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The master branch is now dedicated to analysis of the new atlas data format (xAOD). For production of skims out of the old format (D3PD), please refer to the d3pd branch.

• Latest 5.X ROOT with PyROOT enabled.

• rootpy:

  git clone git://github.com/rootpy/rootpy.git
  cd rootpy
  python setup.py install --user
  

• goodruns:

  pip install --user goodruns
  

• PyYAML:

  pip install --user pyyaml
  

• ConfigObj:

  pip install --user configobj
  

• externaltools:

  git clone git://github.com/htautau/externaltools.git
  

• lumi:

  git clone git://github.com/htautau/lumi.git
  

• hhntup:

  git clone git://github.com/htautau/hhntup.git
  

• TauSpinnerTool:

  svn co svn+ssh://${USER}@svn.cern.ch/reps/atlasoff/PhysicsAnalysis/TauID/TauSpinnerTool/trunk TauSpinnerTool
  

Place externaltools, lumi, and TauSpinnerTool in the same directory containing hhntup to satisfy the symlinks in hhana. See the README in externaltools and TauSpinnerTool for further instructions. Use at least Python version 2.6 (2.7 is preferred).

• Analysis release used:

  Base, 2.0.17
  

• Dataset used:

  mc14_8TeV.147808.PowhegPythia8_AU2CT10_Ztautau.merge.AOD.e2372_s1933_s1911_r5591_r5625
  

• To run the test:

  skim --local-test mc12_hadhad_xaod
  

Now build the C extension module for jet cleaning in the higgstautau package:

make lib

Before running tests locally:

source setup.sh

The skimming is performed by the hhskim.py script.

Run the skims on the grid (after setting up the panda client and your VOMS proxy with the phys-higgs production role):

./skim --yall mc11_hadhad mc12_hadhad \
              data11_hadhad data12_hadhad \
              embed11_hadhad embed12_hadhad

The samples are organized in several blocks defined in skims.cfg. Each block is written following the template:

[block_name]
 student = hhskim.py
 dataset = dataset_block (defined in datasets.cfg)
 version = version_number
 testinput = /path/to/the/input/files/for/test
 dest = SFU-LCG2_LOCALGROUPDISK,

For each block, modify the variable testinput according to your own setup.

Run the test:

./skim --yall block_name --local-test

The output will be created in the main directory as:

hhskim_dataset_block.root

After the skims are finished and downloaded, update the paths in higgstautau/datasets_config.yml and update the datasets database:

./dsdb --reset hh

Then launch the batch jobs that create all the analysis ntuples (nominal and systematics) with:

./run-all