TTreePlayer

class TTreePlayer : public TVirtualTreePlayer

    protected:

       const char* GetNameByIndex(TString& varexp, Int_t* index, Int_t colindex) const
      virtual void MakeIndex(TString& varexp, Int_t* index)
              void TakeAction(Int_t nfill, Int_t& npoints, Int_t& action, TObject* obj, Option_t* option)
              void TakeEstimate(Int_t nfill, Int_t& npoints, Int_t action, TObject* obj, Option_t* option)

    public:

                TTreePlayer TTreePlayer()
                TTreePlayer TTreePlayer(const TTreePlayer&)
               virtual void ~TTreePlayer()
             static TClass* Class()
               virtual void ClearFormula()
               virtual void CompileVariables(const char* varexp, const char* selection)
             virtual TTree* CopyTree(const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
               virtual void CreatePacketGenerator(Int_t nentries, Stat_t firstEntry)
              virtual Int_t DrawSelect(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
               virtual void EntryLoop(Int_t& action, TObject* obj, Int_t nentries = 1000000000, Int_t firstentry = 0, Option_t* option)
              virtual Int_t Fit(const char* formula, const char* varexp, const char* selection, Option_t* option, Option_t* goption, Int_t nentries, Int_t firstentry)
              virtual Int_t GetDimension() const
               virtual TH1* GetHistogram() const
              virtual Int_t GetMultiplicity() const
               virtual void GetNextPacket(TSlave* sl, Int_t& nentries, Stat_t& firstentry, Stat_t& processed)
              virtual Int_t GetNfill() const
          TPacketGenerator* GetPacketGenerator() const
              virtual Int_t GetPacketSize() const
                const char* GetScanFileName() const
      virtual TTreeFormula* GetSelect() const
              virtual Int_t GetSelectedRows() const
          virtual Double_t* GetV1() const
          virtual Double_t* GetV2() const
          virtual Double_t* GetV3() const
      virtual TTreeFormula* GetVar1() const
      virtual TTreeFormula* GetVar2() const
      virtual TTreeFormula* GetVar3() const
      virtual TTreeFormula* GetVar4() const
          virtual Double_t* GetW() const
            virtual TClass* IsA() const
               virtual void Loop(Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
              virtual Int_t MakeClass(const char* classname = "0", Option_t* option)
              virtual Int_t MakeCode(const char* filename = "0")
        virtual TPrincipal* Principal(const char* varexp, const char* selection, Option_t* option = "np", Int_t nentries = 1000000000, Int_t firstentry = 0)
              virtual Int_t Process(const char* filename, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
              virtual Int_t Process(TSelector* selector, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
        virtual TSQLResult* Query(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
              virtual Int_t Scan(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
                     Bool_t ScanRedirected()
               virtual void SetEstimate(Int_t n)
               virtual void SetPacketSize(Int_t size = 100)
                       void SetScanFileName(const char* name)
                       void SetScanRedirect(Bool_t on = kFALSE)
               virtual void SetTree(TTree* t)
               virtual void ShowMembers(TMemberInspector& insp, char* parent)
               virtual void StartViewer(Int_t ww, Int_t wh)
               virtual void Streamer(TBuffer& b)
                       void StreamerNVirtual(TBuffer& b)
              virtual Int_t UnbinnedFit(const char* formula, const char* varexp, const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
               virtual void UpdateFormulaLeaves()

Data Members

    protected:

                    TTree* fTree          Pointer to current Tree
             TTreeFormula* fVar1          Pointer to first variable formula
             TTreeFormula* fVar2          Pointer to second variable formula
             TTreeFormula* fVar3          Pointer to third variable formula
             TTreeFormula* fVar4          Pointer to fourth variable formula
             TTreeFormula* fSelect        Pointer to selection formula
      TTreeFormulaManager* fManager       Pointer to the formula manager
                    Bool_t fScanRedirect  Switch to redirect TTree::Scan output to a file
               const char* fScanFileName  Name of the file where Scan is redirected
                     Int_t fDraw          ! Last entry loop number when object was drawn
                     Int_t fNfill         ! Local for EntryLoop
                     Int_t fMultiplicity  Indicator of the variability of the size of entries
                     Int_t fDimension     Dimension of the current expression
                     Int_t fSelectedRows  Number of selected entries
                     Int_t fPacketSize    Number of entries in one packet for parallel root
                     Int_t fNbins[4]      Number of bins per dimension
                  Double_t fVmin[4]       Minima of varexp columns
                  Double_t fVmax[4]       Maxima of varexp columns
                 Double_t* fV1            [fSelectedRows]Local buffer for variable 1
                 Double_t* fV2            [fSelectedRows]Local buffer for variable 2
                 Double_t* fV3            [fSelectedRows]Local buffer for variable 3
                 Double_t* fW             [fSelectedRows]Local buffer for weights
         TPacketGenerator* fPacketGen     ! Packet generator
                      TH1* fHistogram     ! Pointer to histogram used for the projection

