This repo contains accompanying code for the Master Thesis "Beyond risk scores" by Sander Broos.
Starting point for experiments will be the following command:
python3 fbt/experiments/compare_stats.py \
--inference_method "dummy" \
--experiment_setup "prequential" \
--config_data intermediate_graph_abm_02 \
--config_model model_IG02
Experiments take two configs: one for the model and one for the simulator (data). Whenever 'abm' is in the data config, the ABM simulator will be used.
Experimental setup could be 'single', where inference will be performed on a single, static graph, or 'prequential', where an experiment with conditional testing and quarantining will be performed (similar to related research like CRISP and SIB).
Code convention: We care deeply about good code and scientific reproducibility. As of July 2023, the code contains
42 unittests, spanning more than one thousands line of code (make test or nose2 -v).
The code includes abundant type hints (make hint or pytype fbt).
Code is styled with included '.pylintrc' and pycodestyle (make lint or pylint fbt)
For GSL, follow these instructions
# get the installation file
wget ftp://ftp.gnu.org/gnu/gsl/gsl-latest.tar.gz
# Unpack archive
tar -zxvf gsl-latest.tar.gz
# make a directory for the gsl installation
mkdir /var/scratch/${USER}/projects/gsl
# installation
./configure --prefix=/var/scratch/${USER}/projects/gsl
make
make check
make install
SWIG install
sudo apt-get update
sudo apt-get -y install swig
ABM install
# Get the ABM code
cd ../
mkdir abm
cd abm
git clone https://github.com/aleingrosso/OpenABM-Covid19.git .
cd src
make all
make swig-all
To run a sweep with WandB, run the following command
$ wandb sweep sweep/default.yaml
Copy the sweepid. Then on the cluster, or another computer, start up an agent with
$ export SWEEP=sweepid
$ wandb agent "$USERNAME/fbt-fbt_experiments/$SWEEP"
Some analysis plots of example results can be found in the file testing_policy_analysis.ipynb.
This repo continued from a fork of upstream repo NTTW