pyscail is a package for creating cellular automata. It allows you to specify the allowed states, and the transitions between them, and does everything else for you
You need to have python (>= 3.11) installed on your system. Once you have that, you can:
pip install pyscail(or pip3, depending on your system)
The project's link on PyPI: https://pypi.org/project/pyscail/
See this video for a demonstration of how to use the library: https://youtu.be/BjPNs30i2TQ
A brief summary - provide a class with a next method and a
display method. Provide a initialization function that returns
an instance of your class given some coordinates. Provide a settings
object that you can make using method provided by the library.
Optionally, provide a function that will be called once each generation.
Then, simply call scail.run to run the ruleset.
See the following video for a demonstration on how to write code using this library.
See the demos folder for a lot more (and more varied) examples on how to use the library. Written demo automata include:
- Conway's game of life
- The modified game of life with extinction
- Langton's ant
- Wireworld
- Rock-Paper-Scissors automata
- Belusov-Zhabotinsky reaction (https://www.hermetic.ch/pca/bz.htm)
- the Mandelbrot and Julia sets
- A simulation of grain growth in metals (https://www.sciencedirect.com/science/article/pii/1359646296000553)
- And lastly, this demo of many of the above rulesets combined into one ruleset and run all together, then displayed as a weighted average
Kernel caching is an option you can enable through kernels.initialize_kernel_caching
If this is set, then instead of being calculated every frame, the neighborhoods
of a given point will be calculated once then cached. This will probably
not cause any issues unless you change your neighborhood strategy mid-simulation.
Still, I didn't notice a significant speedup upon implementing caching, so for now it is just an option that is turned off by default.
