library: libTreePlayer #include "TTreePlayer.h"

# TTreePlayer

class description - source file - inheritance tree (.ps)

## class TTreePlayer : public TVirtualTreePlayer

| Inheritance Chart:

`TObject`

<-

`TVirtualTreePlayer`

<-

`TTreePlayer`

        protected:

                 void DeleteSelectorFromFile()
          const char* GetNameByIndex(TString& varexp, Int_t* index, Int_t colindex) const
                 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(const TTreePlayer&)
                         virtual ~TTreePlayer()
          virtual TVirtualIndex* BuildIndex(const TTree* T, const char* majorname, const char* minorname)
                  static TClass* Class()
                  virtual TTree* CopyTree(const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
                   virtual Int_t DrawScript(const char* wrapperPrefix, const char* macrofilename, const char* cutfilename, Option_t* option, Int_t nentries, Int_t firstentry)
                   virtual Int_t DrawSelect(const char* varexp, const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
                   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 GetNfill() const
                     const char* GetScanFileName() const
           virtual TTreeFormula* GetSelect() const
                   virtual Int_t GetSelectedRows() const
                      TSelector* GetSelector() const
               virtual Double_t* GetV1() const
               virtual Double_t* GetV2() const
               virtual Double_t* GetV3() const
               virtual Double_t* GetV4() 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 Int_t MakeClass(const char* classname, Option_t* option)
                   virtual Int_t MakeCode(const char* filename)
                   virtual Int_t MakeProxy(const char* classname, const char* macrofilename = "0", const char* cutfilename = "0", Int_t maxUnrolling = 3)
             virtual TPrincipal* Principal(const char* varexp, const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
                   virtual Int_t Process(const char* filename, Option_t* option, Int_t nentries, Int_t firstentry)
                   virtual Int_t Process(TSelector* selector, Option_t* option, Int_t nentries, Int_t firstentry)
             virtual TSQLResult* Query(const char* varexp, const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
                   virtual Int_t Scan(const char* varexp, const char* selection, Option_t* option, Int_t nentries, Int_t firstentry)
                          Bool_t ScanRedirected()
                    virtual void SetEstimate(Int_t n)
                            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
                  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 fDimension         Dimension of the current expression
                   Int_t fSelectedRows      Number of selected entries
                    TH1* fHistogram         ! Pointer to histogram used for the projection
          TSelectorDraw* fSelector          ! Pointer to current selector
              TSelector* fSelectorFromFile  ! Pointer to a user defined selector created by this TTreePlayer object
                 TClass* fSelectorClass     ! Pointer to the actual class of the TSelectorFromFile
                  TList* fInput             ! input list to the selector
                  TList* fFormulaList       ! Pointer to a list of coordinated list TTreeFormula (used by Scan and Query)

## 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;
     }

TTreePlayer()

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

~TTreePlayer()

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

TVirtualIndex* BuildIndex(const TTree *T, const char *majorname, const char *minorname)

TTree* CopyTree(const char *selection, Option_t *, Int_t nentries, Int_t firstentry)

     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)

     IMPORTANT: The copied tree stays connected with this tree until this tree
                is deleted.  In particular, any changes in branch addresses
                in this tree are forwarded to the clone trees.  Any changes
                made to the branch addresses of the copied trees are over-ridden
                anytime this tree changes its branch addresses.
                Once this tree is deleted, all the addresses of the copied tree
                are reset to their default values.

     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();

void DeleteSelectorFromFile()

     Delete any selector created by this object.
     The selector has been created using TSelector::GetSelector(file)

Int_t DrawScript(const char* wrapperPrefix, const char *macrofilename, const char *cutfilename, Option_t *option, Int_t nentries, Int_t firstentry)

     Draw the result of a C++ script

     macrofilename and optionally cutfilename are assumed to contain
     at least a method with the same name as the file.  The method
     should return a value that can be automatically cast to
     respectively a double and a boolean.

     Both methods will be executed in a context such that the
     branch names can be used as C++ variables. This is
     accomplished by generating a TTreeProxy (see MakeProxy)
     and including the files in the proper location.

     If a cutfilename is specified, for each entry, we execute
       if (cutfilename()) htemp->Fill(macrofilename());
     If no cutfilename is specified, for each entry we execute
       htemp(macrofilename());

     The default for the histogram are the same as for
     TTreePlayer::DrawSelect

Int_t DrawSelect(const char *varexp0, const char *selection, Option_t *option,Int_t nentries, Int_t firstentry)

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

      varexp is an expression of the general form
       - "e1"           produces a 1-d histogram of expression "e1"
       - "e1:e2"        produces a 2-d histogram (or profile) of "e1" versus "e2"
       - "e1:e2:e3"     produces a 3-d scatter-plot of "e1" versus "e2" versus "e3"
       - "e1:e2:e3:e4"  produces a 3-d scatter-plot of "e1" versus "e2" versus "e3"
                        and "e4" mapped on the color number.

      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 distribution of y versus sqrt(x)
                = px:py:pz:2.5*E  produces a 3-d scatter-plot of px vs py ps pz
                  and the color number of each marker will be 2.5*E.
                  If the color number is negative it is set to 0.
                  If the color number is greater than the current number of colors
                     it is set to the highest color number.
                  The default number of colors is 50.
                  see TStyle::SetPalette for setting a new color palette.

