SCINT (Sensor Calibration Interface for Neutrino Team!)

📖 📃 Access the DOCUMENTATION for more information 📃 📖

This is a Python library to process and analyze raw data from the lab.

We want:

• Classless structure, dictionaries hold all the run/channels variables (+ wvfs).
• To avoid as much overcalculation as possible:
  • Calculate pedestal/charge/time... values at once and store them separately from the raw data.
  • Prevent excessive memory usage when dealing with multiple runs by only loading the variables and not the wvfs.

We don't want:

• Complicated hierarchies
• Commented/uncommented lines with the same code but different runs/configs

0 Download

• Clone the repository into a local directory and create your branch:

git clone https://github.com/CIEMAT-Neutrino/SCINT.git
cd SCINT
git checkout -b <your_branch_name>

• You can create a test folder for your custom scripts or code.

• [OPTIONAL] Create a folder for your custom scripts and add them to the .gitignore file:

mkdir <your_folder_name>
echo "<your_folder_name/*>" >> .gitignore

1 To start RUN:

• Go to the scripts folder and set all the utilities needed for the macros:

cd SCINT/scripts
sh setup.sh 

• Create a folder data/ (or use the copy_data.sh script) to copy the data from the server.

mkdir data/
sshfs user@server:path_to_data data

2 Run the following macros FROM the macros' folder:

cd ../macros
python3 XXmacro.py (--flags input) 

3 To better visualize what is happening and perform non-standard analysis, there are Jupyter notebooks available in notebooks

cd ../notebooks
jupyter notebook 00TUTORIAL.ipynb

🚧 Work in progress (check TO DO LIST) :construction:

LICENSE

MIT

Authors (alphabetical order, please insert your name here if you contribute to this project)

• Alvárez-Garrote, Rodrigo
• de la Torre Rojo, Andrés
• Manthey Corchado, Sergio
• Pérez-Molina, Laura