Dependencies

• 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).

Build and setup

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

make lib

Before running tests locally:

source setup.sh

Skimming

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

Creating ntuples

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