH1::CheckConsistentSubAxes(const TAxis* a1, Int_t firstBin1, Int_t lastBin1, const TAxis* a2, Int_t firstBin2 = 0, Int_t lastBin2 = 0)
static boolTH1::CheckEqualAxes(const TAxis* a1, const TAxis* a2)
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const
virtual Double_tTH1::DoIntegral(Int_t ix1, Int_t ix2, Int_t iy1, Int_t iy2, Int_t iz1, Int_t iz2, Double_t& err, Option_t* opt, Bool_t doerr = kFALSE) const
Int_tFill(const Double_t* v)
virtual Bool_tTH1::FindNewAxisLimits(const TAxis* axis, const Double_t point, Double_t& newMin, Double_t& newMax)
voidTObject::MakeZombie()
Bool_tTArray::OutOfBoundsError(const char* where, Int_t i) const
static Bool_tTH1::RecomputeAxisLimits(TAxis& destAxis, const TAxis& anAxis)
static Bool_tTH1::SameLimitsAndNBins(const TAxis& axis1, const TAxis& axis2)
virtual voidTH1::SavePrimitiveHelp(ostream& out, const char* hname, Option_t* option = "")
voidSetBins(const Int_t* nbins, const Double_t* range)
private:
virtual Int_tFill(Double_t)
virtual voidFillN(Int_t, const Double_t*, const Double_t*, Int_t)
Double_t*GetB()
Double_t*GetB2()
Double_t*GetW()
Double_t*GetW2()
virtual voidSetBins(Int_t, const Double_t*, Int_t, const Double_t*)
virtual voidSetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t)
virtual voidSetBins(Int_t, const Double_t*, Int_t, const Double_t*, Int_t, const Double_t*)
virtual voidSetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t, Int_t, Double_t, Double_t)

Data Members

public:
Double_t*TArrayD::fArray[fN] Array of fN doubles
Int_tTArray::fNNumber of array elements
protected:
Short_tTH1::fBarOffset(1000*offset) for bar charts or legos
Short_tTH1::fBarWidth(1000*width) for bar charts or legos
TArrayDfBinEntriesnumber of entries per bin
TArrayDfBinSumw2Array of sum of squares of weights per bin
Double_t*TH1::fBuffer[fBufferSize] entry buffer
Int_tTH1::fBufferSizefBuffer size
TArrayDTH1::fContourArray to display contour levels
Int_tTH1::fDimension!Histogram dimension (1, 2 or 3 dim)
TDirectory*TH1::fDirectory!Pointer to directory holding this histogram
Double_tTH1::fEntriesNumber of entries
EErrorTypefErrorModeOption to compute errors
Color_tTAttFill::fFillColorfill area color
Style_tTAttFill::fFillStylefill area style
TList*TH1::fFunctions->Pointer to list of functions (fits and user)
Double_t*TH1::fIntegral!Integral of bins used by GetRandom
Color_tTAttLine::fLineColorline color
Style_tTAttLine::fLineStyleline style
Width_tTAttLine::fLineWidthline width
Color_tTAttMarker::fMarkerColorMarker color index
Size_tTAttMarker::fMarkerSizeMarker size
Style_tTAttMarker::fMarkerStyleMarker style
Double_tTH1::fMaximumMaximum value for plotting
Double_tTH1::fMinimumMinimum value for plotting
TStringTNamed::fNameobject identifier
Int_tTH1::fNcellsnumber of bins(1D), cells (2D) +U/Overflows
Double_tTH1::fNormFactorNormalization factor
TStringTH1::fOptionhistogram options
TVirtualHistPainter*TH1::fPainter!pointer to histogram painter
Bool_tfScaling!True when TProfile::Scale is called
TArrayDTH1::fSumw2Array of sum of squares of weights
TStringTNamed::fTitleobject title
Double_tTH1::fTsumwTotal Sum of weights
Double_tTH1::fTsumw2Total Sum of squares of weights
Double_tTH1::fTsumwxTotal Sum of weight*X
Double_tTH1::fTsumwx2Total Sum of weight*X*X
Double_tfTsumwyTotal Sum of weight*Y
Double_tfTsumwy2Total Sum of weight*Y*Y
TAxisTH1::fXaxisX axis descriptor
TAxisTH1::fYaxisY axis descriptor
Double_tfYmaxUpper limit in Y (if set)
Double_tfYminLower limit in Y (if set)
TAxisTH1::fZaxisZ axis descriptor
static Bool_tTH1::fgAddDirectory!flag to add histograms to the directory
static Bool_tfgApproximatebin error approximation option
static Int_tTH1::fgBufferSize!default buffer size for automatic histograms
static Bool_tTH1::fgDefaultSumw2!flag to call TH1::Sumw2 automatically at histogram creation time
static Bool_tTH1::fgStatOverflows!flag to use under/overflows in statistics