      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.
      One can retrieve a pointer to this histogram with:
        TH1F *htemp = (TH1F*)gPad->GetPrimitive("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 (and also the current pad).
      Example:
        tree.Draw("sqrt(x)>>hsqrt","y>0")
        will draw sqrt(x) and save the histogram as "hsqrt" in the current
        directory.  To retrieve it do:
        TH1F *hsqrt = (TH1F*)gDirectory->Get("hsqrt");

      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$: return the current iteration over this formula for this
                     entry (i.e. varies from 0 to Length$).

      Alt$(primary,alternate) : return the value of "primary" if it is available
                     for the current iteration otherwise return the value of "alternate".
                     For example, with arr1[3] and arr2[2]
        tree->Draw("arr1-Alt$(arr2,0)");
                     will draw arr[0]+arr2[0] ; arr[1]+arr2[1] and arr[1]+0
                     Or with a variable size array arr3
        tree->Draw("Alt$(arr3[0],0)+Alt$(arr3[1],0)+Alt$(arr3[2],0)");
                     will draw the sum arr3 for the index 0 to min(2,actual_size_of_arr3-1)
                     As a comparison
        tree->Draw("arr3[0]+arr3[1]+arr3[2]");
                     will draw the sum arr3 for the index 0 to 2 only if the
                     actual_size_of_arr3 is greater or equal to 3.
                     Note that the array in 'primary' is flatened/linearilized thus using
                     Alt$ with multi-dimensional arrays of different dimensions in unlikely
                     to yield the expected results.  To visualize a bit more what elements
                     would be matched by TTree::Draw, TTree::Scan can be used:
        tree->Scan("arr1:Alt$(arr2,0)");
                     will print on one line the value of arr1 and (arr2,0) that will be
                     matched by
        tree->Draw("arr1-Alt$(arr2,0)");

         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();"

Int_t Fit(const char *formula ,const char *varexp, const char *selection,Option_t *option ,Option_t *goption,Int_t nentries, Int_t firstentry)

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

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

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

Int_t MakeClass(const char *classname, const char *option)

     Generate skeleton analysis class for this Tree

     The following files are produced: classname.h and classname.C
     If classname is 0, classname will be called "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

Int_t MakeCode(const char *filename)

     Generate skeleton function for this Tree

     The function code is written on filename.
     If filename is 0, filename will be called 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.

Int_t MakeProxy(const char *classname, const char *macrofilename, const char *cutfilename, Int_t maxUnrolling)

     Generate a skeleton analysis class for this Tree using TBranchProxy

TPrincipal* Principal(const char *varexp, const char *selection, Option_t *option, Int_t nentries, Int_t firstentry)

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

Int_t Process(const char *filename,Option_t *option, Int_t nentries, Int_t firstentry)

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

      NOTE
      It may be more interesting to invoke directly the other Process function
      accepting a TSelector* as argument.eg
         MySelector *selector = (MySelector*)TSelector::GetSelector(filename);
         selector->CallSomeFunction(..);
         mytree.Process(selector,..);

Int_t Process(TSelector *selector,Option_t *option, Int_t nentries, Int_t firstentry)

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

Int_t Scan(const char *varexp, const char *selection, Option_t * option, Int_t nentries, Int_t firstentry)

     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".

     Arrays (within an entry) are printed in their linear forms.
     If several arrays with multiple dimensions are printed together,
     they will NOT be synchronized.  For example print
       arr1[4][2] and arr2[2][3] will results in a printing similar to:
     ***********************************************
     *    Row   * Instance *      arr1 *      arr2 *
     ***********************************************
     *        x *        0 * arr1[0][0]* arr2[0][0]*
     *        x *        1 * arr1[0][1]* arr2[0][1]*
     *        x *        2 * arr1[1][0]* arr2[0][2]*
     *        x *        3 * arr1[1][1]* arr2[1][0]*
     *        x *        4 * arr1[2][0]* arr2[1][1]*
     *        x *        5 * arr1[2][1]* arr2[1][2]*
     *        x *        6 * arr1[3][0]*           *
     *        x *        7 * arr1[3][1]*           *

     However, if there is a selection criterium which is an array, then
     all the formulas will be synchronized with the selection criterium
     (see TTreePlayer::DrawSelect for more information).

     If option contains
        lenmax=dd
     Where 'dd' is the maximum number of elements per array that should
     be printed.  If 'dd' is 0, all elements are printed (this is the default)

TSQLResult* Query(const char *varexp, const char *selection, Option_t *, Int_t nentries, Int_t firstentry)

     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.

void SetEstimate(Int_t n)

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

void StartViewer(Int_t ww, Int_t wh)

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

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

Int_t UnbinnedFit(const char *funcname ,const char *varexp, const char *selection,Option_t *option ,Int_t nentries, Int_t firstentry)

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

       It is mandatory 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

void UpdateFormulaLeaves()

     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

                     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)
                    Int_t GetDimension() const
                     TH1* GetHistogram() const
                    Int_t GetNfill() const
              const char* GetScanFileName() const
            TTreeFormula* GetSelect() const
                    Int_t GetSelectedRows() const
               TSelector* GetSelector() 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* GetV4() 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&)

Author: Rene Brun 12/01/96
Last update: root/treeplayer:$Name: $:$Id: TTreePlayer.cxx,v 1.159 2004/07/09 04:40:49 brun Exp $
Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *