TTree

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

    protected:

       const char* GetNameByIndex(TString& varexp, Int_t* index, Int_t colindex) const
      virtual void MakeIndex(TString& varexp, Int_t* index)

    public:

                    TTree TTree()
                    TTree TTree(const char* name, const char* title, Int_t maxvirtualsize = 0)
                    TTree TTree(TTree&)
             virtual void ~TTree()
             virtual void AddTotBytes(Int_t tot)
             virtual void AddZipBytes(Int_t zip)
             virtual void AutoSave()
         virtual TBranch* Branch(const char* name, void* clonesaddress, Int_t bufsize = 32000, Int_t splitlevel = 1)
         virtual TBranch* Branch(const char* name, const char* classname, void* addobj, Int_t bufsize = 32000, Int_t splitlevel = 1)
         virtual TBranch* Branch(const char* name, void* address, const char* leaflist, Int_t bufsize = 32000)
            virtual Int_t Branch(TList* list, Int_t bufsize = 32000)
             virtual void Browse(TBrowser* b)
             virtual void BuildIndex(const char* majorname, const char* minorname)
             virtual void BuildStreamerInfo(TClass* cl, void* pointer = 0)
           static TClass* Class()
           virtual TTree* CloneTree(Int_t nentries = -1, Option_t* option)
            virtual Int_t CopyEntries(TTree* tree, Int_t nentries = -1)
           virtual TTree* CopyTree(const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
             virtual void Delete(Option_t* option)
             virtual void Draw(Option_t* opt)
            virtual Int_t Draw(const char* varexp, TCut selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
            virtual Int_t Draw(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
             virtual void DropBuffers(Int_t nbytes)
            virtual Int_t Fill()
            virtual Int_t Fit(const char* funcname, const char* varexp, const char* selection, Option_t* option, Option_t* goption, Int_t nentries = 1000000000, Int_t firstentry = 0)
         virtual TBranch* GetBranch(const char* name)
            virtual Int_t GetChainEntryNumber(Int_t entry) const
            virtual Int_t GetChainOffset() const
                   TFile* GetCurrentFile() const
              TDirectory* GetDirectory() const
           virtual Stat_t GetEntries() const
            virtual Int_t GetEntry(Int_t entry = 0, Int_t getall = 0)
            virtual Int_t GetEntryNumber(Int_t entry) const
            virtual Int_t GetEntryNumberWithIndex(Int_t major, Int_t minor) const
            virtual Int_t GetEntryWithIndex(Int_t major, Int_t minor)
            virtual Int_t GetEstimate() const
                    Int_t GetEvent(Int_t entry = 0, Int_t getall = 0)
              TEventList* GetEventList() const
                     TH1* GetHistogram()
           virtual Int_t* GetIndex()
        virtual Double_t* GetIndexValues()
           virtual TLeaf* GetLeaf(const char* name)
       virtual TObjArray* GetListOfBranches()
       virtual TObjArray* GetListOfLeaves()
            virtual Int_t GetMaxEntryLoop() const
         virtual Double_t GetMaximum(const char* columname)
            virtual Int_t GetMaxVirtualSize() const
         virtual Double_t GetMinimum(const char* columname)
            virtual Int_t GetNbranches()
            virtual Int_t GetPacketSize() const
      TVirtualTreePlayer* GetPlayer()
            virtual Int_t GetReadEntry() const
            virtual Int_t GetReadEvent() const
            virtual Int_t GetScanField() const
            TTreeFormula* GetSelect()
            virtual Int_t GetSelectedRows()
            virtual Int_t GetTimerInterval() const
           virtual Stat_t GetTotBytes() const
           virtual TTree* GetTree() const
            virtual Int_t GetTreeNumber() const
            virtual Int_t GetUpdate() const
        virtual Double_t* GetV1()
        virtual Double_t* GetV2()
        virtual Double_t* GetV3()
            TTreeFormula* GetVar1()
            TTreeFormula* GetVar2()
            TTreeFormula* GetVar3()
            TTreeFormula* GetVar4()
        virtual Double_t* GetW()
           virtual Stat_t GetZipBytes() const
             virtual void IncrementTotalBuffers(Int_t nbytes)
          virtual TClass* IsA() const
           virtual Bool_t IsFolder() const
            virtual Int_t LoadTree(Int_t entry)
             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 Int_t MakeSelector(const char* selector = 0)
                   Bool_t MemoryFull(Int_t nbytes)
              TPrincipal* Principal(const char* varexp, const char* selection, Option_t* option = np, Int_t nentries = 1000000000, Int_t firstentry = 0)
             virtual void Print(Option_t* option) const
            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 Int_t Project(const char* hname, const char* varexp, const char* selection, 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 void Reset(Option_t* option)
            virtual Int_t Scan(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
             virtual void SetAutoSave(Int_t autos = 10000000)
             virtual void SetBasketSize(const char* bname, Int_t buffsize = 16000)
             virtual void SetBranchAddress(const char* bname, void* add)
             virtual void SetBranchStatus(const char* bname, Bool_t status = 1)
             virtual void SetChainOffset(Int_t offset = 0)
             virtual void SetDirectory(TDirectory* dir)
             virtual void SetEstimate(Int_t nentries = 10000)
             virtual void SetEventList(TEventList* list)
             virtual void SetMaxEntryLoop(Int_t maxev = 1000000000)
             virtual void SetMaxVirtualSize(Int_t size = 0)
             virtual void SetName(const char* name)
             virtual void SetObject(const char* name, const char* title)
             virtual void SetScanField(Int_t n = 50)
             virtual void SetTimerInterval(Int_t msec = 333)
             virtual void SetUpdate(Int_t freq = 0)
             virtual void Show(Int_t entry = -1)
             virtual void ShowMembers(TMemberInspector& insp, char* parent)
             virtual void StartViewer()
             virtual void Streamer(TBuffer& b)
                     void StreamerNVirtual(TBuffer& b)
            virtual Int_t UnbinnedFit(const char* funcname, const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
             virtual void UseCurrentStyle()

