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Workbook for BaBar Offline Users - Analysis in ROOT II

In this section of the Workbook the information presented in the first ROOT section Analysis in ROOT I is extended to include fitting histograms with functions, applying cuts, macros, and an introduction to the ROOT Object Browser. Most of the information in this section was taken from the documents listed in ROOT I.


Further Manipulations of Histograms

For this exercise we will need a root file with more than one 1-D histogram. The file example.root will suffice (you can copy it from the link by right-clicking on here and selecting "save link as" - and remember to be careful which directory you save the file into). At this time you should also download the example file myrootfile.root which will be used in later sections of this tutorial.

Now start up a new ROOT session with bbrroot and load the root file with

   TFile *f = new TFile("example.root");   //load the file

This ROOT file has a more complicated directory structure than the simple file used in the first Workbook section on ROOT. To have a look around the directories and files in example.root use

   f->ls();                          (list the directories, histograms and ntuples)
In this example file there are lots of histograms, but they are all contained in directories. The output from the previous command should look like:
root [1] f->ls();
TFile**         example.root    
 TFile*         example.root    
  KEY: TDirectory       event_dir;1     Event Property Histograms
  KEY: TDirectory       pipi_dir;1      pi pi Histograms
  KEY: TDirectory       bkg_dir;1       Background events
  KEY: TDirectory       track_dir;1     Track Histograms
  KEY: TDirectory       gamma_dir;1     gamma Histograms
  KEY: TDirectory       pi0_dir;1       pi0 Histograms
To change into a directory, say, event_dir:
   gDirectory->cd("event_dir");    //or, possibly best
   f->cd("event_dir");    //where f is the name of the currently
                             //open file
(Note that anything that follows "//" is a comment and is ignored by the ROOT interpreter.) You can now list the contents of that directory with
gDirectory->ls();        //or
The output this time lists the available directories, but also the histograms in the open directory (event_dir):

root [5] f->ls()
TFile**         example.root
 TFile*         example.root
  TDirectory*           event_dir       Event Property Histograms
   KEY: TH1F    eTag_p_CM;1     eTag_p_CM
  KEY: TDirectory       event_dir;1     Event Property Histograms
  KEY: TDirectory       pipi_dir;1      pi pi Histograms
  KEY: TDirectory       bkg_dir;1       Background events
  KEY: TDirectory       track_dir;1     Track Histograms
  KEY: TDirectory       gamma_dir;1     gamma Histograms
  KEY: TDirectory       pi0_dir;1       pi0 Histograms

To change into the base directory of the ROOT file:

If you don't use a semi-colon at the end of the line, you'll get a message like:
This is a return value indicating if the operation (changing directory) has been successfully executed. If the value is 0, it will be accompanied by an error message - usually a message saying you haven't entered a valid directory name). Now change into the "gamma_dir" directory:
list its contents:
root [12] f->ls()                 
TDirectory*             gamma_dir       gamma Histograms
 OBJ: TH2F      gammaEvsMassM   gammaEvsMassM : 0
 KEY: TH1F      num_good_neutM;1        num_good_neutM
 KEY: TH1F      num_good_neutD;1        num_good_neutD
 KEY: TH1F      lateralMomentM38;1      Cluster Lateral Moment
 KEY: TH1F      lateralMomentD38;1      Cluster Lateral Moment
 KEY: TH1F      lateralMomentSig38;1    Cluster Lateral Moment
 KEY: TH1F      gammaEM38;1     gammaEM
 KEY: TH1F      gammaED38;1     gammaED
 KEY: TH1F      gammaESig38;1   gammaESig
 KEY: TH1F      nCrysM38;1      nCrysM
 KEY: TH1F      nCrysD38;1      nCrysD
 KEY: TH1F      nCrysSig38;1    nCrysSig
 KEY: TH1F      gammaCosThM38;1 gammaCosThM
 KEY: TH1F      gammaCosThD38;1 gammaCosThD
 KEY: TH1F      gammaCosThSig38;1       gammaCosThSig
 KEY: TH1F      lateralMomentM;1        Cluster Lateral Moment
 KEY: TH1F      lateralMomentD;1        Cluster Lateral Moment
 KEY: TH1F      lateralMomentSig;1      Cluster Lateral Moment
 KEY: TH1F      gammaEM;1       gammaEM
 KEY: TH1F      gammaED;1       gammaED
 KEY: TH1F      gammaESig;1     gammaESig
 KEY: TH1F      gammaEMFine;1   gammaEMFine
 KEY: TH1F      gammaEDFine;1   gammaEDFine
 KEY: TH1F      gammaESigFine;1 gammaESigFine
 KEY: TH2F      gammaEvsMassD;1 gammaEvsMassD
 KEY: TH2F      gammaEvsMassM;1 gammaEvsMassM
 KEY: TH2F      gammaEvsMassSig;1       gammaEvsMassSig
 KEY: TH1F      nCrysM;1        nCrysM
 KEY: TH1F      nCrysD;1        nCrysD
 KEY: TH1F      nCrysSig;1      nCrysSig
 KEY: TH1F      gammaThetaM;1   gammaThetaM
 KEY: TH1F      gammaThetaD;1   gammaThetaD
 KEY: TH1F      gammaThetaSig;1 gammaThetaSig
 KEY: TH1F      gammaCosThM;1   gammaCosThM
 KEY: TH1F      gammaCosThD;1   gammaCosThD
 KEY: TH1F      gammaCosThSig;1 gammaCosThSig
and display a couple of histograms:
gammaEvsMassM.Draw("surf4");  //display 2-d histogram (surf4 is a
                              //display command specifying a surface style)
nCrysM.Draw();         //display 1-d histogram called nCrysD

Note that you can always check which directory you are in by typing

Where, when you have file "f" open, and are in its root directory, you should see:
root [42] gDirectory->pwd()  

Changing the way your histogram looks

The following commands alter the way your histogram is displayed. Each time you change the display attributes, for example, change between logarithmic and linear axes, you will need to refresh the display with the command:

To zoom and unzoom:

   nCrysM->SetAxisRange(10, 30.5, "x");
   gPad->Modified();                      // Needs a refresh from the command line
To change to logarithmic axes (note that this is a display command, not a histogram method, so won't affect any fits):
To set up gridlines:
These options are controlled by boolean variables, and can be switched off using a "0" option, e.g.:
To change the drawing style (e.g.markers, color)
   nCrysM->Draw("p");                   //draw with points - not joined up
   nCrysM->SetMarkerStyle(20);          //round dots 
   nCrysM->SetMarkerSize(1.);           //fat, round dots
   nCrysM->SetMarkerColor(kBlue);       //fat, blue, round dots
To enlarge axis labels and add axis titles:
   nCrysM->SetTitleSize(0.06, "x");             // Title size, offset and text
   nCrysM->SetTitleOffset(1., "x");
   nCrysM->SetXTitle("Axis title text");
You can also set axis titles with
    nCrysM->GetXaxis()->CenterTitle(1);  // center the name of the x-axis
This command structure should start to become familiar pretty quickly: you access the object you are interested in (in this case, the x-axis object), then you set one of its attributes (SetTitle, CenterTitle,...) (Note: (e)ps output can be missing if you cut off too much, so be sure that you have sufficient margins.) You can also change the y-axis range of your histogram either before or after drawing the histogra using the functions TH1F::SetMinimum(minValue) and TH1F::SetMaximum(maxValue), e.g.
You can also do it with the GUI (see below), moving the cursor over the axis and left-clicking. A pair of lines will appear, one staying where you started, the other following your mouse movements.

You can modify the binning of your histo with the command:

where you need to input actual numbers here.


In addition to ROOT's built-in functions, you can define functions of your own. There are one-, two-, and three-dimensional functions (TF1, TF2 and TF3).

