TH1

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

    private:

      Int_t AxisChoice(Option_t* axis)
       void Build()
      Int_t FitOptionsMake(Option_t* option)

    protected:

      virtual void Copy(TObject& hnew)

    public:

                    TH1 TH1(const Text_t* name, const Text_t* title, Int_t nbinsx, Axis_t xlow, Axis_t xup)
                    TH1 TH1()
                    TH1 TH1(const Text_t* name, const Text_t* title, Int_t nbinsx, Axis_t* xbins)
                    TH1 TH1(TH1&)
           virtual void ~TH1()
           virtual void Add(TH1* h1, TH1* h2, Float_t c1 = 1, Float_t c2 = 1)
           virtual void Add(TH1* h1, Float_t c1 = 1)
           virtual void AddBinContent(Int_t bin)
           virtual void AddBinContent(Int_t bin, Stat_t w)
           virtual void Browse(TBrowser* b)
                TClass* Class()
       virtual Double_t ComputeIntegral()
          virtual Int_t DistancetoPrimitive(Int_t px, Int_t py)
           virtual void Divide(TH1* h1)
           virtual void Divide(TH1* h1, TH1* h2, Float_t c1 = 1, Float_t c2 = 1, Option_t* option)
           virtual void Draw(Option_t* option)
           virtual TH1* DrawCopy(Option_t* option)
           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, Axis_t y, Axis_t z, Stat_t w)
          virtual Int_t Fill(Axis_t x, Axis_t y, Stat_t w)
          virtual Int_t Fill(Axis_t x, Stat_t w)
          virtual Int_t Fill(Axis_t x)
          virtual Int_t Fill12(Axis_t x, Axis_t y)
           virtual void FillN(Int_t ntimes, Axis_t* x, Axis_t* y, Double_t* w, Int_t stride = 1)
           virtual void FillN(Int_t ntimes, Axis_t* x, Double_t* w, Int_t stride = 1)
                   void FillRandom(const char* fname, Int_t ntimes = 5000)
                   void FillRandom(TH1* h, Int_t ntimes = 5000)
          virtual Int_t FindBin(Axis_t x, Axis_t y = 0, Axis_t z = 0)
           virtual void Fit(const Text_t* formula, Option_t* option, Option_t* goption, Float_t xmin = 0, Float_t xmax = 0)
           virtual void FitPanel()
           virtual void FitSlicesX(TF1* f1 = 0, Int_t binmin = 1, Int_t binmax = 0, Int_t cut = 0, Option_t* option = QNR)
           virtual void FitSlicesY(TF1* f1 = 0, Int_t binmin = 1, Int_t binmax = 0, Int_t cut = 0, Option_t* option = QNR)
           virtual void FitSlicesZ(TF1* f1 = 0, Int_t binminx = 1, Int_t binmaxx = 0, Int_t binminy = 1, Int_t binmaxy = 0, Int_t cut = 0, Option_t* option = QNR)
        virtual Color_t GetAxisColor(Option_t* axis = X)
        virtual Float_t GetBarOffset()
        virtual Float_t GetBarWidth()
          virtual Int_t GetBin(Int_t binx, Int_t biny = 0, Int_t binz = 0)
         virtual Axis_t GetBinCenter(Int_t bin)
         virtual Stat_t GetBinContent(Int_t bin)
         virtual Stat_t GetBinError(Int_t bin)
         virtual Axis_t GetBinLowEdge(Int_t bin)
         virtual Axis_t GetBinWidth(Int_t bin)
         virtual Stat_t GetCellContent(Int_t binx, Int_t biny)
         virtual Stat_t GetCellError(Int_t binx, Int_t biny)
           virtual void GetCenter(Axis_t* center)
          virtual Int_t GetContour(Float_t* levels = 0)
        virtual Float_t GetContourLevel(Int_t level)
          virtual Int_t GetDimension() const
            TDirectory* GetDirectory()
         virtual Stat_t GetEntries()
           virtual TF1* GetFunction(const Text_t* name)
      virtual Double_t* GetIntegral()
        virtual Color_t GetLabelColor(Option_t* axis = X)
        virtual Style_t GetLabelFont(Option_t* axis = X)
        virtual Float_t GetLabelOffset(Option_t* axis = X)
        virtual Float_t GetLabelSize(Option_t* axis = X)
                 TList* GetListOfFunctions()
           virtual void GetLowEdge(Axis_t* edge)
        virtual Float_t GetMaximum()
        virtual Float_t GetMaximumStored()
         virtual Stat_t GetMean(Int_t axis = 1)
        virtual Float_t GetMinimum()
        virtual Float_t GetMinimumStored()
          virtual Int_t GetNbinsX() const
          virtual Int_t GetNbinsY() const
          virtual Int_t GetNbinsZ() const
          virtual Int_t GetNdivisions(Option_t* axis = X)
        virtual Float_t GetNormFactor()
        virtual Text_t* GetObjectInfo(Int_t px, Int_t py)