Class Description

                                                                      
 TTree                                                                
                                                                      
  a TTree object has a header with a name and a title.
  It consists of a list of independent branches (TBranch). Each branch
  has its own definition and list of buffers. Branch buffers may be
  automatically written to disk or kept in memory until the Tree attribute
  fMaxVirtualSize is reached.
  Variables of one branch are written to the same buffer.
  A branch buffer is automatically compressed if the file compression
  attribute is set (default).

  Branches may be written to different files (see TBranch::SetFile).

  The ROOT user can decide to make one single branch and serialize one
  object into one single I/O buffer or to make several branches.
  Making one single branch and one single buffer can be the right choice
  when one wants to process only a subset of all entries in the tree.
  (you know for example the list of entry numbers you want to process).
  Making several branches is particularly interesting in the data analysis
  phase, when one wants to histogram some attributes of an object (entry)
  without reading all the attributes.

/*

*/


  ==> TTree *tree = new TTree(name, title, maxvirtualsize)
     Creates a Tree with name and title. Maxvirtualsize is by default 64Mbytes,
     maxvirtualsize = 64000000(default) means: Keeps as many buffers in memory until
     the sum of all buffers is greater than 64 Megabyte. When this happens,
     memory buffers are written to disk and deleted until the size of all
     buffers is again below the threshold.
     maxvirtualsize = 0 means: keep only one buffer in memory.

     Various kinds of branches can be added to a tree:
       A - simple structures or list of variables. (may be for C or Fortran structures)
       B - any object (inheriting from TObject). (we expect this option be the most frequent)
       C - a ClonesArray. (a specialized object for collections of same class objects)

  ==> Case A
      ======
     TBranch *branch = tree->Branch(branchname,address, leaflist, bufsize)
       * address is the address of the first item of a structure
       * leaflist is the concatenation of all the variable names and types
         separated by a colon character :
         The variable name and the variable type are separated by a slash (/).
         The variable type may be 0,1 or 2 characters. If no type is given,
         the type of the variable is assumed to be the same as the previous
         variable. If the first variable does not have a type, it is assumed
         of type F by default. The list of currently supported types is given below:
            - C : a character string terminated by the 0 character
            - B : an 8 bit signed integer (Char_t)
            - b : an 8 bit unsigned integer (UChar_t)
            - S : a 16 bit signed integer (Short_t)
            - s : a 16 bit unsigned integer (UShort_t)
            - I : a 32 bit signed integer (Int_t)
            - i : a 32 bit unsigned integer (UInt_t)
            - F : a 32 bit floating point (Float_t)
            - D : a 64 bit floating point (Double_t)

  ==> Case B
      ======
     TBranch *branch = tree->Branch(branchname,className,object, bufsize, splitlevel)
          object is the address of a pointer to an existing object (derived from TObject).
        if splitlevel=1 (default), this branch will automatically be split
          into subbranches, with one subbranch for each data member or object
          of the object itself. In case the object member is a TClonesArray,
          the mechanism described in case C is applied to this array.
        if splitlevel=0, the object is serialized in the branch buffer.

  ==> Case C
      ======
     TBranch *branch = tree->Branch(branchname,clonesarray, bufsize, splitlevel)
         clonesarray is the address of a pointer to a TClonesArray.
         The TClonesArray is a direct access list of objects of the same class.
         For example, if the TClonesArray is an array of TTrack objects,
         this function will create one subbranch for each data member of
         the object TTrack.


  ==> branch->SetAddress(Void *address)
      In case of dynamic structures changing with each entry for example, one must
      redefine the branch address before filling the branch again.
      This is done via the TBranch::SetAddress member function.

  ==> tree->Fill()
      loops on all defined branches and for each branch invokes the Fill function.

         See also the class TNtuple (a simple Tree with only one branch)

/*

*/

  =============================================================================
______________________________________________________________________________
*-*-*-*-*-*-*A simple example with histograms and a tree*-*-*-*-*-*-*-*-*-*
*-*          ===========================================

  This program creates :
    - a one dimensional histogram
    - a two dimensional histogram
    - a profile histogram
    - a tree

  These objects are filled with some random numbers and saved on a file.