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

TProfile()
Default constructor for Profile histograms*-*-*-
*-*        ==========================================
~TProfile()
Default destructor for Profile histograms*-*-*-
*-*        =========================================
TProfile(const char* name, const char* title, Int_t nbinsx, Double_t xlow, Double_t xup, Option_t* option = "")
Normal Constructor for Profile histograms*-*-*-*-
*-*        ==========================================

  The first five parameters are similar to TH1D::TH1D.
  All values of y are accepted at filling time.
  To fill a profile histogram, one must use TProfile::Fill function.

  Note that when filling the profile histogram the function Fill
  checks if the variable y is betyween fYmin and fYmax.
  If a minimum or maximum value is set for the Y scale before filling,
  then all values below ymin or above ymax will be discarded.
  Setting the minimum or maximum value for the Y scale before filling
  has the same effect as calling the special TProfile constructor below
  where ymin and ymax are specified.

  H(J) is printed as the channel contents. The errors displayed are s(J) if CHOPT='S'
  (spread option), or e(J) if CHOPT=' ' (error on mean).

        See TProfile::BuildOptions for explanation of parameters

 see also comments in the TH1 base class constructors
TProfile(const char* name, const char* title, Int_t nbinsx, const Float_t* xbins, Option_t* option = "")
-*Constructor for Profile histograms with variable bin size
*-*        =========================================================

        See TProfile::BuildOptions for more explanations on errors

 see also comments in the TH1 base class constructors
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Option_t* option = "")
-*Constructor for Profile histograms with variable bin size
*-*        =========================================================

        See TProfile::BuildOptions for more explanations on errors

 see also comments in the TH1 base class constructors
TProfile(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins, Double_t ylow, Double_t yup, Option_t* option = "")
-*Constructor for Profile histograms with variable bin size
*-*        =========================================================

        See TProfile::BuildOptions for more explanations on errors

 see also comments in the TH1 base class constructors
TProfile(const char* name, const char* title, Int_t nbinsx, Double_t xlow, Double_t xup, Double_t ylow, Double_t yup, Option_t* option = "")
Constructor for Profile histograms with range in y
*-*        ==================================================
  The first five parameters are similar to TH1D::TH1D.
  Only the values of Y between ylow and yup will be considered at filling time.
  ylow and yup will also be the maximum and minimum values
  on the y scale when drawing the profile.

        See TProfile::BuildOptions for more explanations on errors

 see also comments in the TH1 base class constructors
void BuildOptions(Double_t ymin, Double_t ymax, Option_t* option)
Set Profile histogram structure and options*-*-
*-*          ===========================================

    If a bin has N data points all with the same value Y (especially
    possible when dealing with integers), the spread in Y for that bin
    is zero, and the uncertainty assigned is also zero, and the bin is
    ignored in making subsequent fits. If SQRT(Y) was the correct error
    in the case above, then SQRT(Y)/SQRT(N) would be the correct error here.
    In fact, any bin with non-zero number of entries N but with zero spread
    should have an uncertainty SQRT(Y)/SQRT(N).