  Data Members

    protected:

                   Stat_t fEntries         Number of entries
                   Stat_t fTotBytes        Total number of bytes in all branches before compression
                   Stat_t fZipBytes        Total number of bytes in all branches after compression
                   Stat_t fSavedBytes      Number of autosaved bytes
                    Int_t fTimerInterval   Timer interval in milliseconds
                    Int_t fScanField       Number of runs before prompting in Scan
                    Int_t fUpdate          Update frequency for EntryLoop
                    Int_t fMaxEntryLoop    Maximum number of entries to process
                    Int_t fMaxVirtualSize  Maximum total size of buffers kept in memory
                    Int_t fAutoSave        Autosave tree when fAutoSave bytes produced
                    Int_t fEstimate        Number of entries to estimate histogram limits
                    Int_t fChainOffset     ! Offset of 1st entry of this Tree in a TChain
                    Int_t fReadEntry       ! Number of the entry being processed
                    Int_t fTotalBuffers    ! Total number of bytes in branch buffers
                    Int_t fPacketSize      ! Number of entries in one packet for parallel root
                    Int_t fNfill           ! Local for EntryLoop
              TDirectory* fDirectory       ! Pointer to directory holding this tree
                TObjArray fBranches        List of Branches
                TObjArray fLeaves          Direct pointers to individual branch leaves
              TEventList* fEventList       ! Pointer to event selection list (if one)
                  TArrayD fIndexValues     Sorted index values
                  TArrayI fIndex           Index of sorted values
      TVirtualTreePlayer* fPlayer          ! Pointer to current Tree player

    public:

      static const enum TObject:: kForceRead  

See also

TChain, TNtuple

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=0, the object is serialized in the branch buffer.
        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=2 ,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,
          it is processed as a TObject*, only one branch.

  ==> 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 branches of floats)

/*

*/

  =============================================================================
______________________________________________________________________________
*-*-*-*-*-*-*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 "TROOT.h"
 #include "TFile.h"
 #include "TH1.h"
 #include "TH2.h"
 #include "TProfile.h"
 #include "TRandom.h"
 #include "TTree.h"


 TROOT simple("simple","Histograms and trees");

 //______________________________________________________________________________
 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
      point.y
      point.z
      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*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ========================

*-*-*-*-*-*-*-*-*-*Normal Tree constructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                ======================

   The Tree is created in the current directory
   Use the various functions Branch below to add branches to this Tree.

