TH1


class description - source file - inheritance tree

class TH1 : public TNamed, public TAttLine, public TAttFill, public TAttMarker

    private:
Int_t AxisChoice(Option_t* axis) const void Build() Int_t FitOptionsMake(Option_t* option) protected:
virtual Int_t BufferFill(Axis_t x, Stat_t w) virtual void Copy(TObject& hnew) const public:
TH1 TH1() TH1 TH1(const char* name, const char* title, Int_t nbinsx, Axis_t xlow, Axis_t xup) TH1 TH1(const char* name, const char* title, Int_t nbinsx, const Float_t* xbins) TH1 TH1(const char* name, const char* title, Int_t nbinsx, const Double_t* xbins) TH1 TH1(const TH1&) virtual void ~TH1() virtual void Add(TF1* h1, Double_t c1 = 1) virtual void Add(const TH1* h1, Double_t c1 = 1) virtual void Add(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1) virtual void AddBinContent(Int_t bin) virtual void AddBinContent(Int_t bin, Stat_t w) static void AddDirectory(Bool_t add = kTRUE) static Bool_t AddDirectoryStatus() virtual void Browse(TBrowser* b) virtual Int_t BufferEmpty(Bool_t deleteBuffer = kFALSE) static TClass* Class() virtual Double_t ComputeIntegral() virtual Int_t DistancetoPrimitive(Int_t px, Int_t py) virtual void Divide(TF1* f1, Double_t c1 = 1) virtual void Divide(const TH1* h1) virtual void Divide(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option) virtual void Draw(Option_t* option) virtual TH1* DrawCopy(Option_t* option) const virtual TH1* DrawNormalized(Option_t* option, Double_t norm = 1) const virtual void DrawPanel() virtual void Eval(TF1* f1, Option_t* option) virtual void ExecuteEvent(Int_t event, Int_t px, Int_t py) virtual Int_t Fill(Axis_t x) virtual Int_t Fill(Axis_t x, Stat_t w) virtual Int_t Fill(const char* name, Stat_t w) virtual void FillN(Int_t ntimes, const Axis_t* x, const Double_t* w, Int_t stride = 1) virtual void FillN(Int_t, const Axis_t*, const Axis_t*, const Double_t*, Int_t) virtual void FillRandom(const char* fname, Int_t ntimes = 5000) virtual void FillRandom(TH1* h, Int_t ntimes = 5000) virtual Int_t FindBin(Axis_t x, Axis_t y = 0, Axis_t z = 0) virtual TObject* FindObject(const char* name) const virtual TObject* FindObject(const TObject* obj) const virtual Int_t Fit(const char* formula, Option_t* option, Option_t* goption, Axis_t xmin = 0, Axis_t xmax = 0) virtual Int_t Fit(TF1* f1, Option_t* option, Option_t* goption, Axis_t xmin = 0, Axis_t xmax = 0) virtual void FitPanel() TH1* GetAsymmetry(TH1* h2, Double_t c2 = 1, Double_t dc2 = 0) virtual Color_t GetAxisColor(Option_t* axis = "X") const virtual Float_t GetBarOffset() const virtual Float_t GetBarWidth() const virtual Int_t GetBin(Int_t binx, Int_t biny = 0, Int_t binz = 0) const virtual Axis_t GetBinCenter(Int_t bin) const virtual Stat_t GetBinContent(Int_t bin) const virtual Stat_t GetBinContent(Int_t binx, Int_t biny) const virtual Stat_t GetBinContent(Int_t binx, Int_t biny, Int_t binz) const virtual Stat_t GetBinError(Int_t bin) const virtual Stat_t GetBinError(Int_t binx, Int_t biny) const virtual Stat_t GetBinError(Int_t binx, Int_t biny, Int_t binz) const virtual Axis_t GetBinLowEdge(Int_t bin) const virtual Axis_t GetBinWidth(Int_t bin) const const Double_t* GetBuffer() const Int_t GetBufferLength() const Int_t GetBufferSize() const virtual Stat_t GetCellContent(Int_t binx, Int_t biny) const virtual Stat_t GetCellError(Int_t binx, Int_t biny) const virtual void GetCenter(Axis_t* center) const virtual Int_t GetContour(Double_t* levels = 0) virtual Double_t GetContourLevel(Int_t level) const static Int_t GetDefaultBufferSize() virtual Int_t GetDimension() const TDirectory* GetDirectory() const virtual Stat_t GetEntries() const virtual TF1* GetFunction(const char* name) const virtual Double_t* GetIntegral() virtual Color_t GetLabelColor(Option_t* axis = "X") const virtual Style_t GetLabelFont(Option_t* axis = "X") const virtual Float_t GetLabelOffset(Option_t* axis = "X") const virtual Float_t GetLabelSize(Option_t* axis = "X") const TList* GetListOfFunctions() const virtual void GetLowEdge(Axis_t* edge) const virtual Double_t GetMaximum() const virtual Int_t GetMaximumBin() const virtual Int_t GetMaximumBin(Int_t& locmax, Int_t& locmay, Int_t& locmaz) const virtual Double_t GetMaximumStored() const virtual Stat_t GetMean(Int_t axis = 1) const virtual Double_t GetMinimum() const virtual Int_t GetMinimumBin() const virtual Int_t GetMinimumBin(Int_t& locmix, Int_t& locmiy, Int_t& locmiz) const virtual Double_t GetMinimumStored() const virtual Int_t GetNbinsX() const virtual Int_t GetNbinsY() const virtual Int_t GetNbinsZ() const virtual Int_t GetNdivisions(Option_t* axis = "X") const virtual Double_t GetNormFactor() const virtual char* GetObjectInfo(Int_t px, Int_t py) const virtual Option_t* GetOption() const TVirtualHistPainter* GetPainter() virtual Int_t GetQuantiles(Int_t nprobSum, Double_t* q, const Double_t* probSum = 0) virtual Axis_t GetRandom() virtual Stat_t GetRMS(Int_t axis = 1) const virtual void GetStats(Stat_t* stats) const virtual Stat_t GetSumOfWeights() const virtual Int_t GetSumw2N() const virtual Float_t GetTickLength(Option_t* axis = "X") const virtual Float_t GetTitleOffset(Option_t* axis = "X") const virtual Float_t GetTitleSize(Option_t* axis = "X") const TAxis* GetXaxis() const TAxis* GetYaxis() const TAxis* GetZaxis() const virtual Stat_t Integral(Option_t* option) const virtual Stat_t Integral(Int_t binx1, Int_t binx2, Option_t* option) const virtual Stat_t Integral(Int_t, Int_t, Int_t, Int_t, Option_t*) const virtual Stat_t Integral(Int_t, Int_t, Int_t, Int_t, Int_t, Int_t, Option_t*) const virtual TClass* IsA() const virtual Double_t KolmogorovTest(TH1* h2, Option_t* option) const virtual void LabelsDeflate(Option_t* axis = "X") virtual void LabelsInflate(Option_t* axis = "X") virtual void LabelsOption(Option_t* option = "h", Option_t* axis = "X") virtual Int_t Merge(TCollection* list) virtual void Multiply(TF1* h1, Double_t c1 = 1) virtual void Multiply(const TH1* h1) virtual void Multiply(const TH1* h1, const TH1* h2, Double_t c1 = 1, Double_t c2 = 1, Option_t* option) virtual void Paint(Option_t* option) virtual void Print(Option_t* option) const virtual void PutStats(Stat_t* stats) virtual TH1* Rebin(Int_t ngroup = 2, const char* newname) virtual void RebinAxis(Axis_t x, Option_t* axis = "X") virtual void Rebuild(Option_t* option) virtual void Reset(Option_t* option) virtual void SavePrimitive(ofstream& out, Option_t* option) virtual void Scale(Double_t c1 = 1) virtual void SetAxisColor(Color_t color = 1, Option_t* axis = "X") virtual void SetAxisRange(Axis_t xmin, Axis_t xmax, Option_t* axis = "X") virtual void SetBarOffset(Float_t offset = 0.25) virtual void SetBarWidth(Float_t width = 0.5) virtual void SetBinContent(Int_t bin, Stat_t content) virtual void SetBinContent(Int_t binx, Int_t biny, Stat_t content) virtual void SetBinContent(Int_t binx, Int_t biny, Int_t binz, Stat_t content) virtual void SetBinError(Int_t bin, Stat_t error) virtual void SetBinError(Int_t binx, Int_t biny, Stat_t error) virtual void SetBinError(Int_t binx, Int_t biny, Int_t binz, Stat_t error) virtual void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax) virtual void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax, Int_t ny, Axis_t ymin, Axis_t ymax) virtual void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax, Int_t ny, Axis_t ymin, Axis_t ymax, Int_t nz, Axis_t zmin, Axis_t zmax) virtual void SetBinsLength(Int_t = -1) virtual void SetBuffer(Int_t buffersize, Option_t* option) virtual void SetCellContent(Int_t binx, Int_t biny, Stat_t content) virtual void SetCellError(Int_t binx, Int_t biny, Stat_t content) virtual void SetContent(const Stat_t* content) virtual void SetContour(Int_t nlevels, const Double_t* levels = 0) virtual void SetContourLevel(Int_t level, Double_t value) static void SetDefaultBufferSize(Int_t buffersize = 1000) virtual void SetDirectory(TDirectory* dir) virtual void SetEntries(Stat_t n) virtual void SetError(const Stat_t* error) virtual void SetLabelColor(Color_t color = 1, Option_t* axis = "X") virtual void SetLabelFont(Style_t font = 62, Option_t* axis = "X") virtual void SetLabelOffset(Float_t offset = 0.005, Option_t* axis = "X") virtual void SetLabelSize(Float_t size = 0.02, Option_t* axis = "X") virtual void SetMaximum(Double_t maximum = -1111) virtual void SetMinimum(Double_t minimum = -1111) virtual void SetName(const char* name) virtual void SetNameTitle(const char* name, const char* title) virtual void SetNdivisions(Int_t n = 510, Option_t* axis = "X") virtual void SetNormFactor(Double_t factor = 1) virtual void SetOption(Option_t* option = " ") virtual void SetStats(Bool_t stats = kTRUE) virtual void SetTickLength(Float_t length = 0.02, Option_t* axis = "X") virtual void SetTitleOffset(Float_t offset = 1, Option_t* axis = "X") virtual void SetTitleSize(Float_t size = 0.02, Option_t* axis = "X") virtual void SetXTitle(const char* title) virtual void SetYTitle(const char* title) virtual void SetZTitle(const char* title) virtual void ShowMembers(TMemberInspector& insp, char* parent) virtual void Smooth(Int_t ntimes = 1) static void SmoothArray(Int_t NN, Double_t* XX, Int_t ntimes = 1) static Double_t SmoothMedian(Int_t n, Double_t* a) virtual void Streamer(TBuffer& b) void StreamerNVirtual(TBuffer& b) virtual void Sumw2() virtual void UseCurrentStyle()

Data Members


    protected:
Int_t fNcells number of bins(1D), cells (2D) +U/Overflows TAxis fXaxis X axis descriptor TAxis fYaxis Y axis descriptor TAxis fZaxis Z axis descriptor Short_t fBarOffset (1000*offset) for bar charts or legos Short_t fBarWidth (1000*width) for bar charts or legos Stat_t fEntries Number of entries Stat_t fTsumw Total Sum of weights Stat_t fTsumw2 Total Sum of squares of weights Stat_t fTsumwx Total Sum of weight*X Stat_t fTsumwx2 Total Sum of weight*X*X Double_t fMaximum Maximum value for plotting Double_t fMinimum Minimum value for plotting Double_t fNormFactor Normalization factor TArrayD fContour Array to display contour levels TArrayD fSumw2 Array of sum of squares of weights TString fOption histogram options TList* fFunctions ->Pointer to list of functions (fits and user) Int_t fBufferSize fBuffer size Double_t* fBuffer [fBufferSize] entry buffer TDirectory* fDirectory !Pointer to directory holding this histogram Int_t fDimension !Histogram dimension (1, 2 or 3 dim) Double_t* fIntegral !Integral of bins used by GetRandom TVirtualHistPainter* fPainter !pointer to histogram painter static Int_t fgBufferSize !default buffer size for automatic histograms static Bool_t fgAddDirectory !flag to add histograms to the directory public:
static const enum TObject:: kNoStats static const enum TObject:: kUserContour static const enum TObject:: kCanRebin static const enum TObject:: kLogX static const enum TObject:: kIsZoomed static const enum TObject:: kNoTitle


See also

TH1C, TH1D, TH1F, TH1K, TH1S, TH2, TH3

Class Description

                     The H I S T O G R A M   Classes
                     ===============================

     ROOT supports the following histogram types:

      1-D histograms:
         TH1C : histograms with one byte per channel.   Maximum bin content = 255
         TH1S : histograms with one short per channel.  Maximum bin content = 65535
         TH1F : histograms with one float per channel.  Maximum precision 7 digits
         TH1D : histograms with one double per channel. Maximum precision 14 digits

      2-D histograms:
         TH2C : histograms with one byte per channel.   Maximum bin content = 255
         TH2S : histograms with one short per channel.  Maximum bin content = 65535
         TH2F : histograms with one float per channel.  Maximum precision 7 digits
         TH2D : histograms with one double per channel. Maximum precision 14 digits

      3-D histograms:
         TH3C : histograms with one byte per channel.   Maximum bin content = 255
         TH3S : histograms with one short per channel.  Maximum bin content = 65535
         TH3F : histograms with one float per channel.  Maximum precision 7 digits
         TH3D : histograms with one double per channel. Maximum precision 14 digits

      Profile histograms: See classes  TProfile and TProfile2D
      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; 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.

   - All histogram classes are derived from the base class TH1

                                TH1
                                 ^
                                 |
                                 |
                                 |
         -----------------------------------------------------
                |                |       |      |      |     |
                |                |      TH1C   TH1S   TH1F  TH1D
                |                |                           |
                |                |                           |
                |               TH2                      TProfile
                |                |
                |                |
                |                -----------------------------
                |                        |      |      |     |
                |                       TH2C   TH2S   TH2F  TH2D
                |                                            |
               TH3                                           |
                |                                        TProfile2D
                |
                ------------------------------
                        |      |      |      |
                       TH3C   TH3S   TH3F   TH3D

      The TH*C classes also inherit from the array class TArrayC.
      The TH*S classes also inherit from the array class TArrayS.
      The TH*F classes also inherit from the array class TArrayF.
      The TH*D classes also inherit from the array class TArrayD.

     Creating histograms
     ===================
     Histograms are created by invoking one of the constructors, eg
       TH1F *h1 = new TH1F("h1","h1 title",100,0,4.4);
       TH2F *h2 = new TH2F("h2","h2 title",40,0,4,30,-3,3);
     histograms may also be created by:
       - calling the Clone function, see below
       - making a projection from a 2-D or 3-D histogram, see below
       - reading an histogram from a file
     When an histogram is created, a reference to it is automatically added
     to the list of in-memory objects for the current file or directory.
     This default behaviour can be changed by:
       h->SetDirectory(0);         // for the current histogram h
       TH1::AddDirectory(kFALSE);  // sets a global switch disabling the reference
     When the histogram is deleted, the reference to it is removed from
     the list of objects in memory.
     When a file is closed, all histograms in memory associated with this file
     are automatically deleted.

      Fix or variable bin size
      ========================

     All histogram types support either fix or variable bin sizes.
     2-D histograms may have fix size bins along X and variable size bins
     along Y or vice-versa. The functions to fill, manipulate, draw or access
     histograms are identical in both cases.
     Each histogram always contains 3 objects TAxis: fXaxis, fYaxis and fZaxis
     To access the axis parameters, do:
        TAxis *xaxis = h->GetXaxis(); etc.
        Double_t binCenter = xaxis->GetBinCenter(bin), etc.
     See class TAxis for a description of all the access functions.
     The axis range is always stored internally in double precision.

      Convention for numbering bins
      =============================
      For all histogram types: nbins, xlow, xup
        bin = 0;       underflow bin
        bin = 1;       first bin with low-edge xlow INCLUDED
        bin = nbins;   last bin with upper-edge xup EXCLUDED
        bin = nbins+1; overflow bin
      In case of 2-D or 3-D histograms, a "global bin" number is defined.
      For example, assuming a 3-D histogram with binx,biny,binz, the function
        Int_t bin = h->GetBin(binx,biny,binz);
      returns a global/linearized bin number. This global bin is useful
      to access the bin information independently of the dimension.

     Alphanumeric Bin Labels
     =======================
     By default, an histogram axis is drawn with its numeric bin labels.
     One can specify alphanumeric labels instead with:
        1- call TAxis::SetBinLabel(bin,label);
           This can always be done before or after filling.
           When the histogram is drawn, bin labels will be automatically drawn.
           See example in $ROOTSYS/tutorials/labels1.C, labels2.C
        2- call to a Fill function with one of the arguments being a string, eg
           hist1->Fill(somename,weigth);
           hist2->Fill(x,somename,weight);
           hist2->Fill(somename,y,weight);
           hist2->Fill(somenamex,somenamey,weight);
           See example in $ROOTSYS/tutorials/hlabels1.C, hlabels2.C
        3- via TTree::Draw.
           see for example $ROOTSYS/tutorials/cern.C
           tree.Draw("Nation::Division"); where "Nation" and "Division"
           are two branches of a Tree.
     When using the options 2 or 3 above, the labels are automatically
     added to the list (THashList) of labels for a given axis.
     By default, an axis is drawn with the order of bins corresponding
     to the filling sequence. It is possible to reorder the axis
       - alphabetically
       - by increasing or decreasing values
     The reordering can be triggered via the TAxis contextMenu by selecting
     the menu item "LabelsOption" or by calling directly
        TH1::LabelsOption(option,axis) where
          -axis may be "X","Y" or "Z"
          -option may be:
           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)

     When using the option 2 above, new labels are added by doubling the current
     number of bins in case one label does not exist yet.
     When the Filling is terminated, it is possible to trim the number
     of bins to match the number of active labels by calling
           TH1::LabelsDeflate(axis) with axis = "X","Y" or "Z"
     This operation is automatic when using TTree::Draw.
     Once bin labels have been created, they become persistent if the histogram
     is written to a file or when generating the C++ code via SavePrimitive.

     Histograms with automatic bins
     ==============================
     When an histogram is created with an axis lower limit greater or equal
     to its upper limit, the SetBuffer is automatically called with an
     argument fBufferSize equal to fgBufferSize (default value=1000).
     fgBufferSize may be reset via the static function TH1::SetDefaultBufferSize.
     The axis limits will be automatically computed when the buffer will
     be full or when the function BufferEmpty is called.

     Filling histograms
     ==================
     An histogram is typically filled with statements like:
       h1->Fill(x);
       h1->Fill(x,w); //fill with weight
       h2->Fill(x,y)
       h2->Fill(x,y,w)
       h3->Fill(x,y,z)
       h3->Fill(x,y,z,w)
     or via one of the Fill functions accepting names described above.
     The Fill functions compute the bin number corresponding to the given
     x,y or z argument and increment this bin by the given weight.
     The Fill functions return the bin number for 1-D histograms or global
     bin number for 2-D and 3-D histograms.
     If TH1::Sumw2 has been called before filling, the sum of squares of
     weights is also stored.
     One can also increment directly a bin number via TH1::AddBinContent
     or replace the existing content via TH1::SetBinContent.
     To access the bin content of a given bin, do:
       Double_t binContent = h->GetBinContent(bin);

     By default, the bin number is computed using the current axis ranges.
     If the automatic binning option has been set via
            h->SetBit(TH1::kCanRebin);
     then, the Fill Function will automatically extend the axis range to
     accomodate the new value specified in the Fill argument. The method
     used is to double the bin size until the new value fits in the range,
     merging bins two by two. This automatic binning options is extensively
     used by the TTree::Draw function when histogramming Tree variables
     with an unknown range.
     This automatic binning option is supported for 1-d, 2-D and 3-D histograms.

     During filling, some statistics parameters are incremented to compute
     the mean value and Root Mean Square with the maximum precision.

     In case of histograms of type TH1C, TH1S, TH2C, TH2S, TH3C, TH3S
     a check is made that the bin contents do not exceed the maximum positive
     capacity (127 or 65535). Histograms of all types may have positive
     or/and negative bin contents.

     Rebinning
     =========
     At any time, an histogram can be rebinned via TH1::Rebin. This function
     returns a new histogram with the rebinned contents.
     If bin errors were stored, they are recomputed during the rebinning.

     Associated errors
     =================
     By default, for each bin, the sum of weights is computed at fill time.
     One can also call TH1::Sumw2 to force the storage and computation
     of the sum of the square of weights per bin.
     If Sumw2 has been called, the error per bin is computed as the
     sqrt(sum of squares of weights), otherwise the error is set equal
     to the sqrt(bin content).
     To return the error for a given bin number, do:
        Double_t error = h->GetBinError(bin);

     Associated functions
     ====================
     One or more object (typically a TF1*) can be added to the list
     of functions (fFunctions) associated to each histogram.
     When TH1::Fit is invoked, the fitted function is added to this list.
     Given an histogram h, one can retrieve an associated function
     with:  TF1 *myfunc = h->GetFunction("myfunc");

     Operations on histograms
     ========================

     Many types of operations are supported on histograms or between histograms
     - Addition of an histogram to the current histogram
     - Additions of two histograms with coefficients and storage into the current
       histogram
     - Multiplications and Divisions are supported in the same way as additions.
     - The Add, Divide and Multiply functions also exist to add,divide or multiply
       an histogram by a function.
     If an histogram has associated error bars (TH1::Sumw2 has been called),
     the resulting error bars are also computed assuming independent histograms.
     In case of divisions, Binomial errors are also supported.


     Fitting histograms
     ==================

     Histograms (1-D,2-D,3-D and Profiles) can be fitted with a user
     specified function via TH1::Fit. When an histogram is fitted, the
     resulting function with its parameters is added to the list of functions
     of this histogram. If the histogram is made persistent, the list of
     associated functions is also persistent. Given a pointer (see above)
     to an associated function myfunc, one can retrieve the function/fit
     parameters with calls such as:
       Double_t chi2 = myfunc->GetChisquare();
       Double_t par0 = myfunc->GetParameter(0); //value of 1st parameter
       Double_t err0 = myfunc->GetParError(0);  //error on first parameter


     Projections of histograms
     ========================
     One can:
      - make a 1-D projection of a 2-D histogram or Profile
        see functions TH2::ProjectionX,Y, TH2::ProfileX,Y, TProfile::ProjectionX
      - make a 1-D, 2-D or profile out of a 3-D histogram
        see functions TH3::ProjectionZ, TH3::Project3D.

     One can fit these projections via:
      TH2::FitSlicesX,Y, TH3::FitSlicesZ.

     Random Numbers and histograms
     =============================
     TH1::FillRandom can be used to randomly fill an histogram using
                    the contents of an existing TF1 function or another
                    TH1 histogram (for all dimensions).
     For example the following two statements create and fill an histogram
     10000 times with a default gaussian distribution of mean 0 and sigma 1:
       TH1F h1("h1","histo from a gaussian",100,-3,3);
       h1.FillRandom("gaus",10000);
     TH1::GetRandom can be used to return a random number distributed
                    according the contents of an histogram.

     Making a copy of an histogram
     =============================
     Like for any other Root object derived from TObject, one can use
     the Clone function. This makes an identical copy of the original histogram
     including all associated errors and functions, eg:
       TH1F *hnew = (TH1F*)h->Clone();
       hnew->SetName("hnew"); //recommended, otherwise you get 2 histograms
                              //with the same name

     Normalizing histograms
     ======================
     One can scale an histogram such that the bins integral is equal to
     to the normalization parameter via TH1::Scale(Double_t norm);

     Drawing histograms
     ==================
     Histograms are drawn via the THistPainter class. Each histogram has
     a pointer to its own painter (to be usable in a multithreaded program).
     Many drawing options are supported.
     See THistPainter::Paint for more details.
     The same histogram can be drawn with different options in different pads.
     When an histogram drawn in a pad is deleted, the histogram is
     automatically removed from the pad or pads where it was drawn.
     If an histogram is drawn in a pad, then filled again, the new status
     of the histogram will be automatically shown in the pad next time
     the pad is updated. One does not need to redraw the histogram.
     To draw the current version of an histogram in a pad, one can use
        h->DrawCopy();
     This makes a clone (see Clone below) of the histogram. Once the clone
     is drawn, the original histogram may be modified or deleted without
     affecting the aspect of the clone.

     One can use TH1::SetMaximum and TH1::SetMinimum to force a particular
     value for the maximum or the minimum scale on the plot.

     TH1::UseCurrentStyle can be used to change all histogram graphics
     attributes to correspond to the current selected style.
     This function must be called for each histogram.
     In case one reads and draws many histograms from a file, one can force
     the histograms to inherit automatically the current graphics style
     by calling before gROOT->ForceStyle();


     Setting Drawing histogram contour levels (2-D hists only)
     =========================================================
     By default contours are automatically generated at equidistant
     intervals. A default value of 20 levels is used. This can be modified
     via TH1::SetContour or TH1::SetContourLevel.
     the contours level info is used by the drawing options "cont", "surf",
     and "lego".

     Setting histogram graphics attributes
     =====================================
     The histogram classes inherit from the attribute classes:
       TAttLine, TAttFill, TAttMarker and TAttText.
     See the member functions of these classes for the list of options.

     Giving titles to the X, Y and Z axis
     =================================
       h->GetXaxis()->SetTitle("X axis title");
       h->GetYaxis()->SetTitle("Y axis title");
     The histogram title and the axis titles can be any TLatex string.
     The titles are part of the persistent histogram.

