. setup.sh
Every analysis (small or large) has to be divided into three steps: (the first two of which need to be done only once)
For now we will use the barebones out of the box.
a sample nanoaod root file to test is here modules/testsample/tree_6.root
python modules/createJSON.py --sampleName test --xsec 1.0 --year 2016 --treename Events --histAxisName test --outname Analysis/barebones/jsons/test.json modules/testsample/
Add this json in a sample.txt file in the analysis folder, which will be input for next step. Example txt file canbe found here: Analysis/barebones/samples.txt
If you call it something else other than samples.txt, you can pass it with the --Samples option in the next command.
If you just want to pass a single json, you can pass it using --Sample bla-bla/bla-bla/something.json
/GluGluHToZGToMuMuG_M125_MLL-50To1000_012j_13TeV_amcatnloFXFX_pythia8/RunIIFall17NanoAOD-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/NANOAODSIM
python modules/createJSON.py --prefix root://cms-xrd-global.cern.ch// --sampleName GluGluHToZG --year 2016 --treename Events --histAxisName GluGluHToZG --xsec 2 --DAS --outname test.json /GluGluHToZGToMuMuG_M125_MLL-50To1000_012j_13TeV_amcatnloFXFX_pythia8/RunIIFall17NanoAOD-PU2017_12Apr2018_94X_mc2017_realistic_v14-v1/NANOAODSIM
preselectpreprocessanalyze
see the script examples from Analysis/barebones (check preselection.py, preprocessor.py, analysis.py)
./expresso.py --Analysis barebones --NumberOfTasks 2 --AnalysisPoint tight_ele_tight_mu
./expresso.py --Analysis barebones --NumberOfTasks 2
--NumberOfTasks is the maximum number of indivudual tasks to run as the analysis will be broken down to several jobs automatically. Give a very large number to run over all events. Each task will run 30,000 events. So if your total events is 60,000, you need atleast 2 tasks. So --NumberOfTasks 4 is certainly sufficient.
The --AnalysisPoint argument is a string is available to be used to your scripts to that you can customize what you want to do
See example in Analysis/barebones (check preselection.py, preprocessor.py, analysis.py). This is an optional argument.
To debug
./expresso.py --Analysis barebones --NumberOfTasks 2 --Debug
To pass some options can be used as strings to use in scripts, similar to analysis point.
./expresso.py --Analysis barebones --NumberOfTasks 2 --PassOptions 2e2u` ## This will do nothing as nothing is defined, but in analysis.py, you can write what to do if PassOptions is `2e2u
To make quick plots you add a --QuickPlots option to the previous command in fact:
/expresso.py --Analysis barebones --NumberOfTasks 2 --AnalysisPoint tight --QuickPlots Nele,sumw
To make more comprehensive plots (multiple backgrounds, signal, data), write a plot file, example Analysis/ZG/allplots.yaml allplots.yaml
Then run
python plot+.py --PlotterScript Analysis/barebones/allplots.yaml --HistoFolder Output/Analysis/barebones/output/analysis/ --SaveLocation Output/Analysis/barebones/output/analysis/
In the above --HistoFolder is where you can find all the histograms that are loaded in --PlotterScript, the Analyze step will print this histogram location on screen.
Check --SaveLocation to find your plots
The plotter script has two parts, year and plots. A simple script is:
'2016':
HG: test_anap_tight.pkl.gz,red,nostack,1
plots:
normal_Nele: Nele
This means the plots will have a label 2016, and use one file test_anap_tight.pkl.gz, with label HG on plots and will plot histogram Nele from the file. Color will be read, plot won't be stacked and will be scaled by 1. normal is a keyword. Please use this as is.
Other possible example:
'2018':
DY: DY_anap_loose.pkl.gz,green,stack,1
ZG: ZG_anap_loose.pkl.gz,blue,stack,1
data: data_anap_loose.pkl.gz,black,nostack,1
plots:
normal_Nele: Nele
To normalize a plot to just see the shape, you can use a scale of -1