To define a function with predefined components:

   TF1 *f1a = new TF1("f1a","sin(x)", -5., 5.);
   // built-in, this defines the function over the range -5<x<+5
   TF1 *f1b = new TF1("f1b","x*sin(x)", -2., 2.);    // combined
   TF1 *f1c = new TF1("f1c", "[0]*x + [1] + gaus(2)",0.,15.);
gaus() is a 3-parameter Gaussian function used for fitting. The combination here is a Gaussian plus a linear function. gaus(2) means that the parameter numbering on the Gaussian starts at 2. Here f1c is defined with 5 parameters, which by default are set to zero, but which you can set before drawing the function. You can also use functions defined with parameters for fitting, and use the fitting to determine the best values for the parameters. For the 5-parameter function above, this is done with, e.g.
   f1c->SetParameters(0.1, 10., 50., 0.5, 0.01);
Now define a 2-dimensional function:
   TF2 *f2 = new TF2("f2", "sin(x)*sin(y)", -10., 10., -10., 10.);
To draw a 1D function, say f1c, enter:
The above command calls the default drawing option for functions. Other drawing options for functions include:
  f1c->Draw("p");    // use markers
  f1c->Draw("h");    // histogram
Note that you may have to set the markers to something sensible before getting output. See above for instructions on how to do this.

2D functions are handled in a very similar manner

 f2.Draw();          //2-d projection - not very impressive
 f2.Draw("surf4");   // surface plot - much nicer
surf1-5 are different surface plot options. To change the colours, you can do, e.g.
gStyle->SetPalette(1)   //and plot again

How to generate histograms from functions

To generate a 1D histogram from a 1D function and plot it:
   TF1 *f1=new TF1("f1","sin(x)",0,10);
   f1.Draw();    // need to draw the function first!
To generate a 2D histogram from a 2D function and plot it:
For the 1D function the smooth function line will be jagged in a histo, and for the 2D function, the only clear difference is possibly the appearance of a statistics box for the histogrammed function (depending on your stats settings).

Errors, already defined functions/histograms/...

Sometimes you'll want to use the same name for a function definition - usually when you're finished with the first. This is not a problem - you simply delete the first function, e.g.
This function now no longer exists and cannot be called, plotted, etc. You can then define f2 afresh, or using something else, e.g.
TF2 *f2 = new TF2("fun2","sin(x)*sin(y)",0.,3.14,0.,3.14);

How to get greek characters and primes into an axis title

For example, with the ROOT file we opened at the start of this session:
Apart from the newest versions of ROOT, it is not possible to include primes in axis or graph titles. Later versions have this facility with the command #prime. Otherwise, the best workaround found so far is to put a comma as a superscript.

Plotting Data Points

The official ROOT website provides many useful tutorials and HOWTOs for a wide range of ROOT tasks. One of these is a macro for reading in data from an ascii file and creating from it a ROOT file with a histogram and an ntuple. That example is reproduced here.

The macro basic.C can be used to read in data from an ascii file containing numbers laid out in columns. The file basic.C is a simple macro which expects the input to come from a simple ascii file, called basic.dat containing, in this example, three columns of numbers.

To run this macro, from within ROOT execute the following command:

.x basic.C

The file reads in the numbers from basic.dat, histograms the values from the first column, and writes all the entries into an ntuple. This output, the histogram and ntuple, are saved to a file called basic.root. This output file can then be studied, ntuple entries printed, and cuts performed on the three histogrammed quantities just like any other ROOT file.

Fitting a Histogram with ROOT

You can use pre-defined functions, or user-defined functions, or compositions of pre-defined functions to fit histograms. ROOT uses the minimisation package Minuit for fitting.

How to fit histograms with predefined functions (these commands assume you are running ROOT from the same directory as you have saved the example file myrootfile.root):

TFile f("myrootfile.root");
h1->Fit("landau","R", "", 1., 5.);
                         // where "R" indicates to fit only in
                         // a range, given in the last two arguments
h1->Fit("landau","R", "P", 1., 5.);
                                        // where "P" is an option indicating
                                        // to plot markers instead of histograms

How to fit with a user-defined function

In a file myfunc.C define

double myfunc(double *x, double *par) {
double arg = 0;
if (par[2]) arg = (x[0] - par[1])/par[2];
return par[0]*TMath::Exp(-0.5*arg*arg);
Load this macro into ROOT and perform a fit with this function
.L myfunc.C
TF1 *f1 = new TF1("f1",myfunc, -1., 1., 3); // where 3 is the number of
                                                      // parameters for the function
f1->SetParameters(10.,h1->GetMean(), h1->GetRMS());
A further example (from the ROOT site) of generating histograms with random numbers from a function and then fitting those histograms is provided here. There are some more examples of fits and functions reproduced here.

How to use the Fit Panel

Move the pointer over the histogram line (the cursor should change from cross to arrow) and click on the right mouse button. A context menu on TH1 should appear, from which you can choose FitPanel.


The FitPanel "slider" can be used to graphically restrict the fit range. The slider is the grey bar near the bottom of the fit panel, directly above the words "Fit", "Default", and "Close". If you move the mouse pointer over this slider, at the ends of its ranges the pointer changes from a cross to "|<-" at the left-hand edge and "->|" at the right-hand edge. When the pointer is displayed in this way, you can change the fit ranges by holding down the left mouse button and dragging the left- or right-hand edge of the slider to a new position. The changing fit range is shown graphically on your canvas as a vertical line that moves along as you move the slider.

Related Documents

Using Cuts

To provide concrete examples of how to use cuts in ROOT, the file taufile.root is required. It can be downloaded from this link.

The ROOT file in this example contains two separate ntuples, or trees. Trees are discussed later in this workbook chapter, but for now, is it sufficienct to follow the instructions below to access one of the trees in this file.

First open the file and access the tree called h2013:

TFile* myfile = new TFile("taufile.root");
TTree* mytree = (TTree*)gDirectory->Get("h2013");

A cut is defined in ROOT by way of a TCut object. For example,

TCut *cut1= new TCut("nPi0s>2");

where here the fully correct C++ syntax is provided to allow this command to be used in a macro. "nPi0s" is a property of the objects about which information is to be plotted. This could be used, for example, to plot thrust vs the minimum angle between particles in each hemisphere of an event for events, but only selecting those events in which there were more than two pi0s detected. The object would then be drawn with, e.g.

c1->Update(); //update canvas called c1

In this case it is assumed that there is one entry in the ntuple (compare: one row in a spreadsheet, where the columns represent different information about that entry). Note also that in the Draw(...) function call, the actual TCut object (*cut1) is passed, rather than just the pointer (cut1).

Also, to plot only a section of the data:


The above command displays "ch_px_cms", where "ch_px_cms" is greater than zero. (Compare with the result when plotting without the cut). In this case, the cut wasn't defined as a TCut object, instead it was simply included in the Draw(...) function call, in quotes.

You can use more than one cut, using logical operators to choose the inter-relation of the cuts, for example


While you can clearly use cuts without having to define a TCut object, it does become cumbersome, particularly if several cuts are to be used, or if the cut is to be used repeatedly and the value of it might be changed. In which case it is much better to define several TCut objects at the start of your code and only have to edit them in one well-defined place.

Related Documents

Using the Graphical User Interface: Canvas, Pad, Object Browser

The ROOT Object Browser

The ROOT information in the Workbook has so far discussed using command line entries to display and manipulate histograms and functions in ROOT. There is also a ROOT Object Browser which provides a graphical view of your files and allows you to navigate through large ROOT ntuples and directories quickly.

A ROOT Object Browser is instantiated with a command like

TBrowser* tb = new TBrowser();
or, simply
TBrowser tb
A new Object Browser window should appear which looks like this


Using a specific example, download the file SimpleTree.root (which we'll actually generate later in this tutorial) and start ROOT in the directory where you have put SimpleTree.root.

Now start a TBrowser with:

root[0] TBrowser tb
Open the file by selecting File->Open in the menu bar and choosing "SimpleTree.root".

You can now look at the contents of this file by double-clicking on ROOT files (in the right-hand pane of the TBrowser) and then double-clicking on the filename. This file contains a single tree (see the Trees section later in this WorkBook chapter) called SimpleTree. To look at the contents of the tree, double-click on that. The display will now list the contents of the tree - namely E, Px, Py, Pz, n.

You can display the data in any of these leaves of the tree by double-clicking on the name of the leaf. Try this by double-clicking on the Px label. You should see a histogram which looks like this file.

Now click on Options in the menu bar of the canvas and select Event Status. Click on the Canvas again and point to the histogram line with the mouse pointer. You should see a display of the bin contents (and other things) in the lowest row of the canvas - this is particularly useful when looking at a log plot to determine the x and y coordinates of a particular point on a line.

Now get the Editor by clicking on Edit->Editor in the menu bar of the canvas containing the histogram:


Get a DrawPanel by moving the mouse pointer to the histogram line in any bin (the pointer should change from a cross to a pointer), clicking the right mouse button and choosing DrawPanel:


Have a play with some of the options (lego1 is nice) by clicking on the option and then clicking on "Draw".

Get a FitPanel by moving the mouse pointer to the histogram line in any bin (the pointer should change from a cross to a pointer), clicking the right mouse button and choosing FitPanel:


Again, have a go by clicking some options and then clicking "Fit" (we'll do a bit more with this later in this Workbook Chapter.

Back in the ROOT Browser: Show the variables contained in the tree by double clicking on the tree icon (SimpleTree):


Display the variable by double-clicking on its name:


Try clicking the right mouse button on the SimpleTree icon, you'll get a context menu. To start the GUI for working with Trees, choose StartViewer from this context menu. (If a pop-up window appears prompting you for width (ww) and height (wh) settings, select OK in that window.

The ROOT Canvas

We saw earlier how to draw a histogram. The graphics window which your histogram was displayed in is called a "canvas". (This canvas is similar to the HIGZ window in PAW.) By default, the first canvas generated in a ROOT session has the name c1. In this section we will see some of the power of the ROOT canvas

First load in a root file as above, e.g. myrootfile.root, and display the histogram:

You can enlarge the canvas like any window by click-and-dragging e.g. a corner of the window containing the canvas.

By right-clicking on different areas of the canvas, you are presented with a drop-down menu with different options for displaying your picture. For example (assuming the graph is displayed with a legend and a stats box):
Click on Options
x-axisattributes of x-axis
y-axisattributes of y-axis
graph titletitle display
area inside histogramhistogram attributes such as fill style
area outside histogramcanvas display options such as log scales
legend boxlegend display
stats boxstats box display
You can also left-click-and-hold and drag the legend and stats boxes around the canvas, and resize them.

How to divide a Canvas into smaller canvases (aka zone 2 2 in PAW)

Assuming you have a canvas c1, the CINT way is

c1->Divide(2,2);    // divisions in x and y
To select the subdivision of the canvas to change the focus to, the command-line entry required is, for example,
c1->cd(3);  //where c1 is the canvas name, and 3 is one of
                        //the subdivisions of the 2x2 canvas

(You can test this by plotting your histogram again, h1->Draw(); and seeing that it appears in the 3rd place.)

The GUI-way is to right-button click on the canvas, choose "Properties", then select "Divide" and fill in the nx and ny attributes. You can then move the mouse pointer over the pad you want to access and click the middle button.


A "Pad" is a subdivision of a canvas. (Similar to a zone in PAW.) By default each canvas is created with one pad which fills the entire canvas. Your histograms and other text and graphics objects are drawn on a pad. You can draw several histograms on one canvas by creating more pads. Opening a new pad also allows the drawing of insets, as in the example that follows (where here we assume you have a canvas c1 (the default canvas), and also that you have the example file example.root in the directory that you are running PAW from):
   c1->Clear();                //clear the contents of the current canvas
   TFile f("example.root");;           //just to check what's there"pi0_dir");  //to change into a subdirectory of the file
   TPad *npad = new TPad("npad", "", 0.6, 0.2, 0.9, 0.5);