     Saving/Reading histograms to/from a Root file
     ================================
     The following statements create a Root file and store an histogram
     on the file. Because TH1 derives from TNamed, the key identifier on
     the file is the histogram name:
        TFile f("histos.root","new");
        TH1F h1("hgaus","histo from a gaussian",100,-3,3);
        h1.FillRandom("gaus",10000);
        h1->Write();
     To Read this histogram in another Root session, do:
        TFile f("histos.root");
        TH1F *h = (TH1F*)f.Get("hgaus");
     One can save all histograms in memory to the file by:
     file->Write();

     Miscelaneous operations
     =======================

      TH1::KolmogorovTest: Statistical test of compatibility in shape between
                           two histograms.
      TH1::Smooth smooths the bin contents of a 1-d histogram
      TH1::Integral returns the integral of bin contents in a given bin range
      TH1::GetMean(int axis) returns the mean value along axis
      TH1::GetRMS(int axis)  returns the Root Mean Square along axis
      TH1::GetEntries returns the number of entries
      TH1::Reset() resets the bin contents and errors of an histogram.


/*

*/

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TH1(): TNamed(), TAttLine(), TAttFill(), TAttMarker()
   -*-*-*-*-*-*-*-*-*Histogram default constructor*-*-*-*-*-*-*-*-*-*-*-*-*
                     =============================

~TH1()
   -*-*-*-*-*-*-*-*-*Histogram default destructor*-*-*-*-*-*-*-*-*-*-*-*-*-*
                     ============================

TH1(const char *name,const char *title,Int_t nbins,Axis_t xlow,Axis_t xup) :TNamed(name,title), TAttLine(), TAttFill(), TAttMarker()
   -*-*-*-*-*-*-*Normal constructor for fix bin size histograms*-*-*-*-*-*-*
                 ==============================================

     Creates the main histogram structure:
        name   : name of histogram (avoid blanks)
        title  : histogram title
        nbins  : number of bins
        xlow   : low edge of first bin
        xup    : upper edge of last bin (not included in last bin)

      When an histogram is created, it is automatically added to the list
      of special objects in the current directory.
      To find the pointer to this histogram in the current directory
      by its name, do:
      TH1F *h1 = (TH1F*)gDirectory->FindObject(name);

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TH1(const char *name,const char *title,Int_t nbins,const Float_t *xbins) :TNamed(name,title), TAttLine(), TAttFill(), TAttMarker()
   -*-*-*-*-*Normal constructor for variable bin size histograms*-*-*-*-*-*-*
             ===================================================

  Creates the main histogram structure:
     name   : name of histogram (avoid blanks)
     title  : histogram title
     nbins  : number of bins
     xbins  : array of low-edges for each bin
              This is an array of size nbins+1

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TH1(const char *name,const char *title,Int_t nbins,const Double_t *xbins) :TNamed(name,title), TAttLine(), TAttFill(), TAttMarker()
   -*-*-*-*-*Normal constructor for variable bin size histograms*-*-*-*-*-*-*
             ===================================================

  Creates the main histogram structure:
     name   : name of histogram (avoid blanks)
     title  : histogram title
     nbins  : number of bins
     xbins  : array of low-edges for each bin
              This is an array of size nbins+1

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Bool_t AddDirectoryStatus()
static function: cannot be inlined on Windows/NT

void Browse(TBrowser *)

void Build()
   -*-*-*-*-*-*-*-*Creates histogram basic data structure*-*-*-*-*-*-*-*-*-*
                   ======================================

void Add(TF1 *f1, Double_t c1)
 Performs the operation: this = this + c1*f1
 if errors are defined (see TH1::Sumw2), errors are also recalculated.

 Only bins inside the function range are recomputed.
 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Add

void Add(const TH1 *h1, Double_t c1)
 Performs the operation: this = this + c1*h1
 if errors are defined (see TH1::Sumw2), errors are also recalculated.
 Note that if h1 has Sumw2 set, Sumw2 is automatically called for this
 if not already set.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Add

void Add(const TH1 *h1, const TH1 *h2, Double_t c1, Double_t c2)
   -*-*-*Replace contents of this histogram by the addition of h1 and h2*-*-*
         ===============================================================

   this = c1*h1 + c2*h2
   if errors are defined (see TH1::Sumw2), errors are also recalculated
   Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this
   if not already set.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Add

void AddBinContent(Int_t)
   -*-*-*-*-*-*-*-*Increment bin content by 1*-*-*-*-*-*-*-*-*-*-*-*-*-*
                   ==========================

void AddBinContent(Int_t, Stat_t)
   -*-*-*-*-*-*-*-*Increment bin content by a weight w*-*-*-*-*-*-*-*-*-*-*
                   ===================================

void AddDirectory(Bool_t add)
 Sets the flag controlling the automatic add of histograms in memory

 By default (fAddDirectory = kTRUE), histograms are automatically added
 to the list of objects in memory.
 Note that one histogram can be removed from its support directory
 by calling h->SetDirectory(0) or h->SetDirectory(dir) to add it
 to the list of objects in the directory dir.

  NOTE that this is a static function. To call it, use;
     TH1::AddDirectory

Int_t BufferEmpty(Bool_t deleteBuffer)
 Fill histogram with all entries in the buffer.
 The buffer is deleted if deleteBuffer is true.

Int_t BufferFill(Axis_t x, Stat_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

Double_t ComputeIntegral()
  Compute integral (cumulative sum of bins)
  The result stored in fIntegral is used by the GetRandom functions.
  This function is automatically called by GetRandom when the fIntegral
  array does not exist or when the number of entries in the histogram
  has changed since the previous call to GetRandom.
  The resulting integral is normalized to 1

void Copy(TObject &obj) const
   -*-*-*-*-*Copy this histogram structure to newth1*-*-*-*-*-*-*-*-*-*-*-*
             =======================================

 Note that this function does not copy the list of associated functions.
 Use TObJect::Clone to make a full copy of an histogram.

Int_t DistancetoPrimitive(Int_t px, Int_t py)
   -*-*-*-*-*-*-*-*-*Compute distance from point px,py to a line*-*-*-*-*-*
                     ===========================================
     Compute the closest distance of approach from point px,py to elements
     of an histogram.
     The distance is computed in pixels units.

     Algorithm:
     Currently, this simple model computes the distance from the mouse
     to the histogram contour only.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

void Divide(TF1 *f1, Double_t c1)
 Performs the operation: this = this/(c1*f1)
 if errors are defined (see TH1::Sumw2), errors are also recalculated.

 Only bins inside the function range are recomputed.
 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Divide

void Divide(const TH1 *h1)
   -*-*-*-*-*-*-*-*-*Divide this histogram by h1*-*-*-*-*-*-*-*-*-*-*-*-*
                     ===========================

   this = this/h1
   if errors are defined (see TH1::Sumw2), errors are also recalculated.
   Note that if h1 has Sumw2 set, Sumw2 is automatically called for this
   if not already set.
   The resulting errors are calculated assuming uncorrelated histograms.
   See the other TH1::Divide that gives the possibility to optionaly
   compute Binomial errors.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Scale

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

   this = c1*h1/(c2*h2)

   if errors are defined (see TH1::Sumw2), errors are also recalculated
   Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this
   if not already set.
   The resulting errors are calculated assuming uncorrelated histograms.
   However, if option ="B" is specified, Binomial errors are computed.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Divide

void Draw(Option_t *option)
   -*-*-*-*-*-*-*-*-*Draw this histogram with options*-*-*-*-*-*-*-*-*-*-*-*
                     ================================

     Histograms are drawn via the THistPainter class. Each histogram has
     a pointer to its own painter (to be usable in a multithreaded program).
     The same histogram can be drawn with different options in different pads.
     When an histogram drawn in a pad is deleted, the histogram is
     automatically removed from the pad or pads where it was drawn.
     If an histogram is drawn in a pad, then filled again, the new status
     of the histogram will be automatically shown in the pad next time
     the pad is updated. One does not need to redraw the histogram.
     To draw the current version of an histogram in a pad, one can use
        h->DrawCopy();
     This makes a clone of the histogram. Once the clone is drawn, the original
     histogram may be modified or deleted without affecting the aspect of the
     clone.
     By default, TH1::Draw clears the current pad.

     One can use TH1::SetMaximum and TH1::SetMinimum to force a particular
     value for the maximum or the minimum scale on the plot.

     TH1::UseCurrentStyle can be used to change all histogram graphics
     attributes to correspond to the current selected style.
     This function must be called for each histogram.
     In case one reads and draws many histograms from a file, one can force
     the histograms to inherit automatically the current graphics style
     by calling before gROOT->ForceStyle();

     See THistPainter::Paint for a description of all the drawing options
     =======================

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TH1* DrawCopy(Option_t *) const
   -*-*-*-*-*Copy this histogram and Draw in the current pad*-*-*-*-*-*-*-*
             ===============================================

     Once the histogram is drawn into the pad, any further modification
     using graphics input will be made on the copy of the histogram,
     and not to the original object.

     See Draw for the list of options

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TH1* DrawNormalized(Option_t *option, Double_t norm) const
  Draw a normalized copy of this histogram.

  A clone of this histogram is normalized to norm and drawn with option.
  A pointer to the normalized histogram is returned.
  The contents of the histogram copy are scaled such that the new
  sum of weights (excluding under and overflow) is equal to norm.
  Note that the returned normalized histogram is not added to the list
  of histograms in the current directory in memory.
  It is the user's responsability to delete this histogram.
  The kCanDelete bit is set for the returned object. If a pad containing
  this copy is cleared, the histogram will be automatically deleted.

     See Draw for the list of options

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

void DrawPanel()
   -*-*-*-*-*Display a panel with all histogram drawing options*-*-*-*-*-*
             ==================================================

      See class TDrawPanelHist for example

void Eval(TF1 *f1, Option_t *option)
   -*-*-*Evaluate function f1 at the center of bins of this histogram-*-*-*-*
         ============================================================

     If option "R" is specified, the function is evaluated only
     for the bins included in the function range.
     If option "A" is specified, the value of the function is added to the
     existing bin contents
     If option "S" is specified, the value of the function is used to
     generate a value, distributed according to the Poisson
     distribution, with f1 as the mean.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

void ExecuteEvent(Int_t event, Int_t px, Int_t py)
   -*-*-*-*-*-*-*-*-*Execute action corresponding to one event*-*-*-*
                     =========================================
     This member function is called when a histogram is clicked with the locator

     If Left button clicked on the bin top value, then the content of this bin
     is modified according to the new position of the mouse when it is released.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Int_t Fill(Axis_t x)
   -*-*-*-*-*-*-*-*Increment bin with abscissa X by 1*-*-*-*-*-*-*-*-*-*-*
                   ==================================

    if x is less than the low-edge of the first bin, the Underflow bin is incremented
    if x is greater than the upper edge of last bin, the Overflow bin is incremented

    If the storage of the sum of squares of weights has been triggered,
    via the function Sumw2, then the sum of the squares of weights is incremented
    by 1 in the bin corresponding to x.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Int_t Fill(Axis_t x, Stat_t w)
   -*-*-*-*-*-*Increment bin with abscissa X with a weight w*-*-*-*-*-*-*-*
               =============================================

    if x is less than the low-edge of the first bin, the Underflow bin is incremented
    if x is greater than the upper edge of last bin, the Overflow bin is incremented

    If the storage of the sum of squares of weights has been triggered,
    via the function Sumw2, then the sum of the squares of weights is incremented
    by w^2 in the bin corresponding to x.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Int_t Fill(const char *namex, Stat_t w)
 Increment bin with namex with a weight w

 if x is less than the low-edge of the first bin, the Underflow bin is incremented
 if x is greater than the upper edge of last bin, the Overflow bin is incremented

 If the storage of the sum of squares of weights has been triggered,
 via the function Sumw2, then the sum of the squares of weights is incremented
 by w^2 in the bin corresponding to x.


void FillN(Int_t ntimes, const Axis_t *x, const Double_t *w, Int_t stride)
   -*-*-*-*-*-*Fill this histogram with an array x and weights w*-*-*-*-*
               =================================================

    ntimes:  number of entries in arrays x and w (array size must be ntimes*stride)
    x:       array of values to be histogrammed
    w:       array of weighs
    stride:  step size through arrays x and w

    If the storage of the sum of squares of weights has been triggered,
    via the function Sumw2, then the sum of the squares of weights is incremented
    by w[i]^2 in the bin corresponding to x[i].
    if w is NULL each entry is assumed a weight=1

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

void FillRandom(const char *fname, Int_t ntimes)
   -*-*-*-*-*Fill histogram following distribution in function fname*-*-*-*
             =======================================================

      The distribution contained in the function fname (TF1) is integrated
      over the channel contents.
      It is normalized to 1.
      Getting one random number implies:
        - Generating a random number between 0 and 1 (say r1)
        - Look in which bin in the normalized integral r1 corresponds to
        - Fill histogram channel
      ntimes random numbers are generated

     One can also call TF1::GetRandom to get a random variate from a function.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-**-*-*-*-*-*-*-*

void FillRandom(TH1 *h, Int_t ntimes)
   -*-*-*-*-*Fill histogram following distribution in histogram h*-*-*-*
             ====================================================

      The distribution contained in the histogram h (TH1) is integrated
      over the channel contents.
      It is normalized to 1.
      Getting one random number implies:
        - Generating a random number between 0 and 1 (say r1)
        - Look in which bin in the normalized integral r1 corresponds to
        - Fill histogram channel
      ntimes random numbers are generated

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-**-*-*-*-*-*-*-*

Int_t FindBin(Axis_t x, Axis_t y, Axis_t z)
   -*-*-*-*Return Global bin number corresponding to x,y,z*-*-*-*-*-*-*
           ===============================================

      2-D and 3-D histograms are represented with a one dimensional
      structure.
      This has the advantage that all existing functions, such as
        GetBinContent, GetBinError, GetBinFunction work for all dimensions.
     See also TH1::GetBin
   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TObject* FindObject(const char *name) const
 search object named name in the list of functions

TObject* FindObject(const TObject *obj) const
 search object obj in the list of functions

Int_t Fit(const char *fname ,Option_t *option ,Option_t *goption, Axis_t xxmin, Axis_t xxmax)
                     Fit histogram with function fname
                     =================================
      fname is the name of an already predefined function created by TF1 or TF2
      Predefined functions such as gaus, expo and poln are automatically
      created by ROOT.

  This function finds a pointer to the TF1 object with name fname
  and calls TH1::Fit(TF1 *f1,...)

Int_t Fit(TF1 *f1 ,Option_t *option ,Option_t *goption, Axis_t xxmin, Axis_t xxmax)
                     Fit histogram with function f1
                     ==============================

      Fit this histogram with function f1.

      The list of fit options is given in parameter option.
         option = "W"  Set all errors to 1
                = "I" Use integral of function in bin instead of value at bin center
                = "L" Use Loglikelihood method (default is chisquare method)
                = "U" Use a User specified fitting algorithm (via SetFCN)
                = "Q" Quiet mode (minimum printing)
                = "V" Verbose mode (default is between Q and V)
                = "E" Perform better Errors estimation using Minos technique
                = "M" More. Improve fit results
                = "R" Use the Range specified in the function range
                = "N" Do not store the graphics function, do not draw
                = "0" Do not plot the result of the fit. By default the fitted function
                      is drawn unless the option"N" above is specified.
                = "+" Add this new fitted function to the list of fitted functions
                      (by default, any previous function is deleted)

      When the fit is drawn (by default), the parameter goption may be used
      to specify a list of graphics options. See TH1::Draw for a complete
      list of these options.

      In order to use the Range option, one must first create a function
      with the expression to be fitted. For example, if your histogram
      has a defined range between -4 and 4 and you want to fit a gaussian
      only in the interval 1 to 3, you can do:
           TF1 *f1 = new TF1("f1","gaus",1,3);
           histo->Fit("f1","R");

      Setting initial conditions
      ==========================
      Parameters must be initialized before invoking the Fit function.
      The setting of the parameter initial values is automatic for the
      predefined functions : poln, expo, gaus. One can however disable
      this automatic computation by specifying the option "B".
      You can specify boundary limits for some or all parameters via
           f1->SetParLimits(p_number, parmin, parmax);
      if parmin>=parmax, the parameter is fixed
      Note that you are not forced to fix the limits for all parameters.
      For example, if you fit a function with 6 parameters, you can do:
        func->SetParameters(0,3.1,1.e-6,-8,0,100);
        func->SetParLimits(3,-10,-4);
        func->FixParameter(4,0);
        func->SetParLimits(5, 1,1);
      With this setup, parameters 0->2 can vary freely
      Parameter 3 has boundaries [-10,-4] with initial value -8
      Parameter 4 is fixed to 0
      Parameter 5 is fixed to 100.
      When the lower limit and upper limit are equal, the parameter is fixed.
      However to fix a parameter to 0, one must call the FixParameter function.

      Note that option "I" gives better results but is slower.


