This workflow assumes that you are in the MuColl-TauStudy directory:
cd <your path to>/MuColl-TauStudy
Generate n tau events and write them to gen_output.slcio:
python generation/lcio_tau_gun.py --nEvents n --outputFile gen_output.slcio
This creates one tau MCParticle per event with uniform distributions of 20 <= pT <= 320 GeV/c, 10 <= theta <= 170 deg, and 0 <= phi <= 2pi rad, which can be manually adjusted.
Before simulating the events, change the MUCOLL_GEO environment variable to the path of the MAIA detector geometry file:
export MUCOLL_GEO=/your/path/to/MuColl-TauStudy/detector_geometry/MAIA_v0/MAIA_v0.xml
Now simulate the decays and material interactions of the generated tau events in the MAIA detector:
ddsim --steeringFile simulation/steer_sim_tau_gun.py --inputFile gen_output.slcio --outputFile sim_output.slcio
Convert simulated hits into realistic hits:
k4run digitisation/k4run/digi_steer.py --LcioEvent.Files sim_output.slcio --outputFile digi_output
This produces two output files: digi_output.slcio and digi_output_light.slcio. The former contains all collections produced from the digitization, while the latter contains only a small subset.
Reconstruct tracks, clusters, and particles of tau decay products (plus other simulated particles):
cp -a reconstruction/k4run/PandoraSettings/ ./
k4run reconstruction/k4run/reco_steer.py --LcioEvent.Files digi_output.slcio --MatFile ${ACTS_MatFile} -- TGeoFile ${ACTS_TGeoFile}
Like the digitization steps, this produces two output files: reco_output.slcio and reco_output_light.slcio. The former contains all collections produced from the reconstruction, while the latter contains only a small subset.