A package for 1-X dimensional cellular automatons. The package is tested and working with python 3+
OTHER License
This package provides an cellular automaton for Python 3
A cellular automaton defines a grid of cells and a set of rules. All cells then evolve their state depending on their neighbours state simultaneously.
For further information on cellular automatons consult e.g. mathworld.wolfram.com
It is not the first python module to provide a cellular automaton, but it is to my best knowledge the first that provides all of the following features:
I originally did not plan to write a new cellular automaton module, but when searching for one, I just found some that had little or no documentation with an API that really did not fit my requirements and/or Code that was desperately asking for some refactoring.
So I started to write my own module with the goal to provide an user friendly API and acceptable documentation. During the implementation I figured, why not just provide n dimensional support and with reading Clean Code from Robert C. Martin the urge to have a clean and tested code with a decent coverage added some more requirements. The speed optimization and multi process capability was more of challenge for myself. IMHO the module now reached an acceptable speed, but there is still room for improvements (e.g. with Numba?).
This module can be loaded and installed from pypi: pip install cellular-automaton
To start and use the automaton you will have to define four things:
class MyCellularAutomaton(CellularAutomaton):
def init_cell_state(self, coordinate: tuple) -> Sequence:
return initial_cell_state
def evolve_rule(self, last_state: tuple, neighbors_last_states: Sequence) -> Sequence:
return next_cell_state
neighborhood = MooreNeighborhood(EdgeRule.IGNORE_EDGE_CELLS)
ca = MyCellularAutomaton(dimension=[100, 100],
neighborhood=neighborhood)
The Neighborhood defines for a cell neighbours in relative coordinates. The evolution of a cell will depend solely on those neighbours.
The Edge Rule passed as parameter to the Neighborhood defines, how cells on the edge of the grid will be handled. There are three options:
A list or Tuple which states each dimensions size. The example above defines a two dimensional grid with 100 x 100 cells.
There is no limitation in how many dimensions you choose but your memory and processor power.
To define the evolution rule and the initial state create a class inheriting from CellularAutomaton
.
init_cell_state
method will be called once during the creation process for every cell.evolve_rule
gets passed the last cell state and the states of all neighbors.The package provides a module for visualization of a 2D automaton in a pygame window.
CAWindow(cellular_automaton=StarFallAutomaton()).run()
The visual part of this module is fully decoupled and thus should be easily replaceable.
The package contains three examples:
Those example implementations should provide a good start for your own project.
Feel free to open pull requests, send me feature requests or even join as developer. There ist still quite some work to do.
And for all others, don't hesitate to open issues when you have problems!
evolve_rule
and init_cell_state
state_to_color_cb
parameter.There is only a dependency for recordclass at the moment.
If you want to use the CAWindow or execute the examples you will have to install pygame for visualisation. If you don't want to use this engine for some reason pass another draw_ending to the CAWindow. It has to provides the same interface as the PygameEngine
This package is distributed under the Apache License, Version 2.0, see LICENSE.txt