      Changing the fitting function
      =============================
     By default the fitting function H1FitChisquare is used.
     To specify a User defined fitting function, specify option "U" and
     call the following functions:
       TVirtualFitter::Fitter(myhist)->SetFCN(MyFittingFunction)
     where MyFittingFunction is of type:
     extern void MyFittingFunction(Int_t &npar, Double_t *gin, Double_t &f, Double_t *u, Int_t flag);

     Associated functions
     ====================
     One or more object (typically a TF1*) can be added to the list
     of functions (fFunctions) associated to each histogram.
     When TH1::Fit is invoked, the fitted function is added to this list.
     Given an histogram h, one can retrieve an associated function
     with:  TF1 *myfunc = h->GetFunction("myfunc");

      Access to the fit results
      =========================
     If the histogram is made persistent, the list of
     associated functions is also persistent. Given a pointer (see above)
     to an associated function myfunc, one can retrieve the function/fit
     parameters with calls such as:
       Double_t chi2 = myfunc->GetChisquare();
       Double_t par0 = myfunc->GetParameter(0); //value of 1st parameter
       Double_t err0 = myfunc->GetParError(0);  //error on first parameter

      Access to the fit covariance matrix
      ===================================
      Example1:
         TH1F h("h","test",100,-2,2);
         h.FillRandom("gaus",1000);
         h.Fit("gaus");
         Double_t matrix[3][3];
         gMinuit->mnemat(&matrix[0][0],3);
      Example2:
         TH1F h("h","test",100,-2,2);
         h.FillRandom("gaus",1000);
         h.Fit("gaus");
         TMatrixD matrix(npar,npar);
         gMinuit->mnemat(matrix.GetElements(),npar);
         matrix.Print();
         matrix.Draw("text");


      Changing the maximum number of parameters
      =========================================
     By default, the fitter TMinuit is initialized with a maximum of 25 parameters.
     You can redefine this default value by calling :
       TVirtualFitter::Fitter(0,150); //to get a maximum of 150 parameters

      Excluding points
      ================
     Use TF1::RejectPoint inside your fitting function to exclude points
     within a certain range from the fit. Example:
     Double_t fline(Double_t *x, Double_t *par)
     {
         if (x[0] > 2.5 && x[0] < 3.5) {
           TF1::RejectPoint();
           return 0;
        }
        return par[0] + par[1]*x[0];
     }

     void exclude() {
        TF1 *f1 = new TF1("f1","[0] +[1]*x +gaus(2)",0,5);
        f1->SetParameters(6,-1,5,3,0.2);
        TH1F *h = new TH1F("h","background + signal",100,0,5);
        h->FillRandom("f1",2000);
        TF1 *fline = new TF1("fline",fline,0,5,2);
        fline->SetParameters(2,-1);
        h->Fit("fline","l");
     }

      Warning when using the option "0"
      =================================
     When selecting the option "0", the fitted function is added to
     the list of functions of the histogram, but it is not drawn.
     You can undo what you disabled in the following way:
       h.Fit("myFunction","0"); // fit, store function but do not draw
       h.Draw(); function is not drawn
       const Int_t kNotDraw = 1<<9;
       h.GetFunction("myFunction")->ResetBit(kNotDraw);
       h.Draw();  // function is visible again

     By default, the fitter TMinuit is initialized with a maximum of 25 parameters.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

void FitPanel()
   -*-*-*-*-*Display a panel with all histogram fit options*-*-*-*-*-*
             ==============================================

      See class TFitPanel for example

TH1* GetAsymmetry(TH1* h2, Double_t c2, Double_t dc2)
  return an histogram containing the asymmetry of this histogram with h2,
  where the asymmetry is defined as:

  Asymmetry = (h1 - h2)/(h1 + h2)  where h1 = this

  works for 1D, 2D, etc. histograms
  c2 is an optional argument that gives a relative weight between the two
  histograms, and dc2 is the error on this weight.  This is useful, for example,
  when forming an asymmetry between two histograms from 2 different data sets that
  need to be normalized to each other in some way.  The function calculates
  the errors asumming Poisson statistics on h1 and h2 (that is, dh = sqrt(h)).

  example:  assuming 'h1' and 'h2' are already filled

     h3 = h1->GetAsymmetry(h2)

  then 'h3' is created and filled with the asymmetry between 'h1' and 'h2';
  h1 and h2 are left intact.

  Note that it is the user's responsibility to manage the created histogram.

  code proposed by Jason Seely (seely@mit.edu) and adapted by R.Brun

Int_t GetDefaultBufferSize()
 return the default buffer size for automatic histograms
 the parameter fgBufferSize may be changed via SetDefaultBufferSize

Double_t GetEntries() const
 return the current number of entries

char* GetObjectInfo(Int_t px, Int_t py) const
   Redefines TObject::GetObjectInfo.
   Displays the histogram info (bin number, contents, integral up to bin
   corresponding to cursor position px,py


TVirtualHistPainter* GetPainter()
 return pointer to painter
 if painter does not exist, it is created

Int_t GetQuantiles(Int_t nprobSum, Double_t *q, const Double_t *probSum)
  Compute Quantiles for this histogram
     Quantile x_q of a probability distribution Function F is defined as

        F(x_q) = q with 0 <= q <= 1.

     For instance the median x_0.5 of a distribution is defined as that value
     of the random variable for which the distribution function equals 0.5:

        F(x_0.5) = Probability(x < x_0.5) = 0.5

  code from Eddy Offermann, Renaissance

 input parameters
   - this 1-d histogram (TH1F,D,etc). Could also be a TProfile
   - nprobSum maximum size of array q and size of array probSum (if given)
   - probSum array of positions where quantiles will be computed.
     if probSum is null, probSum will be computed internally and will
     have a size = number of bins + 1 in h. it will correspond to the
      quantiles calculated at the lowest edge of the histogram (quantile=0) and
     all the upper edges of the bins.
     if probSum is not null, it is assumed to contain at least nprobSum values.
  output
   - return value nq (<=nprobSum) with the number of quantiles computed
   - array q filled with nq quantiles

  Note that the Integral of the histogram is automatically recomputed
  if the number of entries is different of the number of entries when
  the integral was computed last time. In case you do not use the Fill
  functions to fill your histogram, but SetBinContent, you must call
  TH1::ComputeIntegral before calling this function.

  Getting quantiles q from two histograms and storing results in a TGraph,
   a so-called QQ-plot

     TGraph *gr = new TGraph(nprob);
     h1->GetQuantiles(nprob,gr->GetX());
     h2->GetQuantiles(nprob,gr->GetY());
     gr->Draw("alp");

 Example:
     void quantiles() {
        // demo for quantiles
        const Int_t nq = 20;
        TH1F *h = new TH1F("h","demo quantiles",100,-3,3);
        h->FillRandom("gaus",5000);

        Double_t xq[nq];  // position where to compute the quantiles in [0,1]
        Double_t yq[nq];  // array to contain the quantiles
        for (Int_t i=0;i<nq;i++) xq[i] = Float_t(i+1)/nq;
        h->GetQuantiles(nq,yq,xq);

        //show the original histogram in the top pad
        TCanvas *c1 = new TCanvas("c1","demo quantiles",10,10,700,900);
        c1->Divide(1,2);
        c1->cd(1);
        h->Draw();

        // show the quantiles in the bottom pad
        c1->cd(2);
        gPad->SetGrid();
        TGraph *gr = new TGraph(nq,xq,yq);
        gr->SetMarkerStyle(21);
        gr->Draw("alp");
     }

Int_t FitOptionsMake(Option_t *choptin)
   -*-*-*-*-*-*-*Decode string choptin and fill Foption structure*-*-*-*-*-*
                 ================================================

Int_t GetBin(Int_t binx, Int_t biny, Int_t binz) const
   -*-*-*-*Return Global bin number corresponding to binx,y,z*-*-*-*-*-*-*
           ==================================================

      2-D and 3-D histograms are represented with a one dimensional
      structure.
      This has the advantage that all existing functions, such as
        GetBinContent, GetBinError, GetBinFunction work for all dimensions.

     In case of a TH1x, returns binx directly.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Axis_t GetRandom()
 return a random number distributed according the histogram bin contents.
 This function checks if the bins integral exists. If not, the integral
 is evaluated, normalized to one.
 The integral is automatically recomputed if the number of entries
 is not the same then when the integral was computed.
 NB Only valid for 1-d histograms. Use GetRandom2 or 3 otherwise.

Stat_t GetBinContent(Int_t) const
   -*-*-*-*-*Return content of bin number bin
             ================================
 Implemented in TH1C,S,F,D

Stat_t GetBinContent(Int_t binx, Int_t biny) const
   -*-*-*-*-*Return content of bin number binx, biny
             =======================================
 NB: Function to be called for 2-d histograms only

Stat_t GetBinContent(Int_t binx, Int_t biny, Int_t binz) const
   -*-*-*-*-*Return content of bin number binx,biny,binz
             ===========================================
 NB: Function to be called for 3-d histograms only

TAxis* GetXaxis() const
 return a pointer to the X axis object

TAxis* GetYaxis() const
 return a pointer to the Y axis object

TAxis* GetZaxis() const
 return a pointer to the Z axis object

void LabelsDeflate(Option_t *ax)
 Reduce the number of bins for this axis to the number of bins having a label.

void LabelsInflate(Option_t *ax)
 Double the number of bins for axis.
 Refill histogram
 This function is called by TAxis::FindBin(const char *label)

void LabelsOption(Option_t *option, Option_t *ax)
  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)

Int_t Merge(TCollection *list)
 Add all histograms in the collection to 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.
 The function returns the merged number of entries 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.
 Example:

void Multiply(TF1 *f1, Double_t c1)
 Performs the operation: this = this*c1*f1
 if errors are defined (see TH1::Sumw2), errors are also recalculated.

