boolforge-uniform-samplers

Sampling canalizing and nested canalizing functions uniformly at random constitutes a non-trivial combinatorial problem. In a recent manuscript, we described methods to obtain an efficient uniform sampler, which is implemented in BoolForge.

Purpose

This repository contains all code to generate the figures presented in

Ahana Ghosh and Claus Kadelka. Uniform sampling of canalizing Boolean functions reveals hidden biases in Boolean network analysis. Under review.

Repository structure

.
├── src/
├── figures/
├── requirements.txt
└── README.md

scripts/

Source code used for all analyses.

figures/

Generated manuscript figures.

Installation

Clone the repository:

git clone https://github.com/username/boolforge-uniform-samplers.git
cd boolforge-uniform-samplers

Create a virtual environment and install dependencies:

pip install -r requirements.txt

Reproducing results

To reproduce all manuscript figures:

python scripts/create_figures124_uniform_sampler_paper.py
python scripts/create_figure3_uniform_sampler_paper.py

Generated figures will be written to:

figures/

Dependencies

• Python 3.10
• NumPy
• Matplotlib
• BoolForge

Authors

• Ahana Ghosh
• Claus Kadelka

License

MIT License