Higgs to Tau Tau Skimming Code

This repository contains all of the code needed to skim either lepton+tau channel in 2016 or 2017. There is a single binary used to control the skimming for all year/lepton permutations and various headers containing the tree info for each permuation.

Table of Contents

Input File Locations
Quick Start
Using Condor

Input File Locations

Here are the locations of all currently used FSA ntuples

• 2016 ntuples

  • Background Monte Carlo: /hdfs/store/user/aloeliger/SMHTT_2016_20nov/
  • Signal Monte Carlo:
    • /hdfs/store/user/abdollah/FSA_2016_AC_XMass/
    • /hdfs/store/user/aloeliger/SMHTT_2016_20nov_ggH2/
  • Data: /hdfs/store/user/aloeliger/SMHTT_2016_data_18Sep/
  • Embedded: /hdfs/store/user/aloeliger/SMHTT_2016_embedded_18sep/

• 2017 ntuples

  • Background Monte Carlo:
    • /hdfs/store/user/tmitchel/SMHTT_2017_legacy_mc_v3p2_mt/
    • /hdfs/store/user/tmitchel/SMHTT_2017_legacy_mc_v3p2_et/
  • Signal Monte Carlo:
    • /hdfs/store/user/abdollah/FSA_2017_AC_XMass/
    • /hdfs/store/user/tmitchel/SMHTT_2017_legacy_mc_v3p2_ggh-only/
  • Data: /hdfs/store/user/tmitchel/SMHTT_2017_legacy_data_v3/
  • Embedded: /hdfs/store/user/tmitchel/SMHTT_2017_legacy_embedded_v3/

• 2018 ntuples (old global tag)

  • Background Monte Carlo:
    • /hdfs/store/user/caillol/SMHTT_2018_20nov_mc/
    • /hdfs/store/user/caillol/SMHTT_2018_20nov_highMem_etmt_mc/
  • Signal Monte Carlo: /hdfs/store/user/abdollah/FSA_2018_AC_XMass/
  • Data: /hdfs/store/user/caillol/SMHTT_2018_31oct_data/
  • Embedded: /hdfs/store/user/caillol/SMHTT_2018_20nov_embedded/

• 2018 ntuples (new global tag)

  • all in progress

Quick Start

This section is designed so that you can start producing skims by simply copy/pasting the following commands. Refer to other sections of the README for more detailed instructions, if needed.

1. Setup a new CMSSW release

   cmsrel CMSSW_9_4_0 && cd CMSSW_9_4_0/src && cmsenv
   

2. Clone all necessary repositories and get them setup

   • clone this repo

     git clone -b development git@github.com:tmitchel/LTau_skimmer.git
     

   • get the files needed for recoil corrections

     git clone https://github.com/CMS-HTT/RecoilCorrections.git HTT-utilities/RecoilCorrections
     

   • now compile CMSSW things that need compiling

     cd ${CMSSW_BASE}/src
     scram b -j 8
     

   • finally, download Tau ES files

     cd ${CMSSW_BASE}/src/LTau_skimmer/ROOT
     source setup.sh
     

3. Submit skims to condor for a chosen year/lepton/job type Submitting 2016 samples to be skimmed is done using a single python script to submit multiple jobs.

   voms-proxy-init --voms=cms --valid=48:00 # get certificate
   python submit2016.py -p mutau2016_legacy_v1 -l mt -j sig
   

   This will farmout a job to skim all signal samples in the 2016 mutau channel. The output files will be saved to /hdfs/store/user/your_name/mutau2016_stable_v3 or whatever name you provide to the -p option. As you can see from the example, the -l flag is used to give the lepton type and the -j flag is used to pass the job type [sig, bkg1, bkg2, data, embed].

   The script submit2017.py can be used in the exact same way to submit jobs for 2017.

These scripts will be combined into a universal script later when I have some free time.

Skimming with Wisconsin Condor

The primary way to produce skimmed ntuples using this skimmer is through the use of the Wisconsin Condor system. The scripts in the ROOT/scripts directory are used for submitting jobs for processing with Condor.

Skimminate.py is used to skim single directory filled with FSA ntuples. Command-line arguments can be used to customize aspects of the job including the input directory and whether to apply recoil corrections. An example command is shown below

python Skimminate.py --job bkg --recoil Z --jobName chooseAName --samplename DYJets1 --sampledir /hdfs/store/user/tmitchel/input/DYJets1 -l et -y 2016

This command will skim all files in the directory /hdfs/store/user/tmitchel/input/DYJets1 assuming they are from the dataset DYJets1. The corrections appropriate for a background MC sample will be applied and the output files will be stored in /hdfs/store/user/tmitchel/chooseAName. The -l option tells the script for which channel we want to submit skims and the -y option provides the year.

The typical way to produce skims is using the submit*.py scripts which allows entire job types to be submitted at once. An example command to skim all embedded samples, with appropriate corrections, is shown below.

python submit2016.py -p myName -l et -j embed

The output files will be stored in /hdfs/store/user/tmitchel/myName.