Setup tried with conda 4.8.3 and python 3.8.3.

conda env create -f environment.yml --name <env name>`
conda activate <env name>
pip install -r requirements.txt

We also need DeepPurpose to run real data experiments. In external to this repo, do the following

git clone git@github.com:kexinhuang12345/DeepPurpose.git
cd DeepPurpose
pip install -e .

To run the numerical simulations in the paper and create the associated plots, run: python src/main.py --exp <name of experiment> --processes <# of processes allowed for process pool> --out_dir <directory for saving output figures> --result_dir <directory for saving intermediate outputs Possible values of experiment names are lag_comp and wor_comp.

To run the protein binding prediction experiments do the following.

cd src
./run-batch.sh 600 5

After that has finished, plot the results with

python gather_results.py DPP_results ../figures/wcs