This repository contains the artifacts for the following paper:
EXPLORA: AI/ML EXPLainability for the Open RAN
Claudio Fiandrino, Leonardo Bonati, Salvatore d'Oro, Michele Polese, Tommaso Melodia, Joerg Widmer
CoNEXT โ23, December 5โ8, 2023, Paris, France
DOI: 10.1145/3629141
In this repository, we include all data and analysis scripts required to reproduce our results.
Please see the README
files in each sub-directory for further details.
This repository is structured into the following sub-directories:
scripts/
: Contains the python code to reproduce our results.data/
: Contains the data required by the python scripts.results/
: Contains intermediate and final results.paper-plots
: Contains the TiKZ code to generate the figures of the manuscript.
Tested on
Linux 5.11.0-22-generic #23~20.04.1-Ubuntu
- Make sure you have python Python 3.9.13 installed. Create a virtual environment and install the required dependencies (see requirements.txt in the
scripts/
directory - run$ pip install -r requirements.txt
). Install graphviz too viasudo apt-get install graphviz
. - Clone this repository.
- Follow the instructions in the
README
of thescripts/
sub-directory for the order of execution of the scripts. Check-back thedata/
to make sense of the workflow. - Find the results of the processing in
results/
and the final plots of the paper inpaper-plots
.