How to Rtrk Double Ratios

Introduction

One way to asses systematic uncertainties of jet substructure variables is the Rtrk methodology. The following is a brief instruction for the steps necessary to produce double ratios that serve as input for the final estimate of these uncertainties.

Running over DxAODs

First Setup

Download the DeriveJMSR tool from git:

git clone ssh://git@gitlab.cern.ch:7999/amelzer/rtrk.git

Setup the newest release:

cd rtrk
setupATLAS
showVersions|grep AthAnalysisBase
lsetup 'rcsetup Base,2.4.19'

Compile everything:

rc find_packages
rc compile

Check that the GRL, the PRW config files and the lumicalc files are available in the data directory

Now you can run the code:

doJMSUncertainties OutputFolderName ConfigFiles/basicSettings.config inputFile.list [mode] [gridOutputName]

OutputFolderName: all histograms and root files with trees will be saved here
data/basicSettings.config : configFile containing e.g. the jet collections you want to run over and other variables you might want to set
inputFile.list: list with input files to run over e.g. /pnfs/desy.de/atlas/dq2/atlaslocalgroupdisk/rucio/mc15_13TeV/d3/44/DAOD_JETM8.08623892._000001.pool.root.1
[mode]: default is "local", optional "grid"
[gridOutputName]: e.g. user.jdoe.my_run_p0001.root (see naming convention)

Available Variables

Moment xAOD Jet attribute names
N-subjettiness Tau1, Tau2, Tau3, Tau21, Tau32, Tau1_wta, Tau2_wta, Tau3_wta, Tau21_wta, Tau32_wta
kT splitting scale Split12, Split23, Split34
zCut ZCut12, ZCut23, ZCut34
Dipolarity Dip12, Dip13, Dip23, DipExcl12
Angularity Angularity
kT Delta R KtDR
kT Mass drop Mu12
Planar flow PlanarFlow
Energy correlations ECF1, ECF2, ECF3, C2, D2
Thrust ThrustMin, ThrustMaj
FoxWolfram FoxWolfram0, FoxWolfram1, FoxWolfram2, FoxWolfram3, FoxWolfram4
Sphericity Sphericity, Aplanarity
Shower deconstruction ShowerDeconstructionW, ShowerDeconstructionTop
In case you add other variables please do not use underscores.

Configuration

Parameter Explanation
JetAlgos name of the calo jet container
TrackJetAlgos name of the track jet container
skipEvents Skips the first n events of a run. (only for debugging)
configDataPath Directory where all PRW config files, lumicalc files and the GRL are.
ghost-matching If false track jets and calo jets are matched with the dR criterion.
dRCone The dR parameter that is used in case ghost-matching is set to false.
prwConfig Prefix to identify PRW config files.
CalibJetConfig Config file for jet calibration of jets that are evaluated.
Jets Type of the evaluated jet.
CalibSmallRConfig Config file for jet calibration of smallR jets that are used for cleaning only, since no jet cleaning was available for largeR jets at that time.
This should produce several .root files with a TTree. The Tree holds all activated variables for the leading and the sub leading jet with 5 prefixes c, t, tc1, tc2 and tc3.
These are refering to calo jet, track jet and the three variations that are applied to MC only.
tc1 covers track reconstruction efficiency (global, PP0 and IBL), efficiency for dense environment and impact parameter resolution ( including dead modules).
tc2 covers fake rate.
tc3 covers Sagita Bias.

Plotting

After you have retrieved your outputs. You will most likely need to merge it in order to have one .root file per sample and one for data.
In !DeriveJMSR/ you should see plotting/ containing: atlasStyleMacro.py, atlasStyleMacro.pyc, functions.py, functions.pyc, HistoCreator.py, merge_jet1_jet2_doubleFiles.py, merge_jet1_jet2_inclusive.py, rTrack_plottingMaker.py and =run_histo_creator.py=
run_histo_creator.py calls run_histo_creator.py with the specified cuts. Usually you bin these double ratios in pT and m/pT. The binning in pT comes for free, while for each m/pT bin an additional output file is generated.
HistoCreator.py produces for each variable a 2D histogram with the simple ratio X_Calo/X_Track. As well as some 1D histograms to check the continuity of the pT spectrum.
merge_jet1_jet2_inclusive.py merges the output of HistoCreator.py for the leading and sub leading jet if you run inclusive in m/pT.
merge_jet1_jet2_inclusive.py merges the output of HistoCreator.py for the leading and sub leading jet.
rTrack_plottingMaker.py calculates the mean of the simple ratio per bin and produces the 1D histograms as control plots and the 2D maps, that are used as input for the calculation of uncertainties.

To run everything:

setupATLAS
lsetup root
python run_histo_creator.py
python merge_jet1_jet2_doubleFiles.py
python rTrack_plottingMaker.py

(run_histo_creator.py will take quite some time though.)

Settings

In run_histo_creator.py: Choose if you like to run inclusive in m/pT or not. In HistoCreator.py: Normalization:
For the normalization (sliceWeight_...) you need to look up the cross section and the filter efficiency on ami.
The product is then divide by the total number of processed events for JZXW samles and the sum of weights of processed events for JZX samples.
*Types:*
To add another generator put it in

types=[]

. You need to add it as well in

QCD_weights={}

and in

files_dic={}


*Variables:*
In

variables=[]

you specify the axis of the 2D histograms separated by a colon. (y-axis:x-axis)
In

bin_dic={}

you specify the binning of these histograms (#bins x-axis, start, end, #bins y-axis, start, end)
These values are overwritten for histograms ending with /1e3 with the binning defined in binLowE.
In rTrack_plottingMaker.py:
In filDic={} you specify the input. In m_pt_s={} you specify for which variables you would like produce maps.
With pt_mass_vectors_nBins={} you ensure that the binning is done right.
In variables=[] you specify the variables for which you would like to see the control plots.
Other dictionaries specify the layout and labeling of the plots.

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Topic revision: r3 - 2016-10-06 - AlexanderMelzer
 
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