A python-based simple processor for data acquired with XenoDAQ
Project description
# PyLArS > Ricardo Peres, Julian Haas
Comprehensive processing and analysis of SiPM data.
Check the [docs](https://ricmperes.github.io/PyLArS/) and the example notebooks for a quick start!
## Instalation `bash git clone git@github.com:ricmperes/PyLArS.git cd PyLArs pip install . ` For instal in editable source: `bash pip install -e . `
## How to pylars
To use pylars as “black-box” data processor go to the directory where the raw ROOT files are and run `bash pylars `
For more options (raw and output files, level of RMS, polarity of signal and baseline samples) check the help funtion: `bash pylars --help `
- For batch processing use the scripts provided in scripts:
make_job_files.py, option -r for run number: creates a directory jobs and a slurm compatible .job file for each dataset to be submited to a cluster individually.
launch_process.sh: runs sbatch [#.job] for all the files in the jobs directory
cleanup.sh: removes all the .job files
In case batch processing is conducted in a single machine without slurm submission run: `python python make_job_files.py -r [run_number] cd jobs ls | xargs chmod +x ls | xargs -n 1 sh `
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