This course has covered:
numpy for numerical work in Python
Adapt your one-dimensional cellular automaton code to follow a new set of rules. For each cell, look at the cells to its left and right and:
Run a simulation for an array of size 100, for 50 time steps. The initial value of the array should be all
0s, except a single
1 at index 50.
Put the code which runs the simulation in a Python script called
run_simulation.py and run it on the command line. This script should save its results to a numpy output file.
Put the code which visualises the results into a Jupyter Notebook which should read the numpy file and create some graphs or images.
See what happens if instead of starting with a single value of
1, you instead initialise your array randomly.
This course was written by Matt Williams. All text is published under a Creative Commons Attribution 4.0 International License with all code snippets licensed as MIT.
The source for the material can be found on GitLab where fixes are welcome.