This collection of c++
and python 3+
programs is used to (1) study the background component in simulated (Pythia-8) diffractive events at ALICE and (2)
to reject the background component in the measured data.
- The background study (1) builds upon and uses
c++
classes stored in./lib/
. These classes range from base classes necessary to execute tasks to plotting classes. In oder to be able to use these classes, therootlogon
-file has to be modified. Seerootlogon-example.C
for the necessary lines which have to be added. - In order to study the background component ALICE tasks are available in
./tasks/
. These tasks require an additional folder containing the Offline Analysis DataBase - anOADB
folder - to be placed into the./tasks/
folder. A short description on how to run the tasks is presented in the main folder./tasks/README.md
. - If the EventDef class has been used to create a precise list of the decay modes with their respective sub-decays then a
decaymodes.tex
file is created (located in the respective task folder where the.go
script has been evoked) which is a table written in latex format. This table can be transferred into a.pdf
format by copying thedecaymodes.tex
file into the./latex/
folder and invoking./latex/compile.sh
. The pdf file is stored in./latex/output/doc.pdf
. - Plotting is usually done via a special class saved in
./lib
called the PlotTask class. It can be used to make a wide variety of plots (e.g. ratio plots, significance plots, etc.). It can be used to plot the task-output histograms as well standarad histograms saved in a.root
format. The aim of this class is to plot histograms in a uniform style. With multiple implemented functions (see./lib/PlotTask.h
) a plot can be made more quickly and simply without having to deal with individual root funtions for individual hisotgrams. In the folder./plottingscripts/
some macros can be found which make use of this class. - Additional smaller
c++
macros which are not crucial to the background study but may become useful in the study of background events are saved in./misc
The background rejection is done with machine learning methods with python 3+
.
- In oder to use the data stored in the CEP-buffers (i.e. CEPEventBuffer, CEPTrackBuffer,and the raw buffers) a few steps have to be taken.
The necessary programs to do so are stored in the folder
./root2pyt/
and the procedure is described there. - After the data is converted into the special format (refered to as the event-dictionary) machine learning algorithms (neural networks using the
Keras
software framework) can be trained using the programs (and instructions) provided in the./ml/
folder.