The last set of commands creates a 2x2 pad and steps through each element of the pad drawing a different histogram. The output should look like this:


The following command clears the canvas and returns it to having just one pad on the canvas:


CINT 2: CINT Revisited

CINT is quite sophisticated, but not perfect. You can crash it badly. You will restart ROOT much more often than PAW. You need some experience to know when you can continue with CINT after having had an error. Some people (sometimes) would not bet on results obtained with CINT. Keep that in mind when your macro gets complicated. Nothing beats the security and reassurance of a trustworthy C++ compiler.

That said, CINT is great for all the interactive display stuff usually needed for getting plots into a form suited for presentation.

CINT completes partially typed commands, provides you with a list of arguments a given function expects and completes filenames you have to enter. Try

root[0] TFi<TAB>
root[1] TFile f(<TAB>
root[2] TFile f("fr<TAB>
where <TAB> indicates you have to hit the TAB key.

Further, if you type in a variable followed by an arrow, for example:

gStyle->   and then enter a tab
This will print out a listing of all the methods and members of gStyle, and lists all the things that you can dowith gStyle. You can continue it by typing in
etc. If you enter the name of a function, say
gStyle->SetOptStat(    and then a tab
a list of the parameters that are expected for this function will appear. If the method has multiple definitions, called with different parameter lists, then all of them are displayed.

CINT allows you to scroll through your history of commands with the arrow keys (just like PAW). It keeps this history between sessions and you can scroll through previous sessions (unlike PAW). This is a very useful feature.

CINT also provides you with a search facility in its history, accessible with <Ctrl-r>. Try

root[3] <CTRL-r> TF


The equivalent of pawlogon.kumac. It is good to keep it as short as possible.


This text file stores a history of the commands you entered during a ROOT session. These commands can be copied out of this text file and into a macro (see below) to be used later.

Using Macros in ROOT

The aim of this section is to show how to create macros in ROOT. Macros are user-defined functions that are written in separate files and then loaded and executed in a ROOT session. Several functions can be defined in a given macro, and once the macro has been loaded, the functions defined in these files can be called. A large analysis job will usually call several macros to carry out individual tasks.

In the section about fitting you created a macro called myfunc.C to define a new function, myfunc();. A macro is a C++ function defined with the syntax:

return_type function_name(arg1_type arg1_name, arg2_type,
arg2_name, ...) {
commands with ";%quot; at the end of each line;
Macros can be loaded with the command
   .L mymacro.C
And the macro is then called with the command
function_name(parm1, parm2...);
You can also load and execute statements saved in a file using
   .x myfile.C
For example, load the macro myfunc.C you created earlier with
  .L myfunc.C
and define a function with it:
   TF1 *f1 = new TF1("f1", myfunc, -1.,1., 3);
                         // here 3 is the number of parameters for the function
You can now use this function for fitting, plot it, etc.

You can also write unnamed macros as a bunch of commands, enclosed in braces, and with each line ending in a semi-colon, and put them in a file (e.g. macro1.C)

// macro.C
cout << "hello world" <<
and execute them in a ROOT session with
.x macro1.C
You can put functions into a file e.g. macro2.C
void helloWorld() {
cout << "Hello World" << endl;
and load and execute any function in that file in two steps:
root[2] .L macro2.C
root[3] helloWorld()
By the way, after you loaded the file, ROOT knows about your function, so instead of the above, try to hit <TAB>:
root[3] helloWo<TAB>
Further example macros are here. These files are copies of the ROOT distribution examples.

Booking and Filling Histograms in the BaBar Framework

There are various BaBar-specific tools for booking and filling ROOT histograms in the BaBar framework, and a conventional way to include the required statements in BaBar code. This is described in detail in babar_histos.html.