      virtual Option_t* GetOption() const
         virtual Axis_t GetRandom()
           virtual void GetRandom2(Axis_t& x, Axis_t& y)
           virtual void GetRandom3(Axis_t& x, Axis_t& y, Axis_t& z)
         virtual Stat_t GetRMS(Int_t axis = 1)
           virtual void GetStats(Stat_t* stats)
         virtual Stat_t GetSumOfWeights()
          virtual Int_t GetSumw2N()
        virtual Float_t GetTickLength(Option_t* axis = X)
        virtual Float_t GetTitleOffset(Option_t* axis = X)
         virtual TAxis* GetXaxis()
         virtual TAxis* GetYaxis()
         virtual TAxis* GetZaxis()
         virtual Stat_t Integral(Int_t binx1, Int_t binx2, Int_t biny1, Int_t biny2)
         virtual Stat_t Integral(Int_t binx1, Int_t binx2, Int_t biny1, Int_t biny2, Int_t binz1, Int_t binz2)
         virtual Stat_t Integral()
         virtual Stat_t Integral(Int_t binx1, Int_t binx2)
        virtual TClass* IsA() const
           virtual void Multiply(TH1* h1)
           virtual void Multiply(TH1* h1, TH1* h2, Float_t c1 = 1, Float_t c2 = 1, Option_t* option)
           virtual void Paint(Option_t* option)
           virtual void Print(Option_t* option)
              TProfile* ProfileX(const char* name = _pfx, Int_t firstybin = 0, Int_t lastybin = 9999, Option_t* option)
              TProfile* ProfileY(const char* name = _pfy, Int_t firstxbin = 0, Int_t lastxbin = 9999, Option_t* option)
                   TH1* Project3D(Option_t* option = x)
                  TH1D* ProjectionX(const char* name = _px, Int_t firstybin = 0, Int_t lastybin = 9999, Option_t* option)
                  TH1D* ProjectionY(const char* name = _py, Int_t firstxbin = 0, Int_t lastxbin = 9999, Option_t* option)
                  TH1D* ProjectionZ(const char* name = _pz, Int_t firstxbin = 0, Int_t lastxbin = 9999, Int_t firstybin = 0, Int_t lastybin = 9999, Option_t* option)
                   TH1* Rebin(Int_t ngroup = 2, const char* newname)
           virtual void Reset(Option_t* option)
           virtual void SavePrimitive(ofstream& out, Option_t* option)
           virtual void Scale(Float_t c1 = 1)
           virtual void SetAxisColor(Color_t color = 1, Option_t* axis = X)
           virtual void SetAxisRange(Float_t xmin, Float_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 SetBinError(Int_t bin, Stat_t error)
           virtual void SetBins(Int_t nx, Float_t xmin, Float_t xmax, Int_t ny, Float_t ymin, Float_t ymax)
           virtual void SetBins(Int_t nx, Float_t xmin, Float_t xmax)
           virtual void SetBins(Int_t nx, Float_t xmin, Float_t xmax, Int_t ny, Float_t ymin, Float_t ymax, Int_t nz, Float_t zmin, Float_t zmax)
           virtual void SetBinsLength(Int_t)
           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(Stat_t* content)
           virtual void SetContour(Int_t nlevels, Float_t* levels = 0)
           virtual void SetContourLevel(Int_t level, Float_t value)
           virtual void SetDirectory(TDirectory* dir)
           virtual void SetEntries(Stat_t n)
           virtual void SetError(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(Float_t maximum = -1111)
           virtual void SetMinimum(Float_t minimum = -1111)
           virtual void SetName(const Text_t* name)
           virtual void SetNdivisions(Int_t n = 510, Option_t* axis = X)
           virtual void SetNormFactor(Float_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 SetXTitle(Text_t* title)
           virtual void SetYTitle(Text_t* title)
           virtual void SetZTitle(Text_t* title)
           virtual void ShowMembers(TMemberInspector& insp, char* parent)
           virtual void Smooth(Int_t ntimes = 1)
                   void SmoothArray(Int_t NN, Double_t* XX, Int_t ntimes = 1)
               Double_t SmoothMedian(Int_t n, Double_t* a)
           virtual void Streamer(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
                   Float_t fMaximum     Maximum value for plotting
                   Float_t fMinimum     Minimum value for plotting
                   Float_t fNormFactor  Normalization factor
                   TArrayF 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)
               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