    Now, is SQRT(Y)/SQRT(N) really the correct uncertainty?
    that it is only in the case where the Y variable is some sort
    of counting statistics, following a Poisson distribution. This should
    probably be set as the default case. However, Y can be any variable
    from an original NTUPLE, not necessarily distributed "Poissonly".
    The computation of errors is based on the parameter option:
    option:
     ' '  (Default) Errors are Spread/SQRT(N) for Spread.ne.0. ,
                      "     "  SQRT(Y)/SQRT(N) for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0
     's'            Errors are Spread  for Spread.ne.0. ,
                      "     "  SQRT(Y)  for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0
     'i'            Errors are Spread/SQRT(N) for Spread.ne.0. ,
                      "     "  1./SQRT(12.*N) for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0

    The third case above corresponds to Integer Y values for which the
    uncertainty is +-0.5, with the assumption that the probability that Y
    takes any value between Y-0.5 and Y+0.5 is uniform (the same argument
    goes for Y uniformly distributed between Y and Y+1); this would be
    useful if Y is an ADC measurement, for example.
     Other, fancier options
    would be possible, at the cost of adding one more parameter to the PROFILE
    command. For example, if all Y variables are distributed according to some
    known Gaussian of standard deviation Sigma (which can be different for each measurement),
    and the profile has been filled  with a weight equal to 1/Sigma**2,
    then one cam use the following option:

     'G'            Errors are 1./SQRT(Sum(1/sigma**2))
    For example, this would be useful when all Y's are experimental quantities
    measured with different precision Sigma_Y.


TProfile(const TProfile& profile)
 Copy constructor.
void Add(TF1* h1, Double_t c1 = 1, Option_t* option = "")
 Performs the operation: this = this + c1*f1
void Add(const TH1* h1, Double_t c1 = 1)
 Performs the operation: this = this + c1*h1
void Add(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1)
-*-*Replace contents of this profile by the addition of h1 and h2
*-*      =============================================================

   this = c1*h1 + c2*h2

   c1 and c2 are considered as weights applied to the two summed profiles.
   The operation acts therefore like merging the two profiles with a weight c1 and c2

void Approximate(Bool_t approx = kTRUE)
     static function
 set the fgApproximate flag. When the flag is true, the function GetBinError
 will approximate the bin error with the average profile error on all bins
 in the following situation only
  - the number of bins in the profile is less than 1002
  - the bin number of entries is small ( <5)
  - the estimated bin error is extremely small compared to the bin content
  (see TProfile::GetBinError)
Int_t BufferEmpty(Int_t action = 0)
 Fill histogram with all entries in the buffer.
 action = -1 histogram is reset and refilled from the buffer (called by THistPainter::Paint)
 action =  0 histogram is filled from the buffer
 action =  1 histogram is filled and buffer is deleted
             The buffer is automatically deleted when the number of entries
             in the buffer is greater than the number of entries in the histogram
Int_t BufferFill(Double_t x, Double_t y, Double_t w)
 accumulate arguments in buffer. When buffer is full, empty the buffer
 fBuffer[0] = number of entries in buffer
 fBuffer[1] = w of first entry
 fBuffer[2] = x of first entry
 fBuffer[3] = y of first entry
void Copy(TObject& hnew) const
-*-*-*Copy a Profile histogram to a new profile histogram
*-*            ===================================================
void Divide(TF1* h1, Double_t c1 = 1)
 Performs the operation: this = this/(c1*f1)
void Divide(const TH1* h1)
Divide this profile by h1*-*-
*-*                  =========================

   this = this/h1
 This function accepts to divide a TProfile by a histogram

void Divide(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option = "")
-*-*Replace contents of this profile by the division of h1 by h2
*-*      ============================================================

   this = c1*h1/(c2*h2)

TH1 * DrawCopy(Option_t* option = "") const
Draw a copy of this profile histogram*-*-*-*-
*-*            =====================================
Int_t Fill(Double_t x, Double_t y)
-*-*-*Fill a Profile histogram (no weights)
*-*                  =====================================
Int_t Fill(const char* namex, Double_t y)
 Fill a Profile histogram (no weights)

Int_t Fill(Double_t x, Double_t y, Double_t w)
-*-*-*Fill a Profile histogram with weights
*-*                  =====================================
Int_t Fill(const char* namex, Double_t y, Double_t w)
 Fill a Profile histogram with weights

void FillN(Int_t ntimes, const Double_t* x, const Double_t* y, const Double_t* w, Int_t stride = 1)
-*-*-*Fill a Profile histogram with weights
*-*                  =====================================
Double_t GetBinContent(Int_t bin) const
Return bin content of a Profile histogram*-*-*-
*-*          =========================================
Double_t GetBinEntries(Int_t bin) const
Return bin entries of a Profile histogram*-*-*-
*-*          =========================================
Double_t GetBinEffectiveEntries(Int_t bin) const
            Return bin effective entries for a weighted filled Profile histogram.
            In case of an unweighted profile, it is equivalent to the number of entries per bin
            The effective entries is defined as the square of the sum of the weights divided by the
            sum of the weights square.
            TProfile::Sumw2() must be called before filling the profile with weights.
            Only by calling this method the  sum of the square of the weights per bin is stored.

