Experiments with Cellular Automata

This repo contains experiment on Cellular Automat integrated in a python library abio
All computations are done under the hood with PyTorch to be accelerated but also ease the transition to Neural Cellular Automata

Features

• 1D Cellular Automata (computation with 1D-convolutions & visualization)
• 2D Cellular Automata (Game Of Life, and framework to extend) (computation with 2D-convolutions & visualization)
• Streamlit app to facilitate the visualization and use of the library

Installation of the abio library

There is no pypi package yet, but you can use the library locally by cloning the repo, installing the requirements and adding the path to the environment

Library quickstart

Running a 1D Cellular Automata

from abio.cellular_automata import CellularAutomata1D
ca = CellularAutomata1D()
ca.run_random(rule = 30,size = 100,p_init = 0.02,n_steps = 100)

Running a 2D Cellular Automata

from abio.cellular_automata import GameOfLife

# Instantiate the Cellular Automata wrapper
ca = GameOfLife()

# Compute the Cellular Automata
states = ca.run(500,p_init = 0.5,init_size = 100)

# Apply color on persistent cells + resize to better visualize in the video
states.transform(only_alive = True,resize = (400,400),method = "nearest")

# Save the video locally
states.save_video(fps = fps)

To run the Streamlit app locally

• Clone the repo locally
• Install the requirements file
• Run streamlit run index.py

Resources

Take a look at my personal website for more resources https://emergence.pub/docs/#understanding-cellular-automata

License

MIT