Neuromorphic Readout for Hadronic Calorimeters

How to Run

Here is a quick overview of the necessary steps to take in order to run the code contained in this repository. This is not meant to be an exhaustive overview, merely a simple list of instructions for the less tech-savvy audience.

Get this Repository on your System

First, get a local copy of this repository so that you can run and modify it as you wish. In order to do that, I suggest first forking it so that you have your own personal version of it, and then clone it locally on your computer.

WARNING!: The main branch is currently not updated! Please use the lin_model branch to enjoy all the functionalities.

Set up the Python Environment

Second, make sure you have all the packages necessary to run the code. I suggest using a package and environment manager like Anaconda.

Install Miniconda

Install Miniconda on your system, following the information detailed on this page. You can do it easily using these commands on a Linux machine:

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm ~/miniconda3/miniconda.sh
source ~/miniconda3/bin/activate
conda init --all

Create the Conda Env

Generate a conda environment (here is a list of commands you can use) and download the necessary packages, in particular numpy, PyTorch, snnTorch and Jupyter Notebook.
If you want the exact environment that I used, run the following command:

conda env create -f env/environmental_droplet.yml

to create the snn_hgcal environment with all the needed components.