SmoothLifePlus

SmoothLifePlus is a Python implementation and visualizer of SmoothLife, a continuous-state cellular automaton proposed by Stephan Rafler. It is inspired by Conway's Game of Life but operates on a continuous field (values in the range [0, 1]) with smooth transitions rather than binary cell states.

What this repository contains

• smoothlife.py: simulation loop and Matplotlib animation entry point.
• rules.py: SmoothLife transition rules (basic and extended variants).
• calculations.py: precomputed isotropic neighborhood masks and FFT helpers.
• parameters.py: parameter input dialog (Tkinter GUI).
• field.json, glider_field.json: example initial conditions (saved as JSON arrays).
• test.py: unit tests (unittest-based).

Model overview (implementation notes)

This implementation follows the standard SmoothLife structure:

1. Represent the world as a 2D array of floats in [0, 1].
2. Compute two neighborhood averages each step:
   • an "inner" disk average and an "outer" ring (annulus) average.
3. Apply smooth birth/survival thresholds using sigmoid-like functions to produce the next field values.

For performance, neighborhood sums are computed using convolution in the frequency domain (FFT). The masks are precomputed once (see calculations.py) and applied each step via elementwise multiplication in Fourier space, followed by an inverse FFT back to the spatial domain (see SmoothLife.step() in smoothlife.py).

Requirements

• Python 3.8+ (tested with Python 3.12).
• Python packages required to run:
  • numpy
  • matplotlib
• GUI dependency:
  • tkinter (part of the standard library on many platforms, but may require an extra OS package on some Linux distributions such as python3-tk)

Notes on requirements.txt:

• The repository includes a pinned requirements.txt that contains additional packages beyond the core runtime dependencies (for example: pytest, coverage).
• It also includes pywin32, which is Windows-specific and will not install on Linux/macOS without platform markers.

Installation

Create a virtual environment and install the core dependencies:

python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install numpy matplotlib

If you are on Windows (PowerShell):

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install --upgrade pip
python -m pip install numpy matplotlib

Usage

Run the main script:

python smoothlife.py

• A Tkinter dialog is used to input parameters.
• A Matplotlib window then displays the evolving field.

Initial conditions and output files

• Random initialization: SmoothLife.add_speckles() fills the field with random patches.
• Glider initialization: enabling the glider option loads glider_field.json.
• Saving an initial field: enabling the save option writes the generated field to field.json.

Testing

Unit tests are in test.py and use the standard library unittest module.

MPLBACKEND=Agg python -m unittest -v

If you want a coverage report, install pytest and pytest-cov and run:

python -m pip install pytest pytest-cov
python -m pytest --cov=. --cov-report=html test.py

Example coverage output:

References

• Stephan Rafler, "SmoothLife - A continuum version of Conway's Game of Life" (2011). Commonly distributed as a PDF online (often referenced via smoothlife.net).
• Martin Gardner, "Mathematical Games: The fantastic combinations of John Conway's new solitaire game 'life'", Scientific American (October 1970).
• Conway's Game of Life overview: https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life
• "Conway's Game of Life for Curved Surfaces" (0fps). https://0fps.net/2012/11/19/conways-game-of-life-for-curved-surfaces-part-1/
• NumPy FFT documentation (used for frequency-domain convolution in this implementation). https://numpy.org/doc/stable/reference/routines.fft.html

License

No license file is present in this repository. If you intend to reuse or redistribute this code, clarify licensing with the repository owners first.

Authors

Josselin Perret, Oscar Eav, Antonioli Enzo, Arthur De Bom Van Driessche, Solène Zhang.