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

 #include "TFile.h"
 #include "TH1.h"
 #include "TH2.h"
 #include "TProfile.h"
 #include "TRandom.h"
 #include "TTree.h"


 //______________________________________________________________________________
 main(int argc, char **argv)
 {
 // Create a new ROOT binary machine independent file.
 // Note that this file may contain any kind of ROOT objects, histograms,trees
 // pictures, graphics objects, detector geometries, tracks, events, etc..
 // This file is now becoming the current directory.
   TFile hfile("htree.root","RECREATE","Demo ROOT file with histograms & trees");

 // Create some histograms and a profile histogram
   TH1F *hpx   = new TH1F("hpx","This is the px distribution",100,-4,4);
   TH2F *hpxpy = new TH2F("hpxpy","py ps px",40,-4,4,40,-4,4);
   TProfile *hprof = new TProfile("hprof","Profile of pz versus px",100,-4,4,0,20);

 // Define some simple structures
   typedef struct {Float_t x,y,z;} POINT;
   typedef struct {
      Int_t ntrack,nseg,nvertex;
      UInt_t flag;
      Float_t temperature;
   } EVENTN;
   static POINT point;
   static EVENTN eventn;

 // Create a ROOT Tree
   TTree *tree = new TTree("T","An example of ROOT tree with a few branches");
   tree->Branch("point",&point,"x:y:z");
   tree->Branch("eventn",&eventn,"ntrack/I:nseg:nvertex:flag/i:temperature/F");
   tree->Branch("hpx","TH1F",&hpx,128000,0);

   Float_t px,py,pz;
   static Float_t p[3];

 //--------------------Here we start a loop on 1000 events
   for ( Int_t i=0; i<1000; i++) {
      gRandom->Rannor(px,py);
      pz = px*px + py*py;
      Float_t random = gRandom->::Rndm(1);

 //         Fill histograms
      hpx->Fill(px);
      hpxpy->Fill(px,py,1);
      hprof->Fill(px,pz,1);

 //         Fill structures
      p[0] = px;
      p[1] = py;
      p[2] = pz;
      point.x = 10*(random-1);;
      point.y = 5*random;
      point.z = 20*random;
      eventn.ntrack  = Int_t(100*random);
      eventn.nseg    = Int_t(2*eventn.ntrack);
      eventn.nvertex = 1;
      eventn.flag    = Int_t(random+0.5);
      eventn.temperature = 20+random;

 //        Fill the tree. For each event, save the 2 structures and 3 objects
 //      In this simple example, the objects hpx, hprof and hpxpy are slightly
 //      different from event to event. We expect a big compression factor!
      tree->Fill();
   }
  //--------------End of the loop

   tree->Print();

 // Save all objects in this file
   hfile.Write();

 // Close the file. Note that this is automatically done when you leave
 // the application.
   hfile.Close();

   return 0;
 }
                                                                      

*-*-*-*-*-*-*-*-*-*-*Default Tree constructor*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ========================

*-*-*-*-*-*-*-*-*-*-*Tree destructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  =================

*-*-*-*-*-*-*Delete internal buffers*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*          =======================

*-*-*-*-*-*-*Compile input variables and selection expression*-*-*-*-*-*
*-*          ================================================

  varexp is an expression of the general form e1:e2:e3
    where e1,etc is a formula referencing a combination of the columns
  Example:
     varexp = x     simplest case: draw a 1-Dim distribution of column named x
            = sqrt(x)            : draw distribution of sqrt(x)
            = x*y/z
            = y:sqrt(x) 2-Dim dsitribution of y versus sqrt(x)

  selection is an expression with a combination of the columns
  Example:
      selection = "x<y && sqrt(z)>3.2"
       in a selection all the C++ operators are authorized

 copy a Tree with selection
 make a clone of this Tree header.
 then copy the selected entries

 selection is a standard selection expression (see TTreePlayer::Draw)
 option is reserved for possible future use
 nentries is the number of entries to process (default is all)
 first is the first entry to process (default is 0)

 Note that the branch addresses must be correctly set before calling this function
 The following example illustrates how to copy some events from the Tree
 generated in $ROOTSYS/test/Event

   gSystem->Load("libEvent");
   TFile f("Event.root");
   TTree *T = (TTree*)f.Get("T");
   Event *event = new Event();
   T->SetBranchAddress("event",&event);
   TFile f2("Event2.root","recreate");
   TTree *T2 = T->CopyTree("fNtrack<595");
   T2->Write();

 Create or reset the packet generator.

*-*-*-*-*-*-*-*-*-*-*Draw expression varexp for specified entries-*-*-*-*-*
*-*                  ===========================================

  varexp is an expression of the general form e1:e2:e3
    where e1,etc is a formula referencing a combination of the columns
  Example:
     varexp = x     simplest case: draw a 1-Dim distribution of column named x
            = sqrt(x)            : draw distribution of sqrt(x)
            = x*y/z
            = y:sqrt(x) 2-Dim dsitribution of y versus sqrt(x)
  Note that the variables e1, e2 or e3 may contain a selection.
  example, if e1= x*(y<0), the value histogrammed will be x if y<0
  and will be 0 otherwise.

  selection is an expression with a combination of the columns.
  In a selection all the C++ operators are authorized.
  The value corresponding to the selection expression is used as a weight
  to fill the histogram.
  If the expression includes only boolean operations, the result
  is 0 or 1. If the result is 0, the histogram is not filled.
  In general, the expression may be of the form:
      value*(boolean expression)
  if boolean expression is true, the histogram is filled with
  a weight = value.
  Examples:
      selection1 = "x<y && sqrt(z)>3.2"
      selection2 = "(x+y)*(sqrt(z)>3.2"
  selection1 returns a weigth = 0 or 1
  selection2 returns a weight = x+y if sqrt(z)>3.2
             returns a weight = 0 otherwise.

  option is the drawing option
      see TH1::Draw for the list of all drawing options.
      If option contains the string "goff", no graphics is generated.

  nentries is the number of entries to process (default is all)
  first is the first entry to process (default is 0)

     Drawing expressions using arrays and array elements
     ===================================================
 Let assumes, a leaf fMatrix, on the branch fEvent, which is a 3 by 3 array,
 or a TClonesArray.
 In a TTree::Draw expression you can now access fMatrix using the following
 syntaxes:

   String passed    What is used for each entry of the tree

   "fMatrix"       the 9 elements of fMatrix
   "fMatrix[][]"   the 9 elements of fMatrix
   "fMatrix[2][2]" only the elements fMatrix[2][2]
   "fMatrix[1]"    the 3 elements fMatrix[1][0], fMatrix[1][1] and fMatrix[1][2]
   "fMatrix[1][]"  the 3 elements fMatrix[1][0], fMatrix[1][1] and fMatrix[1][2]
   "fMatrix[][0]"  the 3 elements fMatrix[0][0], fMatrix[1][0] and fMatrix[2][0]

   "fEvent.fMatrix...." same as "fMatrix..." (unless there is more than one leaf named fMatrix!).

 In summary, if a specific index is not specified for a dimension, TTree::Draw
 will loop through all the indices along this dimension.  Leaving off the
 last (right most) dimension of specifying then with the two characters '[]'
 is equivalent.  For variable size arrays (and TClonesArray) the range
 of the first dimension is recalculated for each entry of the tree.
 You can also specify the index as an expression of any other variables from the
 tree.

 TTree::Draw also now properly handling operations involving 2 or more arrays.

 Let assume a second matrix fResults[5][2], here are a sample of some
 of the possible combinations, the number of elements they produce and
 the loop used:

  expression                       element(s)  Loop

  "fMatrix[2][1] - fResults[5][2]"   one     no loop
  "fMatrix[2][]  - fResults[5][2]"   three   on 2nd dim fMatrix
  "fMatrix[2][]  - fResults[5][]"    two     on both 2nd dimensions
  "fMatrix[][2]  - fResults[][1]"    three   on both 1st dimensions
  "fMatrix[][2]  - fResults[][]"     six     on both 1st and 2nd dimensions of
                                             fResults
  "fMatrix[][2]  - fResults[3][]"    two     on 1st dim of fMatrix and 2nd of
                                             fResults (at the same time)
  "fMatrix[][]   - fResults[][]"     six     on 1st dim then on  2nd dim

  "fMatrix[][fResult[][]]"           30      on 1st dim of fMatrix then on both
                                             dimensions of fResults.  The value
                                             if fResults[j][k] is used as the second
                                             index of fMatrix.

 In summary, TTree::Draw loops through all un-specified dimensions.  To
 figure out the range of each loop, we match each unspecified dimension
 from left to right (ignoring ALL dimensions for which an index has been
 specified), in the equivalent loop matched dimensions use the same index
 and are restricted to the smallest range (of only the matched dimensions).
 When involving variable arrays, the range can of course be different
 for each entry of the tree.