 Only bins inside the function range are recomputed.
 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Multiply

void Multiply(const TH1 *h1)
   -*-*-*-*-*-*-*-*-*Multiply this histogram by h1*-*-*-*-*-*-*-*-*-*-*-*-*
                     =============================

   this = this*h1

   If errors of this are available (TH1::Sumw2), errors are recalculated.
   Note that if h1 has Sumw2 set, Sumw2 is automatically called for this
   if not already set.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Multiply

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

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

   If errors of this are available (TH1::Sumw2), errors are recalculated.
   Note that if h1 or h2 have Sumw2 set, Sumw2 is automatically called for this
   if not already set.

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Multiply

void Paint(Option_t *option)
   -*-*-*-*-*-*-*Control routine to paint any kind of histograms*-*-*-*-*-*-*
                 ===============================================

  This function is automatically called by TCanvas::Update.
  (see TH1::Draw for the list of options)

TH1* Rebin(Int_t ngroup, const char*newname)
   -*-*-*Rebin this histogram grouping ngroup bins together*-*-*-*-*-*-*-*-*
         ==================================================
   if newname is not blank a new temporary histogram hnew is created.
   else the current histogram is modified (default)
   The parameter ngroup indicates how many bins of this have to me merged
   into one bin of hnew
   If the original histogram has errors stored (via Sumw2), the resulting
   histograms has new errors correctly calculated.

   examples: if h1 is an existing TH1F histogram with 100 bins
     h1->Rebin();  //merges two bins in one in h1: previous contents of h1 are lost
     h1->Rebin(5); //merges five bins in one in h1
     TH1F *hnew = h1->Rebin(5,"hnew"); // creates a new histogram hnew
                                       //merging 5 bins of h1 in one bin
   NOTE1: This function is currently implemented only for 1-D histograms

   NOTE2: If ngroup is not an exact divider of the number of bins,
          the top limit of the rebinned histogram 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.

   NOTE3: This function cannot be used with variable bin size histograms.

void RebinAxis(Axis_t x, const char *ax)
 Histogram is resized along ax 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 algorithm works for 1-d, 2-d and 3-d histograms.
 The bit kCanRebin must be set before invoking this function.
  Ex:  h->SetBit(TH1::kCanRebin);

void Scale(Double_t c1)
   -*-*-*Multiply this histogram by a constant c1*-*-*-*-*-*-*-*-*
         ========================================

   this = c1*this

 Note that both contents and errors(if any) are scaled.
 This function uses the services of TH1::Add

 IMPORTANT NOTE: If you intend to use the errors of this histogram later
 you should call Sumw2 before making this operation.
 This is particularly important if you fit the histogram after TH1::Scale

void SetDefaultBufferSize(Int_t buffersize)
 static function to set the default buffer size for automatic histograms.
 When an histogram is created with one of its axis lower limit greater
 or equal to its upper limit, the function SetBuffer is automatically
 called with the default buffer size.

void SmoothArray(Int_t NN, Double_t *XX, Int_t ntimes)
 smooth array XX, translation of Hbook routine hsmoof.F
 based on algorithm 353QH twice presented by J. Friedman
 in Proc.of the 1974 CERN School of Computing, Norway, 11-24 August, 1974.

Double_t SmoothMedian(Int_t n, Double_t *a)
 return the median of a vector a in monotonic order with length n
 where median is a number which divides sequence of n numbers
 into 2 halves. When n is odd, the median is kth element k = (n + 1) / 2.
 when n is even the median is a mean of the elements k = n/2 and k = n/2 + 1.

void Smooth(Int_t ntimes)
 Smooth bin contents of this histogram.
 bin contents are replaced by their smooth values.
 Errors (if any) are not modified.
 algorithm can only be applied to 1-d histograms

void Streamer(TBuffer &b)
   -*-*-*-*-*-*-*Stream a class object*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
                 =====================

void Print(Option_t *option) const
   -*-*-*-*-*Print some global quantities for this histogram*-*-*-*-*-*-*-*
             ===============================================

  If option "range" is given, bin contents and errors are also printed
                     for all bins in the current range (default 1-->nbins)
  If option "all" is given, bin contents and errors are also printed
                     for all bins including under and overflows.


void Rebuild(Option_t *)
 Using the current bin info, recompute the arrays for contents and errors

void Reset(Option_t *option)
   -*-*-*-*-*-*Reset this histogram: contents, errors, etc*-*-*-*-*-*-*-*
               ===========================================

 if option "ICE" is specified, resets only Integral, Contents and Errors

void SavePrimitive(ofstream &out, Option_t *option)
 Save primitive as a C++ statement(s) on output stream out

void UseCurrentStyle()
   -*-*-*-*Replace current attributes by current style*-*-*-*-*
           ===========================================

Stat_t GetMean(Int_t axis) const
   -*-*-*-*-*-*Return mean value of this histogram along the X axis*-*-*-*-*
               ====================================================

Stat_t GetRMS(Int_t axis) const
   -*-*-*-*-*-*Return the Root Mean Square value of this histogram*-*-*-*-*
               ===================================================

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

 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 PutStats(Stat_t *stats)
 Replace current statistics with the values in array stats

Stat_t GetSumOfWeights() const
   -*-*-*-*-*-*Return the sum of weights excluding under/overflows*-*-*-*-*
               ===================================================

Stat_t Integral(Option_t *option) const
Return integral of bin contents. Only bins in the bins range are considered.
 By default the integral is computed as the sum of bin contents in the range.
 if option "width" is specified, the integral is the sum of
 the bin contents multiplied by the bin width in x.

Stat_t Integral(Int_t binx1, Int_t binx2, Option_t *option) const
Return integral of bin contents between binx1 and binx2 for a 1-D histogram
 By default the integral is computed as the sum of bin contents in the range.
 if option "width" is specified, the integral is the sum of
 the bin contents multiplied by the bin width in x.

Double_t KolmogorovTest(TH1 *h2, Option_t *option) const
  Statistical test of compatibility in shape between
  THIS histogram and h2, using Kolmogorov test.
     Default: Ignore under- and overflow bins in comparison

     option is a character string to specify options
         "U" include Underflows in test  (also for 2-dim)
         "O" include Overflows     (also valid for 2-dim)
         "N" include comparison of normalizations
         "D" Put out a line of "Debug" printout
         "M" Return the Maximum Kolmogorov distance instead of prob
         "X" Run the pseudo experiments post-processor with the following procedure:
             make pseudoexperiments based on random values from the parent
             distribution and compare the KS distance of the pseudoexperiment
             to the parent distribution. Bin the KS distances in a histogram,
             and then take the integral of all the KS values above the value
             obtained from the original data to Monte Carlo distribution.
             The number of pseudo-experiments NEXPT is currently fixed at 1000.
             The function returns the integral.
             (thanks to Ben Kilminster to submit this procedure). Note that
             this option "X" is much slower.

   The returned function value is the probability of test
       (much less than one means NOT compatible)

  Code adapted by Rene Brun from original HBOOK routine HDIFF

void SetContent(const Stat_t *content)
   -*-*-*-*-*-*Replace bin contents by the contents of array content*-*-*-*
               =====================================================

Int_t GetContour(Double_t *levels)
  Return contour values into array levels if pointer levels is non zero

  The function returns the number of contour levels.
  see GetContourLevel to return one contour only


Double_t GetContourLevel(Int_t level) const
 Return value of contour number level
 see GetContour to return the array of all contour levels

void SetBuffer(Int_t buffersize, Option_t * /*option*/)
 set the maximum number of entries to be kept in the buffer

void SetContour(Int_t nlevels, const Double_t *levels)
   -*-*-*-*-*-*Set the number and values of contour levels*-*-*-*-*-*-*-*-*
               ===========================================

  By default the number of contour levels is set to 20.

  if argument levels = 0 or issing, equidistant contours are computed


void SetContourLevel(Int_t level, Double_t value)
   -*-*-*-*-*-*-*-*-*Set value for one contour level*-*-*-*-*-*-*-*-*-*-*-*
                     ===============================

Double_t GetMaximum() const
   -*-*-*-*-*-*-*-*-*Return maximum value of bins in the range*-*-*-*-*-*
                     =========================================

Int_t GetMaximumBin() const
   -*-*-*-*-*Return location of bin with maximum value in the range*-*
             ======================================================

Int_t GetMaximumBin(Int_t &locmax, Int_t &locmay, Int_t &locmaz) const
   -*-*-*-*-*Return location of bin with maximum value in the range*-*
             ======================================================

Double_t GetMinimum() const
   -*-*-*-*-*-*-*-*-*Return minimum value of bins in the range-*-*-*-*-*
                     =========================================

Int_t GetMinimumBin() const
   -*-*-*-*-*Return location of bin with minimum value in the range*-*
             ======================================================

Int_t GetMinimumBin(Int_t &locmix, Int_t &locmiy, Int_t &locmiz) const
   -*-*-*-*-*Return location of bin with minimum value in the range*-*
             ======================================================

void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax)
   -*-*-*-*-*-*-*Redefine  x axis parameters*-*-*-*-*-*-*-*-*-*-*-*
                 ===========================
 The X axis parameters are modified.
 The bins content array is resized
 if errors (Sumw2) the errors array is resized
 The previous bin contents are lost
 To change only the axis limits, see TAxis::SetRange

void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax, Int_t ny, Axis_t ymin, Axis_t ymax)
   -*-*-*-*-*-*-*Redefine  x and y axis parameters*-*-*-*-*-*-*-*-*-*-*-*
                 =================================
 The X and Y axis parameters are modified.
 The bins content array is resized
 if errors (Sumw2) the errors array is resized
 The previous bin contents are lost
 To change only the axis limits, see TAxis::SetRange

void SetBins(Int_t nx, Axis_t xmin, Axis_t xmax, Int_t ny, Axis_t ymin, Axis_t ymax, Int_t nz, Axis_t zmin, Axis_t zmax)
   -*-*-*-*-*-*-*Redefine  x, y and z axis parameters*-*-*-*-*-*-*-*-*-*-*-*
                 ====================================
 The X, Y and Z axis parameters are modified.
 The bins content array is resized
 if errors (Sumw2) the errors array is resized
 The previous bin contents are lost
 To change only the axis limits, see TAxis::SetRange

void SetMaximum(Double_t maximum)
   -*-*-*-*-*-*-*Set the maximum value for the Y axis*-*-*-*-*-*-*-*-*-*-*-*
                 ====================================
 By default the maximum value is automatically set to the maximum
 bin content plus a margin of 10 per cent.
 Use TH1::GetMaximum to find the maximum value of an histogram
 Use TH1::GetMaximumBin to find the bin with the maximum value of an histogram


void SetMinimum(Double_t minimum)
   -*-*-*-*-*-*-*Set the minimum value for the Y axis*-*-*-*-*-*-*-*-*-*-*-*
                 ====================================
 By default the minimum value is automatically set to zero if all bin contents
 are positive or the minimum - 10 per cent otherwise.
 Use TH1::GetMinimum to find the minimum value of an histogram
 Use TH1::GetMinimumBin to find the bin with the minimum value of an histogram


void SetDirectory(TDirectory *dir)
 By default when an histogram is created, it is added to the list
 of histogram objects in the current directory in memory.
 Remove reference to this histogram from current directory and add
 reference to new directory dir. dir can be 0 in which case the
 histogram does not belong to any directory.

void SetError(const Stat_t *error)
   -*-*-*-*-*-*-*Replace bin errors by values in array error*-*-*-*-*-*-*-*-*
                 ===========================================

void SetName(const char *name)
 Change the name of this histogram


void SetNameTitle(const char *name, const char *title)
 Change the name and title of this histogram


void SetStats(Bool_t stats)
   -*-*-*-*-*-*-*Set statistics option on/off
                 ============================
  By default, the statistics box is drawn.
  The paint options can be selected via gStyle->SetOptStats.
  This function sets/resets the kNoStats bin in the histogram object.
  It has priority over the Style option.

void Sumw2()
   -*-*-*Create structure to store sum of squares of weights*-*-*-*-*-*-*-*
         ===================================================

     if histogram is already filled, the sum of squares of weights
     is filled with the existing bin contents

     The error per bin will be computed as sqrt(sum of squares of weight)
     for each bin.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

TF1* GetFunction(const char *name) const
   -*-*-*Return pointer to function with name*-*-*-*-*-*-*-*-*-*-*-*-*
         ===================================

 Functions such as TH1::Fit store the fitted function in the list of
 functions of this histogram.

Stat_t GetBinError(Int_t bin) const
   -*-*-*-*-*Return value of error associated to bin number bin*-*-*-*-*
             ==================================================

    if the sum of squares of weights has been defined (via Sumw2),
    this function returns the sqrt(sum of w2).
    otherwise it returns the sqrt(contents) for this bin.

   -*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Stat_t GetBinError(Int_t binx, Int_t biny) const
   -*-*-*-*-*Return error of bin number binx, biny
             =====================================
 NB: Function to be called for 2-d histograms only

Stat_t GetBinError(Int_t binx, Int_t biny, Int_t binz) const
   -*-*-*-*-*Return error of bin number binx,biny,binz
             =========================================
 NB: Function to be called for 3-d histograms only

Stat_t GetCellContent(Int_t binx, Int_t biny) const
   -*-*-*-*-*Return content of bin number binx, biny
             =====================================
 NB: Function to be called for 2-d histograms only

Stat_t GetCellError(Int_t binx, Int_t biny) const
   -*-*-*-*-*Return error of bin number binx, biny
             =====================================
 NB: Function to be called for 2-d histograms only

void SetBinError(Int_t bin, Stat_t error)

void SetBinContent(Int_t binx, Int_t biny, Stat_t content)

void SetBinContent(Int_t binx, Int_t biny, Int_t binz, Stat_t content)

void SetCellContent(Int_t binx, Int_t biny, Stat_t content)

void SetBinError(Int_t binx, Int_t biny, Stat_t error)

void SetBinError(Int_t binx, Int_t biny, Int_t binz, Stat_t error)

void SetCellError(Int_t binx, Int_t biny, Stat_t error)

void SetBinContent(Int_t, Stat_t)



Inline Functions


                  Int_t AxisChoice(Option_t* axis) const
                   void FillN(Int_t, const Axis_t*, const Axis_t*, const Double_t*, Int_t)
                  Int_t GetBufferLength() const
                  Int_t GetBufferSize() const
        const Double_t* GetBuffer() const
              Double_t* GetIntegral()
                 TList* GetListOfFunctions() const
                  Int_t GetNdivisions(Option_t* axis = "X") const
                Color_t GetAxisColor(Option_t* axis = "X") const
                Color_t GetLabelColor(Option_t* axis = "X") const
                Style_t GetLabelFont(Option_t* axis = "X") const
                Float_t GetLabelOffset(Option_t* axis = "X") const
                Float_t GetLabelSize(Option_t* axis = "X") const
                Float_t GetTitleOffset(Option_t* axis = "X") const
                Float_t GetTitleSize(Option_t* axis = "X") const
                Float_t GetTickLength(Option_t* axis = "X") const
                Float_t GetBarOffset() const
                Float_t GetBarWidth() const
                 Axis_t GetBinCenter(Int_t bin) const
                 Axis_t GetBinLowEdge(Int_t bin) const
                 Axis_t GetBinWidth(Int_t bin) const
                   void GetCenter(Axis_t* center) const
            TDirectory* GetDirectory() const
                  Int_t GetDimension() const
                   void GetLowEdge(Axis_t* edge) const
               Double_t GetMaximumStored() const
               Double_t GetMinimumStored() const
                  Int_t GetNbinsX() const
                  Int_t GetNbinsY() const
                  Int_t GetNbinsZ() const
               Double_t GetNormFactor() const
              Option_t* GetOption() const
                  Int_t GetSumw2N() const
                 Stat_t Integral(Int_t, Int_t, Int_t, Int_t, Option_t*) const
                 Stat_t Integral(Int_t, Int_t, Int_t, Int_t, Int_t, Int_t, Option_t*) const
                   void SetAxisColor(Color_t color = 1, Option_t* axis = "X")
                   void SetAxisRange(Axis_t xmin, Axis_t xmax, Option_t* axis = "X")
                   void SetBarOffset(Float_t offset = 0.25)
                   void SetBarWidth(Float_t width = 0.5)
                   void SetBinsLength(Int_t = -1)
                   void SetEntries(Stat_t n)
                   void SetLabelColor(Color_t color = 1, Option_t* axis = "X")
                   void SetLabelFont(Style_t font = 62, Option_t* axis = "X")
                   void SetLabelOffset(Float_t offset = 0.005, Option_t* axis = "X")
                   void SetLabelSize(Float_t size = 0.02, Option_t* axis = "X")
                   void SetNdivisions(Int_t n = 510, Option_t* axis = "X")
                   void SetNormFactor(Double_t factor = 1)
                   void SetOption(Option_t* option = " ")
                   void SetTickLength(Float_t length = 0.02, Option_t* axis = "X")
                   void SetTitleOffset(Float_t offset = 1, Option_t* axis = "X")
                   void SetTitleSize(Float_t size = 0.02, Option_t* axis = "X")
                   void SetXTitle(const char* title)
                   void SetYTitle(const char* title)
                   void SetZTitle(const char* title)
                TClass* Class()
                TClass* IsA() const
                   void ShowMembers(TMemberInspector& insp, char* parent)
                   void StreamerNVirtual(TBuffer& b)
                    TH1 TH1(const TH1&)


Author: Rene Brun 26/12/94
Last update: root/hist:$Name: $:$Id: TH1.cxx,v 1.126 2003/01/31 11:21:16 brun Exp $
Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *


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