A great package.
Project description
mario-mapyde v0.2.0
Docker Images
Docker images are made available in our container registry.
docker pull ghcr.io/scipp-atlas/mario-mapyde/madgraph
docker pull ghcr.io/scipp-atlas/mario-mapyde/delphes
docker pull ghcr.io/scipp-atlas/mario-mapyde/pyplotting
If you want to run on a machine with an NVidia GPU and use it for limit setting
with pyhf
, then there's a container for that too:
docker pull ghcr.io/scipp-atlas/mario-mapyde/pyplotting-cuda
Running
There are a few layers of scripts to factorize the different tasks. A typical pipeline will look like:
- Call test/wrapper_mgpy.sh to run MadGraph+Pythia and
produce a .hepmc file. The script takes options to specify things like:
- proc/param/run cards for MadGraph
- includes specifying particle masses, and
- any kinematic cuts to apply at parton level
- pythia card
- center of mass energy
- number of cores to use for MadGraph and Pythia
- proc/param/run cards for MadGraph
- Call test/wrapper_delphes.sh to run Delphes,
which is a parameterized detector simulation. The output is a ROOT file. The
script takes arguments to specify things like:
- Delphes card
- Call something like test/wrapper_ana.sh to analyze
the Delphes output. Note that this script can run user-specified code:
- scripts/SimpleAna.py will make a generic "flat" ntuple in a ROOT file.
- scripts/Delphes2SA.py will make an ntuple that
can be parsed by
SimpleAnalysis
for limit setting.
- If you want to run limits, then there are two additional steps:
- Run test/wrapper_SimpleAnalysis.sh to
analyze the output of
Delphes2SA.py
and make inputs for limit setting - Run test/wrapper_pyhf.sh to plug the results
from
SimpleAnalysis
into the public likelihood.
- Run test/wrapper_SimpleAnalysis.sh to
analyze the output of
Each job gets its own ${tag}
, which is used to tell the various steps in the
pipeline which data to operate on.
For an example of a full pipeline, see run_VBFSUSY_standalone, which itself takes various options to help steer the work.
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