*-*          =========================================
Double_t GetBinError(Int_t bin) const
 *-*-*-*-*-*-*Return bin error of a Profile histogram*-*-*-*-*-*-*-*-*-*
 *-*          =======================================

 Computing errors: A moving field

 The computation of errors for a TProfile has evolved with the versions
 of ROOT. The difficulty is in computing errors for bins with low statistics.
 - prior to version 3.00, we had no special treatment of low statistic bins.
   As a result, these bins had huge errors. The reason is that the
   expression eprim2 is very close to 0 (rounding problems) or 0.
 - in version 3.00 (18 Dec 2000), the algorithm is protected for values of
   eprim2 very small and the bin errors set to the average bin errors, following
   recommendations from a group of users.
 - in version 3.01 (19 Apr 2001), it is realized that the algorithm above
   should be applied only to low statistic bins.
 - in version 3.02 (26 Sep 2001), the same group of users recommend instead
   to take two times the average error on all bins for these low
   statistics bins giving a very small value for eprim2.
 - in version 3.04 (Nov 2002), the algorithm is modified/protected for the case
   when a TProfile is projected (ProjectionX). The previous algorithm
   generated a N^2 problem when projecting a TProfile with a large number of
   bins (eg 100000).
 - in version 3.05/06, a new static function TProfile::Approximate
   is introduced to enable or disable (default) the approximation.

 Ideas for improvements of this algorithm are welcome. No suggestions
 received since our call for advice to roottalk in Jul 2002.
 see for instance: http://root.cern.ch/root/roottalk/roottalk02/2916.html
Option_t * GetErrorOption() const
-*Return option to compute profile errors
*-*                =======================================
char* GetObjectInfo(Int_t px, Int_t py) const
   Redefines TObject::GetObjectInfo.
   Displays the profile info (bin number, contents, eroor, entries per bin
   corresponding to cursor position px,py

void GetStats(Double_t* stats) const
 fill the array stats from the contents of this profile
 The array stats must be correctly dimensionned in the calling program.
 stats[0] = sumw
 stats[1] = sumw2
 stats[2] = sumwx
 stats[3] = sumwx2
 stats[4] = sumwy
 stats[5] = sumwy2

 If no axis-subrange is specified (via TAxis::SetRange), the array stats
 is simply a copy of the statistics quantities computed at filling time.
 If a sub-range is specified, the function recomputes these quantities
 from the bin contents in the current axis range.
void LabelsDeflate(Option_t* axis = "X")
 Reduce the number of bins for this axis to the number of bins having a label.
void LabelsInflate(Option_t* axis = "X")
 Double the number of bins for axis.
 Refill histogram
 This function is called by TAxis::FindBin(const char *label)
void LabelsOption(Option_t* option = "h", Option_t* axis = "X")
  Set option(s) to draw axis with labels
  option = "a" sort by alphabetic order
         = ">" sort by decreasing values
         = "<" sort by increasing values
         = "h" draw labels horizonthal
         = "v" draw labels vertical
         = "u" draw labels up (end of label right adjusted)
         = "d" draw labels down (start of label left adjusted)
Long64_t Merge(TCollection* list)
Merge all histograms in the collection in this histogram.
This function computes the min/max for the x axis,
compute a new number of bins, if necessary,
add bin contents, errors and statistics.
If overflows are present and limits are different the function will fail.
The function returns the total number of entries in the result histogram
if the merge is successfull, -1 otherwise.

