Skip to content

Edler1/Kalman-tracking

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

41 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Kalman-tracking

This code contains a standalone version of the tracking code included in DELPHES. The calculation of the track covariance matrix can be done either with standard full covariance matrix of the measurements, including multiple scattering effects, or with a Kalman filter approach.

Standalone C script (ROOT)

Running instructions:

root

root> .L examples/LoadTrk.c+

root> LoadTrk()

root> KalmanCheck("./Geometries/GeoIDEA_NewDCH.txt")

This program will generate plots using both the standard version or the Kalman version of the code.

root> PlotGeo("./Geometries/GeoIDEA_NewDCH.txt")

will make a simple plot of the geometry and display the material as a function of the polar angle or its cosine.

Python multi-detector comparison script

The perf_multi.py script allows to compare tracking performance across multiple detector geometries. It produces resolution scans, geometry plots, material budget plots, and optionally a LaTeX beamer report.

Environment setup (lxplus)

To run on lxplus you need to set up the LCG software stack:

source /cvmfs/sft.cern.ch/lcg/views/LCG_105/x86_64-el9-gcc13-opt/setup.sh
export PATH=/cvmfs/sft.cern.ch/lcg/external/texlive/2020/bin/x86_64-linux:$PATH

The second export is needed to produce the LaTeX report.

Example

python3 perf_multi.py \
  --card Geometries/GeoIDEA_NewDCH.txt --label IDEA --bfield 2.0 --doKalman true --doMS true --doRes true \
  --card Geometries/GeoCLD.txt --label CLD --bfield 2.0 --doKalman true --doMS true --doRes true \
  --inc examples/classes --compile --workers 60 --latex --npoints 100 \
  --outdir .

When using the --latex flag, a beamer PDF report like this one will be produced.

About

Tracking resolution code with standard and Kalman filter methods

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • Python 100.0%