 So the loop equivalent to "fMatrix[][2] - fResults[3][]" is:

    for (Int_t i0; i0 < min(3,2); i0++) {
       use the value of (fMatrix[i0][2] - fMatrix[3][i0])
    }

 So the loop equivalent to "fMatrix[][2] - fResults[][]" is:

    for (Int_t i0; i0 < min(3,5); i0++) {
       for (Int_t i1; i1 < 2; i1++) {
          use the value of (fMatrix[i0][2] - fMatrix[i0][i1])
       }
    }

 So the loop equivalent to "fMatrix[][] - fResults[][]" is:

    for (Int_t i0; i0 < min(3,5); i0++) {
       for (Int_t i1; i1 < min(3,2); i1++) {
          use the value of (fMatrix[i0][i1] - fResults[i0][i1])
       }
    }

 So the loop equivalent to "fMatrix[][fResults[][]]" is:

    for (Int_t i0; i0 < 3; i0++) {
       for (Int_t j2; j2 < 5; j2++) {
          for (Int_t j3; j3 < 2; j3++) {
             i1 = fResults[j2][j3];
             use the value of fMatrix[i0][i1]
       }
    }

     Saving the result of Draw to an histogram
     =========================================
  By default the temporary histogram created is called htemp.
  If varexp0 contains >>hnew (following the variable(s) name(s),
  the new histogram created is called hnew and it is kept in the current
  directory.
  Example:
    tree.Draw("sqrt(x)>>hsqrt","y>0")
    will draw sqrt(x) and save the histogram as "hsqrt" in the current
    directory.

  The binning information is taken from the environment variables

     Hist.Binning.?D.?

  In addition, the name of the histogram can be followed by up to 9
  numbers between '(' and ')', where the numbers describe the
  following:

   1 - bins in x-direction
   2 - lower limit in x-direction
   3 - upper limit in x-direction
   4-6 same for y-direction
   7-9 same for z-direction

   When a new binning is used the new value will become the default.
   Values can be skipped.
  Example:
    tree.Draw("sqrt(x)>>hsqrt(500,10,20)"
          // plot sqrt(x) between 10 and 20 using 500 bins
    tree.Draw("sqrt(x):sin(y)>>hsqrt(100,10,60,50,.1,.5)"
          // plot sqrt(x) against sin(y)
          // 100 bins in x-direction; lower limit on x-axis is 10; upper limit is 60
          //  50 bins in y-direction; lower limit on y-axis is .1; upper limit is .5

  By default, the specified histogram is reset.
  To continue to append data to an existing histogram, use "+" in front
  of the histogram name.
  A '+' in front of the histogram name is ignored, when the name is followed by
  binning information as described in the previous paragraph.
    tree.Draw("sqrt(x)>>+hsqrt","y>0")
      will not reset hsqrt, but will continue filling.
  This works for 1-D, 2-D and 3-D histograms.

     Special functions and variables
     ===============================

  Entry$:  A TTree::Draw formula can use the special variable Entry$
  to access the entry number being read.  For example to draw every
  other entry use:
    tree.Draw("myvar","Entry$%2==0");

  Entry$    : return the current entry number (== TTree::GetReadEntry())
  Entries$  : return the total number of entries (== TTree::GetEntries())
  Length$   : return the total number of element of this formula for this
  		   entry (==TTreeFormula::GetNdata())
  Iteration$: return the current iteration over this formula for this
                 entry (i.e. varies from 0 to Length$).

     Making a Profile histogram
     ==========================
  In case of a 2-Dim expression, one can generate a TProfile histogram
  instead of a TH2F histogram by specyfying option=prof or option=profs.
  The option=prof is automatically selected in case of y:x>>pf
  where pf is an existing TProfile histogram.

     Making a 2D Profile histogram
     ==========================
  In case of a 3-Dim expression, one can generate a TProfile2D histogram
  instead of a TH3F histogram by specyfying option=prof or option=profs.
  The option=prof is automatically selected in case of z:y:x>>pf
  where pf is an existing TProfile2D histogram.

     Saving the result of Draw to a TEventList
     =========================================
  TTree::Draw can be used to fill a TEventList object (list of entry numbers)
  instead of histogramming one variable.
  If varexp0 has the form >>elist , a TEventList object named "elist"
  is created in the current directory. elist will contain the list
  of entry numbers satisfying the current selection.
  Example:
    tree.Draw(">>yplus","y>0")
    will create a TEventList object named "yplus" in the current directory.
    In an interactive session, one can type (after TTree::Draw)
       yplus.Print("all")
    to print the list of entry numbers in the list.

  By default, the specified entry list is reset.
  To continue to append data to an existing list, use "+" in front
  of the list name;
    tree.Draw(">>+yplus","y>0")
      will not reset yplus, but will enter the selected entries at the end
      of the existing list.