IMPORTANT remark. The axis x may have different number
of bins and different limits, BUT the largest bin width must be
a multiple of the smallest bin width and the upper limit must also
be a multiple of the bin width.
void Multiply(TF1* h1, Double_t c1 = 1)
 Performs the operation: this = this*c1*f1
void Multiply(const TH1* h1)
Multiply this profile by h1*-*-
*-*                  =============================

   this = this*h1

void Multiply(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option = "")
-*-*-*Replace contents of this profile by multiplication of h1 by h2
*-*      ================================================================

   this = (c1*h1)*(c2*h2)

TH1D * ProjectionX(const char* name = "_px", Option_t* option = "e") const
Project this profile into a 1-D histogram along X*-*-
*-*      =================================================

   The projection is always of the type TH1D.

   if option "E" is specified the errors of the projected histogram are computed and set
      to be equal to the errors of the profile.
      Option "E" is defined as the default one in the header file.
   if option "" is specified the histogram errors are simply the sqrt of its content
   if option "B" is specified, the content of bin of the returned histogram
      will be equal to the GetBinEntries(bin) of the profile,
      otherwise (default) it will be equal to GetBinContent(bin)
   if option "C=E" the bin contents of the projection are set to the
       bin errors of the profile
   if option "W" is specified the bin content of the projected histogram  is set to the
       product of the bin content of the profile and the entries.
       With this option the returned histogram will be equivalent to the one obtained by
       filling directly a TH1D using the 2-nd value as a weight.
       This makes sense only for profile filled with weights =1. If not, the error of the
        projected histogram obtained with this option will not be correct.
void PutStats(Double_t* stats)
 Replace current statistics with the values in array stats
TH1 * Rebin(Int_t ngroup = 2, const char* newname = "", const Double_t* xbins = 0)
Rebin this profile grouping ngroup bins together*-*-*-*-
*-*      ================================================
  -case 1  xbins=0
   if newname is not blank a new temporary profile hnew is created.
   else the current profile is modified (default)
   The parameter ngroup indicates how many bins of this have to me merged
   into one bin of hnew
   If the original profile has errors stored (via Sumw2), the resulting
   profile has new errors correctly calculated.

   examples: if hp is an existing TProfile histogram with 100 bins
     hp->Rebin();  //merges two bins in one in hp: previous contents of hp are lost
     hp->Rebin(5); //merges five bins in one in hp
     TProfile *hnew = hp->Rebin(5,"hnew"); // creates a new profile hnew
                                       //merging 5 bins of hp in one bin

   NOTE:  If ngroup is not an exact divider of the number of bins,
          the top limit of the rebinned profile is changed
          to the upper edge of the bin=newbins*ngroup and the corresponding
          bins are added to the overflow bin.
          Statistics will be recomputed from the new bin contents.

  -case 2  xbins!=0
   a new profile is created (you should specify newname).
   The parameter ngroup is the number of variable size bins in the created profile
   The array xbins must contain ngroup+1 elements that represent the low-edge
   of the bins.
   The data of the old bins are added to the new bin which contains the bin center
   of the old bins. It is possible that information from the old binning are attached
   to the under-/overflow bins of the new binning.

   examples: if hp is an existing TProfile with 100 bins
     Double_t xbins[25] = {...} array of low-edges (xbins[25] is the upper edge of last bin
     hp->Rebin(24,"hpnew",xbins);  //creates a new variable bin size profile hpnew
void RebinAxis(Double_t x, TAxis* axis)
 Profile histogram is resized along x axis such that x is in the axis range.
 The new axis limits are recomputed by doubling iteratively
 the current axis range until the specified value x is within the limits.
 The algorithm makes a copy of the histogram, then loops on all bins
 of the old histogram to fill the rebinned histogram.
 Takes into account errors (Sumw2) if any.
 The bit kCanRebin must be set before invoking this function.
  Ex:  h->SetBit(TH1::kCanRebin);
void Reset(Option_t* option = "")
-*Reset contents of a Profile histogram
*-*                =====================================
void SavePrimitive(ostream& out, Option_t* option = "")
 Save primitive as a C++ statement(s) on output stream out
void Scale(Double_t c1 = 1, Option_t* option = "")
 *-*-*-*-*Multiply this profile by a constant c1*-*-*-*-*-*-*-*-*
 *-*      ======================================

