Overview of fitting method

The fitting method folder is structured in folders and main files. Main files are those ones that are used to run the most important codes. Below is a list of folders presented in this method and the files encontered here. It is important to note that this code has been tested on root 6.22/00.

Fitting method folder structure

The folders contained in fitting method are described below.

Folder	Purpose
📂 DATA	Where .root with data should be placed for measuring efficiency
📂 src	Where important files related to main code are keeped
└ 📂 dofits	Here it keeps files that are responsible to do the fitting over invariant masses histograms
📂 tests	Some teste made during the development of this tool
📂 results	This folder stores the results output and it is created when any code finnish running

Main files

There are six main files in the fitting method. For simple results like the ones obtained in sideband subtraction method the file used is efficiency.cpp.

Main files are explained below.

📄 simplify_data.cpp

The simplify_data.cpp file, as the name sugest, simplify a DATA file obtained from this Tag and Probe tool. It is necessary to simplify due RooFit limitations where fitting method codes here used are based on.

There are two lines responsable for input and output file:

TFile *file0  = TFile::Open("INPUT_FILE_PATH.root");

TFile *fileIO = TFile::Open("OUTPUT_FILE_PATH.root","RECREATE");

Every user should run this code firstly to simplify .root files in order to use it in fitting method.

The input files here are provenient from the main Tag and Probe tool in this repository. If you want to get a new ntuple, you should run it.

📄 efficiency.cpp

This file is responsible to measure the efficiency simple by fitting method as described in this fitting method section.

Choosing ressonance

Here it include the file that is responsible to fit the ressonance and return the yield obtained with error.

//Change if you need
#include "src/dofits/DoFit_Jpsi_Run.h"

By default out tool keeps all ressonance fit in the folder src/dofits. There are some example there for specific ressonances and fits.

There are two main parameters to control this code.

//Which Muon Id do you want to study?
string MuonId   = "trackerMuon";

The string MuonId supports "trackerMuon", "standaloneMuon" and "globalMuon" values.

//Which quantity do you want to use?
string quantity = "Pt";     double bins[] = {0., 2.0, 3.4, 4.0, 4.4, 4.7, 5.0, 5.6, 5.8, 6.0, 6.2, 6.4, 6.6, 6.8, 7.3, 9.5, 13.0, 17.0, 40.};

string quantity supports "Pt", "Eta" and "Phi" values.

double bins[] is used to set histogram bins limits. In the example above, the first bin is [0., 2.), the second is [2., 4.) and so on.

Output

There are two output folders in this file by default. They are defined in those lines of code:

//Path where is going to save results png for every bin 
const char* path_bins_fit_folder = "results/bins_fit/efficiency/";

path_bins_fit_folder refers to the path where each individual fit of bins will be stored as .png. In this folder you can find every fit made in this method.

//Path where is going to save efficiency 
string directoryToSave = string("results/efficiencies/efficiency/") + output_folder_name + string("/");

The directoryToSave stores the path to save the efficiency result. It is saved as a .root file containing passing and total histograms as well the efficiency result histogram.

Informations about the output is printed at end of running.

📄 loop_over_efficiencies.cpp

The purpose of this code is rerun the efficiency.cpp for differents configurations. This code is not recommended for systematic calculations indeed and it was firstly created for systematic studies only.

The importants variables to keep in mind are listed below

Type	Name	Purpose
double	default_min	the minimum invariant mass window postion
double	default_max	the maximum invariant mass window postion
bool	should_loop_muon_id	if true, it loops over all muons id (tracking, standalone, global)
bool	should_loop_settings	if true, it loops over all settings presented in set_settings() function
int	setting	if should_loop_settings is false, it uses only this setting number
bool	exactly	This only affect the name of output plots inside .root. Its recommended to keep it set to false

set_settings(...)

It is one of four functions presented in this code. Its is called by:

void set_settings(int index, bool exactly = false)

Inside this function are preset settings that this file runs over. Each setting is associated with a number here named as index. This function is responsible to set the index configuration to the efficiency for running the efficiency.cpp file.

loop_settings()

void loop_settings()

If should_loop_muon_id is true, this function is called. It loops over all muon ids: tracking, standalone, global.

loop_muon_id()

void loop_muon_id()

If should_loop_settings is true, this function is called. It loops over all settings preset in set_settings(...) function.

loop_over_efficiencies()

void loop_over_efficiencies()

It is the main function of this file. It is the function which calls every other function when it is needed.

📄 plot_sys_efficiency.cpp

The plot_sys_efficiency.cpp code creates a single .root with variations made. Unlike the previous code, the loop_over_efficiencies.cpp, that makes each source of uncertainty be in a separate .root, this one puts all of them in a single .root. This code has been further optimized than his precursor and also as a differential it already calculates the systematic uncertainty. Below it is specified main variables used in this code.

//Which Muon Id do you want to study?
string MuonId   = "trackerMuon";

The string MuonId supports "trackerMuon", "standaloneMuon" and "globalMuon" values.

//Which quantity do you want to use?
string quantity = "Pt";     double bins[] = {0., 2.0, 3.4, 4.0, 4.4, 4.7, 5.0, 5.6, 5.8, 6.0, 6.2, 6.4, 6.6, 6.8, 7.3, 9.5, 13.0, 17.0, 40.};

string quantity supports "Pt", "Eta" and "Phi" values.

double bins[] is used to set histogram bins limits. In the example above, the first bin is [0., 2.), the second is [2., 4.) and so on.

Inside plot_sys_efficiency(), there is some useful variables too:

Type	Name	Purpose
string	path_bins_fit_folder	Stores the path to the output folder where .png of fit for each bin made will be
string	directoryToSave	Stores the path to output file

📄 overplot_efficiencies.cpp

The overplot_efficiencies.cpp code will take the results of the previous topic and make a single graph containing all its variations and will output a .png containing the graph.

All main variables in this file are in overplot_efficiencies() function

Type	Name	Purpose
const char*	input_folder_name	Stores the path to input folder where .root is
const char*	output_folder_name	Stores the path to output folder
string	MuonId	It accepts values of "trackerMuon", "standaloneMuon" and "globalMuon"
string	quantity	It accepts values of "Pt", "Eta" and "Phi"

Remeber when selecting MuonId and quantity to run plot_sys_efficiency.cpp before with same configurations.

📄 plot_sys_efficiency_2d.cpp

In order to calculate systematic uncertainties in 2D, it was necessary to create another code: the plot_sys_efficiency_2d.cpp. It has a .root output containing the efficiency histograms that can be viewed through the new TBrowser on root command.

The variables in this file is shown below:

Type	Name	Purpose
string	MuonId	It accepts values of "trackerMuon", "standaloneMuon" and "globalMuon"
string	xquantity	It accepts values of "Pt", "Eta" and "Phi" for horizontal axis
double[]	xbins	is used to set histogram bins limits for horizontal axis
string	yquantity	It accepts values of "Pt", "Eta" and "Phi" for vertical axis
double[]	ybins	is used to set histogram bins limits for vertical axis
string	path_bins_fit_folder	Stores the path folder where is going to save fit results png for every bin
const char*	output_folder_name	Stores the path to output folder where is going to save the 2D efficiency result