      Using a TEventList as Input
      ===========================
  Once a TEventList object has been generated, it can be used as input
  for TTree::Draw. Use TTree::SetEventList to set the current event list
  Example:
     TEventList *elist = (TEventList*)gDirectory->Get("yplus");
     tree->SetEventList(elist);
     tree->Draw("py");

  If arrays are used in the selection critera, the event entered in the
  list are all the event that have at least one element of the array that
  satisfy the selection.
  Example:
      tree.Draw(">>pyplus","fTracks.fPy>0");
      tree->SetEventList(pyplus);
      tree->Draw("fTracks.fPy");
  will draw the fPy of ALL tracks in event with at least one track with
  a positive fPy.

  To select only the elements that did match the original selection
  use TEventList::SetReapplyCut.
  Example:
      tree.Draw(">>pyplus","fTracks.fPy>0");
      pyplus->SetReapplyCut(kTRUE);
      tree->SetEventList(pyplus);
      tree->Draw("fTracks.fPy");
  will draw the fPy of only the tracks that have a positive fPy.

  Note: Use tree->SetEventList(0) if you do not want use the list as input.

      How to obtain more info from TTree::Draw
      ========================================

  Once TTree::Draw has been called, it is possible to access useful
  information still stored in the TTree object via the following functions:
    -GetSelectedRows()    // return the number of entries accepted by the
                          //selection expression. In case where no selection
                          //was specified, returns the number of entries processed.
    -GetV1()              //returns a pointer to the float array of V1
    -GetV2()              //returns a pointer to the float array of V2
    -GetV3()              //returns a pointer to the float array of V3
    -GetW()               //returns a pointer to the double array of Weights
                          //where weight equal the result of the selection expression.
   where V1,V2,V3 correspond to the expressions in
   TTree::Draw("V1:V2:V3",selection);

   Example:
    Root > ntuple->Draw("py:px","pz>4");
    Root > TGraph *gr = new TGraph(ntuple->GetSelectedRows(),
                                   ntuple->GetV2(), ntuple->GetV1());
    Root > gr->Draw("ap"); //draw graph in current pad
    creates a TGraph object with a number of points corresponding to the
    number of entries selected by the expression "pz>4", the x points of the graph
    being the px values of the Tree and the y points the py values.

   Important note: By default TTree::Draw creates the arrays obtained
    with GetV1, GetV2, GetV3, GetW with a length corresponding to the
    parameter fEstimate. By default fEstimate=10000 and can be modified
    via TTree::SetEstimate. A possible recipee is to do
       tree->SetEstimate(tree->GetEntries());
    You must call SetEstimate if the expected number of selected rows
    is greater than 10000.

    You can use the option "goff" to turn off the graphics output
    of TTree::Draw in the above example.

           Automatic interface to TTree::Draw via the TTreeViewer
           ======================================================

    A complete graphical interface to this function is implemented
    in the class TTreeViewer.
    To start the TTreeViewer, three possibilities:
       - select TTree context menu item "StartViewer"
       - type the command  "TTreeViewer TV(treeName)"
       - execute statement "tree->StartViewer();"

*-*-*-*-*-*-*-*-*-*-*-*-*Loop on all entries*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                      ==================

  nentries is the number of entries to process (default is all)
  first is the first entry to process (default is 0)

  action =  1  Fill 1-D histogram obj
         =  2  Fill 2-D histogram obj
         =  3  Fill 3-D histogram obj
         =  4  Fill Profile histogram obj
         =  5  Fill a TEventlist
         = 11  Estimate Limits
         = 12  Fill 2-D PolyMarker obj
         = 13  Fill 3-D PolyMarker obj
  action < 0   Evaluate Limits for case abs(action)

*-*-*-*-*-*-*-*-*Fit  a projected item(s) from a Tree*-*-*-*-*-*-*-*-*-*
*-*              ======================================

  formula is a TF1 expression.

  See TTree::Draw for explanations of the other parameters.

  By default the temporary histogram created is called htemp.
  If varexp contains >>hnew , the new histogram created is called hnew
  and it is kept in the current directory.
  Example:
    tree.Fit("pol4","sqrt(x)>>hsqrt","y>0")
    will fit sqrt(x) and save the histogram as "hsqrt" in the current
    directory.

*-*-*-*-*-*-*-*-*Return name corresponding to colindex in varexp*-*-*-*-*-*
*-*              ===============================================

   varexp is a string of names separated by :
   index is an array with pointers to the start of name[i] in varexp

 Return in nentries and firstentry the optimal range of entries (packet)
 to be processed by slave sl. See TPacketGenerator for the algorithm
 used to get the packet size.