See also

TH1C, TH1D, TH1F, TH1S

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 class TProfile
*-*
*-*- All histogram classes are derived from the base class TH1
*-*   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.
*-*
*-*   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
*-*

/*

*/

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

*-*-*-*-*-*-*-*-*-*-*Histogram default constructor*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  =============================

*-*-*-*-*-*-*-*-*-*-*Histogram default destructor*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ============================

*-*-*-*-*-*-*-*-*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);

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

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

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

*-*-*-*-*-*-*-*-*-*Creates histogram basic data structure*-*-*-*-*-*-*-*-*-*
*-*                ======================================

 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.

*-*-*-*-*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.

*-*-*-*-*-*-*-*-*-*Increment bin content by 1*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                ==========================

*-*-*-*-*-*-*-*-*-*Increment bin content by a weight w*-*-*-*-*-*-*-*-*-*-*
*-*                ===================================

  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

*-*-*-*-*-*-*Copy this histogram structure to newth1*-*-*-*-*-*-*-*-*-*-*-*
*-*          =======================================

*-*-*-*-*-*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*-*-*-*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.

*-*-*-*-*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.

*-*-*-*-*-*-*-*-*-*-*Draw this histogram with options*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ================================
*-*
*-*  This histogram is added in the list of objects to be drawn in the
*-*  current pad.
*-*  It is important to note that only a reference to this histogram is added.
*-*  This means that if the histogram contents change between pad redraws,
*-*  the current histogram contents will be shown.
*-*  Use function DrawCopy to force a copy of the histogram at the time
*-*  of the Draw operation in the Pad list.
*-*
*-*  The following options are supported on all types:
*-*    "SAME"   : Superimpose on previous picture in the same pad
*-*    "CYL"    : Use Cylindrical coordinates
*-*    "POL"    : Use Polar coordinates
*-*    "SPH"    : Use Spherical coordinates
*-*    "PSR"    : Use PseudoRapidity/Phi coordinates
*-*    "LEGO"   : Draw a lego plot with hidden line removal
*-*    "LEGO1"  : Draw a lego plot with hidden surface removal
*-*    "LEGO2"  : Draw a lego plot using colors to show the cell contents
*-*    "SURF"   : Draw a surface plot with hidden line removal
*-*    "SURF1"  : Draw a surface plot with hidden surface removal
*-*    "SURF2"  : Draw a surface plot using colors to show the cell contents
*-*    "SURF3"  : same as SURF with in addition a contour view drawn on the top
*-*    "SURF4"  : Draw a surface using Gouraud shading
*-*
*-*  The following options are supported for 1-D types:
*-*    "AH"     : Draw histogram, but not the axis labels and tick marks
*-*    "B"      : Bar chart option
*-*    "C"      : Draw a smooth Curve througth the histogram bins
*-*    "E"      : Draw error bars
*-*    "E0"     : Draw error bars including bins with o contents
*-*    "E1"     : Draw error bars with perpendicular lines at the edges
*-*    "E2"     : Draw error bars with rectangles
*-*    "E3"     : Draw a fill area througth the end points of the vertical error bars
*-*    "E4"     : Draw a smoothed filled area through the end points of the error bars
*-*    "L"      : Draw a line througth the bin contents
*-*    "P"      : Draw current marker at each bin
*-*    "*H"     : Draw histogram with a * at each bin
*-*
*-*
*-*  The following options are supported for 2-D types:
*-*    "ARR"    : arrow mode. Shows gradient between adjacent cells
*-*    "BOX"    : a box is drawn for each cell with surface proportional to contents
*-*    "COL"    : a box is drawn for each cell with a color scale varying with contents
*-*    "COLZ"   : same as "COL". In addition the color mapping is also drawn