Linking Multiple ROOT Files Together

You can link multiple ROOT files together using TChain, provided those files have the same internal structure. In that way, you can treat them as one contiguous ROOT file. For example, if you have two ROOT files, fil1.root and fil2.root, you can link them using the command:
input_data( TChain* dataChain )

ROOT Trees

As discussed in the Workbook section, ROOT I, a ROOT Tree is similar to a PAW Ntuple. It has branches which can hold many other objects, for example vectors. An ntuple in ROOT (TNtuple) is just a simple TTree, where each branch contains floating point (Float_t) data.

A single ROOT file can hold several trees, as in the example file taufile.root first introduced in the Cuts section in this workbook chapter. Each tree is independent, like an individual file, and it is not possible to plot quantities in one tree subject to cuts on quantities in another tree.

Opening the example file:

root [0] TFile *myfile=new TFile("taufile.root");

We can list the objects (trees and histograms) contained in the file:

root [1]
TFile**         taufile.root    HBOOK file: .../tau-1571.hbook converted to ROOT
 TFile*         taufile.root    HBOOK file: .../tau-1571.hbook converted to ROOT
  KEY: TTree    h2013;1 1-3
  KEY: TTree    h2033;1 3-3

This tells you the irrelevant information that this file was actually made by converting a PAW file to ROOT format. It also shows that there are two trees in the file, h2013 and h2033, and no histograms.

To access the contents of a tree, you can make a tree object which holds the contents of one of the trees in the file:   //make sure ROOT's focus is on  myfile
TTree* mytree = (TTree*)gDirectory->Get("h2013");

By calling TTree functions of the mytree object, you can now access the contents of the tree h2013 from taufile.root. For example, to get a list of branch or leaf names, enter:

You can also inspect the contents of a tree with the TBrowser described here.

How to Book and Fill a Tree

The macro roottest.C is a slightly-modified version of the example from a SLAC ROOT tutorial.

Executing the example with

.x roottest.C
creates a tree with up to 200,000 variables per event. It creates a tree called "SimpleTree" which contains 5 branches, n, E, Px, Py, Pz. The last 4 entries are array-valued entries, containing n elements for each entry, which could be the energy and 3 momenta of tracks for BaBar events containing n tracks per event. The energy and momentum components have Gaussian distributions, as defined in the macro.

The resulting tree is written into a file called SimpleTree.root. This root file, and the tree in it can be inspected in the manner described in this Workbook chapter, and in ROOT I.

Printing ROOT output directly to a file

It is often desirable to save a copy of the ascii ROOT output which appears during an interactive ROOT session (in analogy with the OUTPUT_LP facility in PAW). There are two easy ways to print this output to a text file:
  • Piping macro output to a text file
You can simply execute a macro which contains all the commands you want to save the responses from and redirect that to a file with the command
.x > outFile.txt
  • Sending selected output to a text file
So save only selected command outputs to a text file, another option is to use commands of the form:
  ofstream fout;
  int count;"outputFile.dat");
  for (count=0; count<total; ++count) {
   fout << sig[count].name  << "  "
        << sig[count].slope << "  "
	<< sig[count].coeff << endl;
Finally, you can dump the output of an ntuple directly to a text file with the commands
             ntp->Print(); > output.log
   ntp1->Scan("momentum"); > output.log
to get the output (of a tree ntp1) into a file. Don't forget the ';'.

Other Useful ROOT Commands

To execute shell command in a shell
   .! command
for example,
 .! ls
will list the contents of the current shell directory, i.e. the directory from which you started the present ROOT session. To display a message:

RooFit - ROOT-based Modelling Toolkit

The RooFit packages provide a toolkit for modelling the expected distribution of events in a physics analysis. Models can be used to perform likelihood fits, produce plots, and generate "toy Monte Carlo" samples for various studies. The RooFit tools are integrated with the object-oriented and interactive ROOT environment.

Follow the link above for instructions for setting up and using RooFit for BaBar analyses. During BaBar Collaboration meetings, there are often RooFit tutorials conducted by experts.

General Related Documents:

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Author: Jenny Williams
Contributions taken from various hypernews postings and user feedback

Last modification: 13 June 2005
Last significant update: 10 February 2003