*-*-*-*-*-*-*-*-*Loop on nentries of this tree starting at firstentry
*-*              ===================================================

====>
*-*-*-*-*-*-*Generate skeleton analysis class for this Tree*-*-*-*-*-*-*
*-*          ==============================================

   The following files are produced: classname.h and classname.C
   if classname is NULL, classname will be nameoftree.

   When the option "selector" is specified, the function generates the
   selector class described in TTree::MakeSelector.

   The generated code in classname.h includes the following:
      - Identification of the original Tree and Input file name
      - Definition of analysis class (data and functions)
      - the following class functions:
         -constructor (connecting by default the Tree file)
         -GetEntry(Int_t entry)
         -Init(TTree *tree) to initialize a new TTree
         -Show(Int_t entry) to read and Dump entry

   The generated code in classname.C includes only the main
   analysis function Loop.

   To use this function:
      - connect your Tree file (eg: TFile f("myfile.root");)
      - T->MakeClass("MyClass");
    where T is the name of the Tree in file myfile.root
    and MyClass.h, MyClass.C the name of the files created by this function.
   In a Root session, you can do:
      Root > .L MyClass.C
      Root > MyClass t
      Root > t.GetEntry(12); // Fill t data members with entry number 12
      Root > t.Show();       // Show values of entry 12
      Root > t.Show(16);     // Read and show values of entry 16
      Root > t.Loop();       // Loop on all entries

====>

====>
*-*-*-*-*-*-*-*-*Generate skeleton function for this Tree*-*-*-*-*-*-*
*-*              ========================================

   The function code is written on filename
   if filename is NULL, filename will be nameoftree.C

   The generated code includes the following:
      - Identification of the original Tree and Input file name
      - Connection of the Tree file
      - Declaration of Tree variables
      - Setting of branches addresses
      - a skeleton for the entry loop

   To use this function:
      - connect your Tree file (eg: TFile f("myfile.root");)
      - T->MakeCode("user.C");
    where T is the name of the Tree in file myfile.root
    and user.C the name of the file created by this function.

   NOTE: Since the implementation of this function, new and better
         function TTree::MakeClass and TTree::MakeSelector have been developped.

          Author: Rene Brun
====>

*-*-*-*-*-*-*-*-*Build Index array for names in varexp*-*-*-*-*-*-*-*-*-*-*
*-*              =====================================

*-*-*-*-*-*-*-*-*Interface to the Principal Components Analysis class*-*-*
*-*              ====================================================

   Create an instance of TPrincipal
   Fill it with the selected variables
   if option "n" is specified, the TPrincipal object is filled with
                 normalized variables.
   If option "p" is specified, compute the principal components
   If option "p" and "d" print results of analysis
   If option "p" and "h" generate standard histograms
   If option "p" and "c" generate code of conversion functions
   return a pointer to the TPrincipal object. It is the user responsability
   to delete this object.
   The option default value is "np"

   see TTreePlayer::DrawSelect for explanation of the other parameters.

*-*-*-*-*-*-*-*-*Process this tree executing the code in filename*-*-*-*-*
*-*              ================================================

   The code in filename is loaded (interpreted or compiled , see below)
   filename must contain a valid class implementation derived from TSelector.
   where TSelector has the following member functions:

     void TSelector::Begin(). This function is called before looping on the
          events in the Tree. The user can create his histograms in this function.

     Bool_t TSelector::Notify(). This function is called at the first entry
          of a new file in a chain.

     Bool_t TSelector::ProcessCut(Int_t tentry). This function is called
          before processing tentry. It is the user's responsability to read
          the corresponding entry in memory (may be just a partial read).
          The function returns kTRUE if the entry must be processed,
          kFALSE otherwise. tentry is the entry number in the current Tree.

     void TSelector::ProcessFill(Int_t tentry). This function is called for
          all selected events. User fills histograms in this function.

     void TSelector::Terminate(). This function is called at the end of
          the loop on all events.

   if filename is of the form file.C, the file will be interpreted.
   if filename is of the form file.C++, the file file.C will be compiled
      and dynamically loaded.
   if filename is of the form file.C+, the file file.C will be compiled
      and dynamically loaded. At next call, if file.C is older than file.o
      and file.so, the file.C is not compiled, only file.so is loaded.

*-*-*-*-*-*-*-*-*Process this tree executing the code in selector*-*-*-*-*
*-*              ================================================

   The TSelector class has the following member functions:

     void TSelector::Begin(). This function is called before looping on the
          events in the Tree. The user can create his histograms in this function.