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

*-*-*-*-*-*-*-*-*-*-*AutoSave tree header every fAutoSave bytes*-*-*-*-*-*
*-*                  ==========================================

   When large Trees are produced, it is safe to activate the AutoSave
   procedure. Some branches may have buffers holding many entries.
   AutoSave is automatically called by TTree::Fill when the number of bytes
   generated since the previous AutoSave is greater than fAutoSave bytes.
   This function may also be invoked by the user, for example every
   N entries.
   Each AutoSave generates a new key on the file.
   Once the key with the tree header has been written, the previous cycle
   (if any) is deleted.

   Note that calling TTree::AutoSave too frequently (or similarly calling
   TTree::SetAutoSave with a small value) is an expensive operation.
   You should make tests for your own application to find a compromize
   between speed and the quantity of information you may loose in case of
   a job crash.

   In case your program crashes before closing the file holding this tree,
   the file will be automatically recovered when you will connect the file
   in UPDATE mode.
   The Tree will be recovered at the status corresponding to the last AutoSave.

*-*-*-*-*-*-*-*-*-*-*Create a new TTree Branch*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  =========================

     This Branch constructor is provided to support non-objects in
     a Tree. The variables described in leaflist may be simple variables
     or structures.
    See the two following constructors for writing objects in a Tree.

    By default the branch buffers are stored in the same file as the Tree.
    use TBranch::SetFile to specify a different file

*-*-*-*-*-*-*-*-*-*-*Create a new TTree BranchObject*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ===============================

    Build a TBranchObject for an object of class classname.
    addobj is the address of a pointer to an object of class classname.
    IMPORTANT: classname must derive from TObject.
    The class dictionary must be available (ClassDef in class header).

    This option requires access to the library where the corresponding class
    is defined. Accessing one single data member in the object implies
    reading the full object.
    See the next Branch constructor for a more efficient storage
    in case the entry consists of arrays of identical objects.

    By default the branch buffers are stored in the same file as the Tree.
    use TBranch::SetFile to specify a different file

      IMPORTANT NOTE about branch names
    In case two or more master branches contain subbranches with
    identical names, one must add a "." (dot) character at the end
    of the master branch name. This will force the name of the subbranch
    to be master.subbranch instead of simply subbranch.
    This situation happens when the top level object (say event)
    has two or more members referencing the same class.
    For example, if a Tree has two branches B1 and B2 corresponding
    to objects of the same class MyClass, one can do:
       tree.Branch("B1.","MyClass",&b1,8000,1);
       tree.Branch("B2.","MyClass",&b2,8000,1);
    if MyClass has 3 members a,b,c, the two instructions above will generate
    subbranches called B1.a, B1.b ,B1.c, B2.a, B2.b, B2.c

*-*-*-*-*-*-*-*-*-*-*Create a new TTree BranchClones*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ===============================

    name:    global name of this BranchClones
    bufsize: buffersize in bytes of each individual data member buffer
    clonesaddress is the address of a pointer to a TClonesArray.

    This Tree option is provided in case each entry consists of one
    or more arrays of same class objects (tracks, hits,etc).
    This function creates as many branches as there are public data members
    in the objects pointed by the TClonesArray. Note that these data members
    can be only basic data types, not pointers or objects.

    BranchClones have the following advantages compared to the two other
    solutions (Branch and BranchObject).
      - When reading the Tree data, it is possible to read selectively
        a subset of one object (may be just one single data member).
      - This solution minimizes the number of objects created/destructed.
      - Data members of the same type are consecutive in the basket buffers,
        therefore optimizing the compression algorithm.
      - Array processing notation becomes possible in the query language.

    By default the branch buffers are stored in the same file as the Tree.
    use TBranch::SetFile to specify a different file

    By default the two members of TObject (fBits and fUniqueID) are stored
    on individual branches. If the splitlevel > 1, these two branches
    will not be created.

   This new function creates one branch for each element in the list.
   Two cases are supported:
      list[i] is a TObject*: a TBranchObject is created with a branch name
                             being the name of the object.
      list[i] is a TClonesArray*: A TBranchClones is created.
      if list[i]->TestBit(TClonesArray::kNoSplit) is 1, the TClonesArray
      is not split.
      if list[i]->TestBit(TClonesArray::kForgetBits) is 1 and the TClonesArray
      is split, then no branches are created for the fBits and fUniqueID
      of the TObject part of the class referenced by the TClonesArray.
   The function returns the total number of branches created.

 Build an index table using the leaves with name: major & minor name
 The index is built in the following way:
    A pass on all entries is made using TTree::Draw
    var1 = majorname
    var2 = minorname
    sel  = majorname +minorname*1e-9
    The standard result from TTree::Draw is stored in fV1, fV2 and fW
    The array fW is sorted into fIndex
  Once the index is computed, one can retrieve one entry via
    TTree:GetEntryWithIndex(majornumber, minornumber)
 Example:
  tree.BuildIndex("Run","Event"); //creates an index using leaves Run and Event
  tree.GetEntryWithIndex(1234,56789); //reads entry corresponding to
                                        Run=1234 and Event=56789

 Note that once the index is built, it can be saved with the TTree object
 with tree.Write(); //if the file has been open in "update" mode.

 The most convenient place to create the index is at the end of
 the filling process just before saving the Tree header.
 If a previous index was computed, it is redefined by this new call.

 Note that this function can also be applied to a TChain.

 Build StreamerInfo for class cl
 pointer is an optional argument that may contain a pointer to an object of cl

 Create a clone of this tree and copy nentries
 By default copy all entries
 option is reserved for future use
        plan to implement option "ACTIVE" to copy only active branches

 IMPORTANT: Before invoking this function, the branch addresses
            of this TTree must have been set.
 For examples of CloneTree, see tutorials
  -copytree:
    Example of Root macro to copy a subset of a Tree to a new Tree
    The input file has been generated by the program in $ROOTSYS/test/Event
    with   Event 1000 1 1 1
  -copytree2:
    Example of Root macro to copy a subset of a Tree to a new Tree
    One branch of the new Tree is written to a separate file
    The input file has been generated by the program in $ROOTSYS/test/Event
    with   Event 1000 1 1 1

 Copy nentries from tree to this tree
 By default copy all entries
 Return number of bytes copied to this tree.

*-*-*-*-*-*-*-*-*copy a Tree with selection*-*-*-*-*-*
*-*              ==========================

*-*-*-*-*-*-*-*-*Delete this tree from memory or/and disk
*-*              ========================================

  if option == "all" delete Tree object from memory AND from disk
                     all baskets on disk are deleted. All keys with same name
                     are deleted.
  if option =="" only Tree object in memory is deleted.

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

      This function accepts TCut objects as arguments.
      Useful to use the string operator +
         example:
            ntuple.Draw("x",cut1+cut2+cut3);

*-*-*-*-*-*-*-*-*-*-*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)

  This function returns the number of selected entries. It returns -1
  if an error occurs.

     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.

 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


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

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

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

  By default, the specified histogram is reset.
  To continue to append data to an existing histogram, use "+" in front
  of the histogram name;
    tree.Draw("sqrt(x)>>+hsqrt","y>0")
      will not reset hsqrt, but will continue filling.

     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.

     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");

  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 double array of V1
    -GetV2()              //returns a pointer to the double array of V2
    -GetV3()              //returns a pointer to the double 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();"

*-*-*-*-*Drop branch buffers to accomodate nbytes below MaxVirtualsize*-*-*-*

*-*-*-*-*Fill all branches of a Tree*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*      ===========================

   This function loops on all the branches of this tree.
   For each branch, it copies to the branch buffer (basket) the current
   values of the leaves data types.
   If a leaf is a simple data type, a simple conversion to a machine
   independent format has to be done.

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

  funcname is a TF1 function.

  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.

  The function returns the number of selected entries.

  Example:
    tree.Fit(pol4,sqrt(x)>>hsqrt,y>0)
    will fit sqrt(x) and save the histogram as "hsqrt" in the current
    directory.

   See also TTree::UnbinnedFit

*-*-*-*-*-*Return pointer to the branch with name*-*-*-*-*-*-*-*
*-*        ======================================

*-*-*-*-*-*Return pointer to the current file*-*-*-*-*-*-*-*
*-*        ==================================

*-*-*-*-*-*Read all branches of entry and return total number of bytes*-*-*
*-*        ===========================================================
     getall = 0 : get only active branches
     getall = 1 : get all branches

*-*-*-*-*-*Return entry number corresponding to entry*-*-*
*-*        ==========================================
     if no selection list returns entry
     else returns the entry number corresponding to the list index=entry

 Return entry number corresponding to major and minor number
 Note that this function returns only the entry number, not the data
 To read the data corresponding to an entry number, use TTree::GetEntryWithIndex
 the BuildIndex function has created a table of Double_t* of sorted values
 corresponding to val = major + minor*1e-9;
 The function performs binary search in this sorted table.
 If it find an array value that maches val, it returns directly the
 index in the table.
 If an entry corresponding to major and minor is not found, the function
 returns a value = -lowest -1 where lowest is the entry number in the table
 immediatly lower than the requested value.

 Return entry  corresponding to major and minor number
 For example:
     Int_t run   = 1234;
     Int_t event = 345;
     Int_t serial= tree.GetEntryNumberWithIndex(run,event);
    now the variable serial is in the range [0,nentries] and one can do
    tree.GetEntry(serial);

*-*-*-*-*-*Return pointer to the 1st Leaf named name in any Branch-*-*-*-*-*
*-*        =======================================================

*-*-*-*-*-*-*-*-*Return maximum of column with name columname*-*-*-*-*-*-*
*-*              ============================================

*-*-*-*-*-*-*-*-*Return minimum of column with name columname*-*-*-*-*-*-*
*-*              ============================================

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

 Load the TTreePlayer (if not already done)
 Pointer to player is fPlayer

*-*-*-*-*-*-*-*-*Set current Tree entry
*-*              ======================

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

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

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

   The generated code in selector.h includes the following:
      - Identification of the original Tree and Input file name
      - Definition of selector class (data and functions)
      - the following class functions:
         - constructor and destructor
         - void    Begin(TTree *tree)
         - void    Init(TTree *tree)
         - Bool_t  Notify()
         - Bool_t  ProcessCut(Int-t entry)
         - void    ProcessFill(Int-t entry)
         - void    Terminate

   The class selector derives from TSelector.
   The generated code in selector.C includes empty functions defined above:

   To use this function:
      - connect your Tree file (eg: TFile f("myfile.root");)
      - T->MakeSelector("myselect");
    where T is the name of the Tree in file myfile.root
    and myselect.h, myselect.C the name of the files created by this function.
   In a Root session, you can do:
      Root > T->Process("select.C")

====>

====>
*-*-*-*-*-*-*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 "anal" is specified, the function generates the
   analysis class described in TTree::makeAnal.

   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("anal.C");
    where T is the name of the Tree in file myfile.root
    and anal.C the name of the file created by this function.

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

          Author: Rene Brun
====>

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

*-*-*-*-*-*Check if adding nbytes to memory we are still below MaxVirtualsize
*-*        ==================================================================

*-*-*-*-*-*-*-*-*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 TTree::Draw for explanation of the other parameters.

   The created object is  named "principal" and a reference to it
   is added to the list of specials Root objects.
   you can retrieve a pointer to the created object via:
      TPrincipal *principal =
        (TPrincipal*)gROOT->GetListOfSpecials()->FindObject("principal");

 Print a summary of the Tree contents. In case options are "p" or "pa"
 print information about the TPacketGenerator ("pa" is equivalent to
 TPacketGenerator::Print("all")).

*-*-*-*-*-*-*-*-*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::ProcessCut(Int_t entry). This function is called
          before processing entry. 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.
     void TSelector::ProcessFill(Int_t entry). 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.
     void TTreeProcess::Begin(). This function is called before looping on the
          events in the Tree. The user can create his histograms in this function.

   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. The corresponding binary file and shared library
      will be deleted at the end of the function.
   if filename is of the form file.C+, the file file.C will be compiled
      and dynamically loaded. The corresponding binary file and shared library
      will be kept at the end of the function. 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.

   The function returns the number of processed entries. It returns -1
   in case of an error.

*-*-*-*-*-*-*-*-*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::ProcessCut(Int_t entry). This function is called
          before processing entry. 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.
     void TSelector::ProcessFill(Int_t entry). 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.
     void TTreeProcess::Begin(). This function is called before looping on the
          events in the Tree. The user can create his histograms in this function.

*-*-*-*-*-*-*-*-*Make a projection of a Tree using selections*-*-*-*-*-*-*
*-*              =============================================

   Depending on the value of varexp (described in Draw) a 1-D,2-D,etc
   projection of the Tree will be filled in histogram hname.
   Note that the dimension of hname must match with the dimension of varexp.

 Loop on Tree & return TSQLResult object containing entries following selection

*-*-*-*-*-*-*-*Reset buffers and entries count in all branches/leaves*-*-*
*-*            ======================================================

*-*-*-*-*-*-*-*-*Loop on Tree & print entries following selection*-*-*-*-*-*
*-*              ===============================================

*-*-*-*-*-*-*-*-*Set branc(es) basket size*-*-*-*-*-*-*-*
*-*              =========================

     bname is the name of a branch.
     if bname="*", apply to all branches.
     if bname="xxx*", apply to all branches with name starting with xxx
     see TRegexp for wildcarding options
     buffsize = branc basket size

*-*-*-*-*-*-*-*-*Set branch address*-*-*-*-*-*-*-*
*-*              ==================

      If object is a TTree, this function is only an interface to TBranch::SetAddress
      Function overloaded by TChain.

*-*-*-*-*-*-*-*-*Set branch status Process or DoNotProcess*-*-*-*-*-*-*-*
*-*              =========================================

     bname is the name of a branch.
     if bname="*", apply to all branches.
     if bname="xxx*", apply to all branches with name starting with xxx
     see TRegexp for wildcarding options
      status = 1  branch will be processed
             = 0  branch will not be processed

 Remove reference to this tree from current directory and add
 reference to new directory dir. dir can be 0 in which case the tree
 does not belong to any directory.

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

 Change the name of this Tree

 Change the name and title of this Tree

*-*-*-*-*-*Print values of all active leaves for entry*-*-*-*-*-*-*-*
*-*        ===========================================
 if entry==-1, print current entry (default)

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

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

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

*-*-*-*-*-*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

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

Inline Functions

                 void AddTotBytes(Int_t tot)
                 void AddZipBytes(Int_t zip)
                Int_t Draw(const char* varexp, const char* selection, Option_t* option, Int_t nentries = 1000000000, Int_t firstentry = 0)
                Int_t GetChainEntryNumber(Int_t entry) const
                Int_t GetChainOffset() const
          TDirectory* GetDirectory() const
               Stat_t GetEntries() const
                Int_t GetEstimate() const
                Int_t GetEvent(Int_t entry = 0, Int_t getall = 0)
          TEventList* GetEventList() const
                 TH1* GetHistogram()
               Int_t* GetIndex()
            Double_t* GetIndexValues()
           TObjArray* GetListOfBranches()
           TObjArray* GetListOfLeaves()
                Int_t GetMaxEntryLoop() const
                Int_t GetMaxVirtualSize() const
                Int_t GetNbranches()
                Int_t GetPacketSize() const
                Int_t GetReadEntry() const
                Int_t GetReadEvent() const
                Int_t GetScanField() const
        TTreeFormula* GetSelect()
                Int_t GetSelectedRows()
                Int_t GetTimerInterval() const
               TTree* GetTree() const
                Int_t GetUpdate() const
                Int_t GetTreeNumber() const
        TTreeFormula* GetVar1()
        TTreeFormula* GetVar2()
        TTreeFormula* GetVar3()
        TTreeFormula* GetVar4()
            Double_t* GetV1()
            Double_t* GetV2()
            Double_t* GetV3()
            Double_t* GetW()
               Stat_t GetTotBytes() const
               Stat_t GetZipBytes() const
                 void IncrementTotalBuffers(Int_t nbytes)
               Bool_t IsFolder() const
                 void SetAutoSave(Int_t autos = 10000000)
                 void SetChainOffset(Int_t offset = 0)
                 void SetEventList(TEventList* list)
                 void SetMaxEntryLoop(Int_t maxev = 1000000000)
                 void SetMaxVirtualSize(Int_t size = 0)
                 void SetScanField(Int_t n = 50)
                 void SetTimerInterval(Int_t msec = 333)
                 void SetUpdate(Int_t freq = 0)
              TClass* Class()
              TClass* IsA() const
                 void ShowMembers(TMemberInspector& insp, char* parent)
                 void StreamerNVirtual(TBuffer& b)
                TTree TTree(TTree&)