   this = c1*this

 This function uses the services of TProfile::Add

void SetBinEntries(Int_t bin, Double_t w)
Set the number of entries in bin*-*-*-
*-*              ================================
void SetBins(Int_t nbins, Double_t xmin, Double_t xmax)
Redefine  x axis parameters*-*-*-
*-*              ===========================
void SetBins(Int_t nx, const Double_t* xbins)
Redefine  x axis parameters*-*-*-
*-*              ===========================
void SetBuffer(Int_t buffersize, Option_t* option = "")
 set the buffer size in units of 8 bytes (double)
void SetErrorOption(Option_t* option = "")
-*Set option to compute profile errors
*-*                =====================================

    The computation of errors is based on the parameter option:
    option:
     ' '  (Default) Errors are Spread/SQRT(N) for Spread.ne.0. ,
                      "     "  SQRT(Y)/SQRT(N) for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0
     's'            Errors are Spread  for Spread.ne.0. ,
                      "     "  SQRT(Y)  for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0
     'i'            Errors are Spread/SQRT(N) for Spread.ne.0. ,
                      "     "  1./SQRT(12.*N) for Spread.eq.0,N.gt.0 ,
                      "     "  0.  for N.eq.0
     'g'            Errors are 1./SQRT(W) for Spread.ne.0. ,
                      "     "  0.  for N.eq.0
                    W is the sum of weights of the profile.
                    This option is for measurements y +/ dy and  the profile is filled with
                    weights w = 1/dy**2

   See TProfile::BuildOptions for explanation of all options
void Streamer(TBuffer& b)
 Stream an object of class TProfile.
void Sumw2()
 Create structure to store sum of squares of weights per bin  *-*-*-*-*-*-*-*
   This is needed to compute  the correct statistical quantities
    of a profile filled with weights


  This function is automatically called when the histogram is created
  if the static function TH1::SetDefaultSumw2 has been called before.
Int_t BufferFill(Double_t , Double_t )
{return -2;}
void SetBins(const Int_t* nbins, const Double_t* range)
 helper methods for the Merge unification in TProfileHelper
{ SetBins(nbins[0], range[0], range[1]); }
Int_t Fill(const Double_t* v)
{ return Fill(v[0], v[1], v[2]); }
Int_t Fill(Double_t )
{ MayNotUse("Fill(Double_t)"); return -1;}
void FillN(Int_t , const Double_t* , const Double_t* , Int_t )
{ MayNotUse("FillN(Int_t, Double_t*, Double_t*, Int_t)"); }
Double_t * GetB()
{return &fBinEntries.fArray[0];}
Double_t * GetB2()
{return (fBinSumw2.fN ? &fBinSumw2.fArray[0] : 0 ); }
Double_t * GetW()
{return &fArray[0];}
Double_t * GetW2()
{return &fSumw2.fArray[0];}
void SetBins(Int_t , Double_t , Double_t , Int_t , Double_t , Double_t )
{ MayNotUse("SetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t"); }
void SetBins(Int_t , const Double_t* , Int_t , const Double_t* )
{ MayNotUse("SetBins(Int_t, const Double_t*, Int_t, const Double_t*"); }
void SetBins(Int_t , Double_t , Double_t , Int_t , Double_t , Double_t , Int_t , Double_t , Double_t )
{ MayNotUse("SetBins(Int_t, Double_t, Double_t, Int_t, Double_t, Double_t, Int_t, Double_t, Double_t"); }
void SetBins(Int_t , const Double_t* , Int_t , const Double_t* , Int_t , const Double_t* )
{ MayNotUse("SetBins(Int_t, const Double_t*, Int_t, const Double_t*, Int_t, const Double_t*"); }
Double_t GetBinContent(Int_t bin) const
Double_t GetBinContent(Int_t bin, Int_t ) const
{return GetBinContent(bin);}
Double_t GetBinError(Int_t bin) const
Double_t GetBinError(Int_t bin, Int_t ) const
{return GetBinError(bin);}
TArrayD * GetBinSumw2()
{return &fBinSumw2;}
const TArrayD * GetBinSumw2() const
{return &fBinSumw2;}
Double_t GetYmin() const
{return fYmin;}
Double_t GetYmax() const
{return fYmax;}