     Bool_t TSelector::Notify(). This function is called at the first entry
          of a new file in a chain.

     Bool_t TSelector::ProcessCut(Int_t tentry). This function is called
          before processing tentry. It is the user's responsability to read
          the corresponding entry in memory (may be just a partial read).
          The function returns kTRUE if the entry must be processed,
          kFALSE otherwise. tentry is the entry number in the current Tree.

     void TSelector::ProcessFill(Int_t tentry). This function is called for
          all selected events. User fills histograms in this function.

     void TSelector::Terminate(). This function is called at the end of
          the loop on all events.

  If the Tree (Chain) has an associated EventList, the loop is on the nentries
  of the EventList, starting at firstentry, otherwise the loop is on the
  specified Tree entries.

 Loop on Tree and print entries passing selection. If varexp is 0 (or "")
 then print only first 8 columns. If varexp = "*" print all columns.
 Otherwise a columns selection can be made using "var1:var2:var3".

 Loop on Tree and return TSQLResult object containing entries passing
 selection. If varexp is 0 (or "") then print only first 8 columns.
 If varexp = "*" print all columns. Otherwise a columns selection can
 be made using "var1:var2:var3". In case of error 0 is returned otherwise
 a TSQLResult object which must be deleted by the user.

*-*-*-*-*-*-*-*-*Set number of entries to estimate variable limits*-*-*-*
*-*              ================================================

*-*-*-*-*-*-*-*-*Set number of entries per packet for parallel root*-*-*-*-*
*-*              =================================================

*-*-*-*-*-*-*-*-*Start the TTreeViewer on this TTree*-*-*-*-*-*-*-*-*-*
*-*              ===================================

  ww is the width of the canvas in pixels
  wh is the height of the canvas in pixels

*-*-*-*-*-*Execute action for object obj nfill times*-*-*-*-*-*-*-*-*-*
*-*        =========================================

*-*-*-*-*-*Estimate limits for 1-D, 2-D or 3-D objects*-*-*-*-*-*-*-*-*-*
*-*        ===========================================

*-*-*-*-*-*Unbinned fit of one or more variable(s) from a Tree*-*-*-*-*-*
*-*        ===================================================

  funcname is a TF1 function.

  See TTree::Draw for explanations of the other parameters.

   Fit the variable varexp using the function funcname using the
   selection cuts given by selection.

   The list of fit options is given in parameter option.
      option = "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

   You can specify boundary limits for some or all parameters via
        func->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.

   For the fit to be meaningful, the function must be self-normalized.

   i.e. It must have the same integral regardless of the parameter
   settings.  Otherwise the fit will effectively just maximize the
   area.

   In practice it is convenient to have a normalization variable
   which is fixed for the fit.  e.g.

     TF1* f1 = new TF1("f1", "gaus(0)/sqrt(2*3.14159)/[2]", 0, 5);
     f1->SetParameters(1, 3.1, 0.01);
     f1->SetParLimits(0, 1, 1); // fix the normalization parameter to 1
     data->UnbinnedFit("f1", "jpsimass", "jpsipt>3.0");
   

   1, 2 and 3 Dimensional fits are supported.
   See also TTree::Fit

 this function is called by TChain::LoadTree when a new Tree is loaded.
 Because Trees in a TChain may have a different list of leaves, one
 must update the leaves numbers in the TTreeFormula used by the TreePlayer.

Inline Functions

                    Int_t GetDimension() const
                     TH1* GetHistogram() const
                    Int_t GetMultiplicity() const
                    Int_t GetNfill() const
        TPacketGenerator* GetPacketGenerator() const
                    Int_t GetPacketSize() const
              const char* GetScanFileName() const
            TTreeFormula* GetSelect() const
                    Int_t GetSelectedRows() const
            TTreeFormula* GetVar1() const
            TTreeFormula* GetVar2() const
            TTreeFormula* GetVar3() const
            TTreeFormula* GetVar4() const
                Double_t* GetV1() const
                Double_t* GetV2() const
                Double_t* GetV3() const
                Double_t* GetW() const
                   Bool_t ScanRedirected()
                     void SetScanRedirect(Bool_t on = kFALSE)
                     void SetScanFileName(const char* name)
                     void SetTree(TTree* t)
                  TClass* Class()
                  TClass* IsA() const
                     void ShowMembers(TMemberInspector& insp, char* parent)
                     void Streamer(TBuffer& b)
                     void StreamerNVirtual(TBuffer& b)
              TTreePlayer TTreePlayer(const TTreePlayer&)