                                               G. Cowan
					       RHUL Physics
					       19 November, 2008


                      TMVA Examples
                      -------------

The programs in this directory contain simple examples of multivariate
analyses using routines in the TMVA package.  The examples are
standalone C++ programs that must be linked with the ROOT and TMVA
libraries.  Normally TMVA should be included automatically with ROOT.

To build the programs, first download the files copying the directory
structure.  Alternatively you can copy the tarball tmvaExamples.tar to
your area and type

tar -xvf tmvaExamples.tar

This will automatically place everything in its correct subdirectory.

To build the programs, go into the corresponding subdirectory and type
gmake.  The ROOT environment needs to be set up first -- consult your
local expert.

Note that the subdirectory inc needs to contain the header file
Event.h.  This declares the class Event, which corresponds to a single
data event.  To allow one to store the data easily in a file, this
class contains only data members, no member functions.

For more information on the TMVA methods, see the website

 http://tmva.sourceforge.net/

The examples in the individual subdirectories are:

generateData -- generates data according to a 3-dimensional
	        distribution for two different hypotheses
		(signal and background) and stores the
		result in a root file (as two TTree objects).

readData --     a test program to read the data.  You can
		ignore this one.

tmvaTrain --    reads in the root file and trains two
		simple multivariate discriminators:  a
		Fisher discriminant and a multilayer 
		perceptron (neural network).  The 
		coefficients for the discriminant functions
		are stored in a subdirectory ./train/weights/.

analyzeData --  reads in n-tuples of signal and background
		data and computes the discriminating variable.
		The user can select events, compute efficiency,
		purity, etc.