*-*    "CONT"   : Draw a contour plot (same as CONT0)
*-*    "CONT0"  : Draw a contour plot using colors to distinguish contours
*-*    "CONT1"  : Draw a contour plot using line styles to distinguish contours
*-*    "CONT2"  : Draw a contour plot using the same line style for all contours
*-*    "CONT3"  : Draw a contour plot using fill area colors
*-*    "FB"     : With LEGO or SURFACE, suppress the Front-Box
*-*    "BB"     : With LEGO or SURFACE, suppress the Back-Box
*-*    "SCAT"   : Draw a scatter-plot (default)
*-*
*-*  Note that most options above can be concatenated, example:
*-*  h-Draw("e1same");
*-*  Options are case insensitive
*-*
*-*  When using the options "BOX", "COL" or "COLZ", the color palette used
*-*  is the one defined in the current style (see TStyle::SetPalette)
*-*
*-*  When using the "CONT" or "SURF" or "LEGO" options, the number
*-*  of contour levels can be changed via TH1::SetContour.
*-*  (default is 20 equidistant levels)
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

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

*-*-*-*-*-*-*Display a panel with all histogram drawing options*-*-*-*-*-*
*-*          ==================================================
*-*
*-*   See class TDrawPanelHist for example

*-*-*-*-*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 an integer value, distributed according to the Poisson
*-*  distribution, with f1 as the mean.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

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

*-*-*-*-*-*-*-*-*-*-*Increment cell defined by x,y by 1*-*-*-*-*-*-*-*-*-*
*-*                  ==================================
*-*
*-* if x or/and y is less than the low-edge of the corresponding axis first bin,
*-*   the Underflow cell is incremented.
*-* if x or/and y is greater than the upper edge of corresponding axis last bin,
*-*   the Overflow cell 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 1in the cell corresponding to x,y.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*-*-*-*Increment cell defined by x,y by a weight w*-*-*-*-*-*
*-*                  ===========================================
*-*
*-* if x or/and y is less than the low-edge of the corresponding axis first bin,
*-*   the Underflow cell is incremented.
*-* if x or/and y is greater than the upper edge of corresponding axis last bin,
*-*   the Overflow cell 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 cell corresponding to x,y.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*-*-*-*Increment cell defined by x,y,z by a weight 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^2 in the cell corresponding to x,y,z.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*Fill a 2-D histogram with an array of values and weights*-*-*-*
*-*          ========================================================
*-*
*-* ntimes:  number of entries in arrays x and w (array size must be ntimes*stride)
*-* x:       array of x values to be histogrammed
*-* y:       array of y values to be histogrammed
*-* w:       array of weights
*-* stride:  step size through arrays x, y 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 cell corresponding to x[i],y[i].
*-* if w is NULL each entry is assumed a weight=1
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

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

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

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

*-*-*-*-*-*-*-*-*-*-*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.
*-*
*-*   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
*-*             = "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");
*-*
*-*   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-6,0.1,-8,100);
*-*     func->SetParLimits(4,-10,-4);
*-*     func->SetParLimits(5, 1,1);
*-*   With this setup, parameters 0->3 can vary freely
*-*   Parameter 4 has boundaries [-10,-4] with initial value -8
*-*   Parameter 5 is fixed to 100.
*-*
*-*   Note that option "I" gives better results but is slower.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*Display a panel with all histogram fit options*-*-*-*-*-*
*-*          ==============================================
*-*
*-*   See class TFitPanel for example

 Project slices along X in case of a 2-D histogram, then fit each slice
 with function f1 and make a histogram for each fit parameter
 Only bins along Y between binmin and binmax are considered.
 if f1=0, a gaussian is assumed
 Before invoking this function, one can set a subrange to be fitted along X
 via f1->SetRange(xmin,xmax)
 The argument option (default="QNR") can be used to change the fit options.
     "Q" means Quiet mode
     "N" means do not show the result of the fit
     "R" means fit the function in the specified function range

 Note that the generated histograms are added to the list of objects
 in the current directory. It is the user's responsability to delete
 these histograms.

  Example: Assume a 2-d histogram h2
   Root > h2->FitSlicesX(); produces 4 TH1D histograms
          with h2_0 containing parameter 0(Constant) for a Gaus fit
                    of each bin in Y projected along X
          with h2_1 containing parameter 1(Mean) for a gaus fit
          with h2_2 containing parameter 2(RMS)  for a gaus fit
          with h2_chi2 containing the chisquare/number of degrees of freedom for a gaus fit

   Root > h2->FitSlicesX(0,15,22,10);
          same as above, but only for bins 15 to 22 along Y
          and only for bins in Y for which the corresponding projection
          along X has more than cut bins filled.

 Project slices along Y in case of a 2-D histogram, then fit each slice
 with function f1 and make a histogram for each fit parameter
 Only bins along X between binmin and binmax are considered.
 if f1=0, a gaussian is assumed
 Before invoking this function, one can set a subrange to be fitted along Y
 via f1->SetRange(ymin,ymax)
 The argument option (default="QNR") can be used to change the fit options.
     "Q" means Quiet mode
     "N" means do not show the result of the fit
     "R" means fit the function in the specified function range

 Note that the generated histograms are added to the list of objects
 in the current directory. It is the user's responsability to delete
 these histograms.

  Example: Assume a 2-d histogram h2
   Root > h2->FitSlicesY(); produces 4 TH1D histograms
          with h2_0 containing parameter 0(Constant) for a Gaus fit
                    of each bin in X projected along Y
          with h2_1 containing parameter 1(Mean) for a gaus fit
          with h2_2 containing parameter 2(RMS)  for a gaus fit
          with h2_chi2 containing the chisquare/number of degrees of freedom for a gaus fit

   Root > h2->FitSlicesY(0,15,22,10);
          same as above, but only for bins 15 to 22 along X
          and only for bins in X for which the corresponding projection
          along Y has more than cut bins filled.

 A complete example of this function is given in  tutorial:fitslicesy.C 
 with the following output:

/*

*/

 Project slices along Z in case of a 3-D histogram, then fit each slice
 with function f1 and make a 2-d histogram for each fit parameter
 Only cells in the bin range [binminx,binmaxx] and [binminy,binmaxy] are considered.
 if f1=0, a gaussian is assumed
 Before invoking this function, one can set a subrange to be fitted along Z
 via f1->SetRange(zmin,zmax)
 The argument option (default="QNR") can be used to change the fit options.
     "Q" means Quiet mode
     "N" means do not show the result of the fit
     "R" means fit the function in the specified function range


  Example: Assume a 3-d histogram h3
   Root > h3->FitSlicesZ(); produces 4 TH2D histograms
          with h3_0 containing parameter 0(Constant) for a Gaus fit
                    of each cell in X,Y projected along Z
          with h3_1 containing parameter 1(Mean) for a gaus fit
          with h3_2 containing parameter 2(RMS)  for a gaus fit
          with h3_chi2 containing the chisquare/number of degrees of freedom for a gaus fit

   Root > h3->Fit(0,15,22,0,0,10);
          same as above, but only for bins 15 to 22 along X
          and only for cells in X,Y for which the corresponding projection
          along Z has more than cut bins filled.

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

*-*-*-*-*-*-*-*-*Decode string choptin and fill Foption structure*-*-*-*-*-*
*-*              ================================================

*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

 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.

 return 2 random numbers along axis x and y distributed according
 the cellcontents of a 2-dim histogram

 return 3 random numbers along axis x , y and z distributed according
 the cellcontents of a 3-dim histogram

*-*-*-*-*-*-*Return content of global bin number bin*-*-*-*-*-*-*-*-*-*-*-*
*-*          =======================================

*-*-*-*-*-*-*-*-*-*-*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.

*-*-*-*-*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.

*-*-*-*-*-*-*-*-*Control routine to paint any kind of histograms*-*-*-*-*-*-*
*-*              ===============================================

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

*-*-*-*-*Project a 2-D histogram into a profile histogram along X*-*-*-*-*-*
*-*      ========================================================

   The projection is made from the channels along the Y axis
   ranging from firstybin to lastybin included.

*-*-*-*-*Project a 2-D histogram into a profile histogram along Y*-*-*-*-*-*
*-*      ========================================================

   The projection is made from the channels along the X axis
   ranging from firstxbin to lastxbin included.

*-*-*-*-*Project a 2-D histogram into a 1-D histogram along X*-*-*-*-*-*-*
*-*      ====================================================

   The projection is always of the type TH1D.
   The projection is made from the channels along the Y axis
   ranging from firstybin to lastybin included.

   if option "E" is specified, the errors are computed.

*-*-*-*-*Project a 2-D histogram into a 1-D histogram along Y*-*-*-*-*-*-*
*-*      ====================================================

   The projection is always of the type TH1D.
   The projection is made from the channels along the X axis
   ranging from firstxbin to lastxbin included.

   if option "E" is specified, the errors are computed.

*-*-*-*-*Project a 3-D histogram into a 1-D histogram along Z*-*-*-*-*-*-*
*-*      ====================================================

   The projection is always of the type TH1D.
   The projection is made from the cells along the X axis
   ranging from ixmin to ixmax and iymin to iymax included.

   if option "E" is specified, the errors are computed.

   code from Paola Collins & Hans Dijkstra

 Project a 3-d histogram into 1 or 2-d histograms depending on the
 option parameter
 option may contain a combination of the characters x,y,z,e
 option = "x" return the x projection into a TH1D histogram
 option = "y" return the y projection into a TH1D histogram
 option = "z" return the z projection into a TH1D histogram
 option = "xy" return the x versus y projection into a TH2D histogram
 option = "yx" return the y versus x projection into a TH2D histogram
 option = "xz" return the x versus z projection into a TH2D histogram
 option = "zx" return the z versus x projection into a TH2D histogram
 option = "yz" return the y versus z projection into a TH2D histogram
 option = "zy" return the z versus y projection into a TH2D histogram

 If option contains the string "e", errors are computed

 The projection is made for the selected bins only

*-*-*-*-*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
   NOTE: This function is currently implemented only for 1-D histograms

*-*-*-*-*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

 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.

 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.

 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

*-*-*-*-*-*-*-*-*Stream a class object*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*              =====================

*-*-*-*-*-*-*Print some global quantities for this histogram*-*-*-*-*-*-*-*
*-*          ===============================================

  If option "all" is given, bin contents and errors are also printed.

*-*-*-*-*-*-*-*Reset this histogram: contents, errors, etc*-*-*-*-*-*-*-*
*-*            ===========================================

 Save primitive as a C++ statement(s) on output stream out

*-*-*-*-*-*Replace current attributes by current style*-*-*-*-*
*-*        ===========================================

*-*-*-*-*-*-*-*Return mean value of this histogram along the X axis*-*-*-*-*
*-*            ====================================================

*-*-*-*-*-*-*-*Return the Root Mean Square value of this histogram*-*-*-*-*
*-*            ===================================================

 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
 stats[4] = sumwy   if 2-d or 3-d
 stats[5] = sumwy2
 stats[6] = sumwz   if 3-d
 stats[7] = sumwz2

 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.

*-*-*-*-*-*-*-*Return the sum of weights excluding under/overflows*-*-*-*-*
*-*            ===================================================

Return integral of bin contents. Only bins in the bins range are considered.

Return integral of bin contents between binx1 and binx2 for a 1-D histogram

Return integral of bin contents in range [binx1,binx2],[biny1,biny2]
 for a 2-D histogram

Return integral of bin contents in range [binx1,binx2],[biny1,biny2],[binz1,binz2]
 for a 3-D histogram

*-*-*-*-*-*-*-*Replace bin contents by the contents of array content*-*-*-*
*-*            =====================================================

*-*-*-*-*-*-*-*Return contour values into array levels*-*-*-*-*-*-*-*-*-*
*-*            =======================================
*-*
*-*  The number of contour levels can be returned by getContourLevel
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

*-*-*-*-*-*-*-*Return the number of contour 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

*-*-*-*-*-*-*-*-*-*-*Set value for one contour level*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ===============================

*-*-*-*-*-*-*-*-*-*-*Return maximum value of all bins*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ================================

*-*-*-*-*-*-*-*-*-*-*Return minimum value of all bins*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ================================

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

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

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

*-*-*-*-*-*-*-*-*Set the maximum value for the Y axis*-*-*-*-*-*-*-*-*-*-*-*
*-*              ====================================
 By default the maximum value is automatically set to the maximum
 bin content plyus a margin of 10 per cent.

*-*-*-*-*-*-*-*-*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.

 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.

*-*-*-*-*-*-*-*-*Replace bin errors by values in array error*-*-*-*-*-*-*-*-*
*-*              ===========================================

*-*-*-*-*-*-*-*-*-*-*Change the name of this histogram*-*-*-*-*-*-*-*-*-*-*
*-*                  =================================

*-*-*-*-*-*-*-*-*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.

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

*-*-*-*-*Return pointer to function with name*-*-*-*-*-*-*-*-*-*-*-*-*
*-*      ===================================

*-*-*-*-*-*-*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.
*-*
*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*

Inline Functions

              Int_t AxisChoice(Option_t* axis)
          Double_t* GetIntegral()
             TList* GetListOfFunctions()
              Int_t GetNdivisions(Option_t* axis = X)
            Color_t GetAxisColor(Option_t* axis = X)
            Color_t GetLabelColor(Option_t* axis = X)
            Style_t GetLabelFont(Option_t* axis = X)
            Float_t GetLabelOffset(Option_t* axis = X)
            Float_t GetLabelSize(Option_t* axis = X)
            Float_t GetTitleOffset(Option_t* axis = X)
            Float_t GetTickLength(Option_t* axis = X)
            Float_t GetBarOffset()
            Float_t GetBarWidth()
             Axis_t GetBinCenter(Int_t bin)
             Axis_t GetBinLowEdge(Int_t bin)
             Axis_t GetBinWidth(Int_t bin)
               void GetCenter(Axis_t* center)
        TDirectory* GetDirectory()
             Stat_t GetEntries()
              Int_t GetDimension() const
               void GetLowEdge(Axis_t* edge)
            Float_t GetMaximumStored()
            Float_t GetMinimumStored()
              Int_t GetNbinsX() const
              Int_t GetNbinsY() const
              Int_t GetNbinsZ() const
            Float_t GetNormFactor()
          Option_t* GetOption() const
              Int_t GetSumw2N()
             TAxis* GetXaxis()
             TAxis* GetYaxis()
             TAxis* GetZaxis()
               void SetAxisColor(Color_t color = 1, Option_t* axis = X)
               void SetAxisRange(Float_t xmin, Float_t xmax, Option_t* axis = X)
               void SetBarOffset(Float_t offset = 0.25)
               void SetBarWidth(Float_t width = 0.5)
               void SetBinsLength(Int_t)
               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(Float_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 SetXTitle(Text_t* title)
               void SetYTitle(Text_t* title)
               void SetZTitle(Text_t* title)
            TClass* Class()
            TClass* IsA() const
               void ShowMembers(TMemberInspector& insp, char* parent)
                TH1 TH1(TH1&)