Simulating an elementary cellular automaton
Cellular automata are discrete dynamical systems evolving on a grid of cells. These cells can be in a finite number of states (for example, on/off). The evolution of a cellular automaton is governed by a set of rules, describing how the state of a cell changes according to the state of its neighbors.
Although extremely simple, these models can initiate highly complex and chaotic behaviors. Cellular automata can model real-world phenomena such as car traffic, chemical reactions, propagation of fire in a forest, epidemic propagations, and much more. Cellular automata are also found in nature. For example, the patterns of some seashells are generated by natural cellular automata.
An elementary cellular automaton is a binary, one-dimensional automaton, where the rules concern the immediate left and right neighbors of every cell.
In this recipe, we will simulate elementary cellular automata with NumPy using their Wolfram code.
How to do it...
- We import...
