This is a simulation coded in Python of the cellular automaton model created by John H Conway.

1. Download this repo and store it in your computer.
2. Open Powershell and go to the folder's root directory where the repo was stored.
3. Install needed dependencies by typing:

$: pip install numpy
$: pip install matplotlib

4. In order to run the simulation with Example 1, now type:

$: python conway.py -s 80 -g 200 -i config.dat

This will make a Conway Simulation with grid size 80x80 and run 200 generations, with the initial configuration defined in the file config.dat, which is in the same folder as the conway.py script.

5. At the end of the simulation, you will see the text file report.txt with all the reported Life beings that were tracked throughout every moment in time during the simulation, as well as their percentage of appearance at the bottom of the document.

$: python conway.py -s <size_number> -g <number_of_generations> -i <init_file>

With <size_number> and <number_of_generations> as integer number parameters, and <init_file> as the file name of the initial configuration input file.

This is the coolest interesting example I found on the web to debug and test. This is the example you run on step 4.

$: python conway.py -s 80 -g 200 -i config.dat

This example is on the root folder so you don't need to move any file from the repo as it is.

To run the following examples, go to folder other-configs and move the .dat file you want to test to the root folder, then you can type the commands below.

The folder contains the corresponding output report to each configuration if you want to check them.

This is another interesting example I found on the web.

$: python conway.py -s 80 -g 200 -i config2.dat

Small example. Debugs how the pogram works with Others category and Rotation of seeds.

$: python conway.py -s 40 -g 20 -i config3.dat

Another quite interesting example of a glider gun.

$: python conway.py -s 42 -g 200 -i config4.dat

Small example. Another quite interesting example to check gliders and oscilators.

$: python conway.py -s 20 -g 60 -i config5.dat

Language: Python 3.8.1

• The simulation always takes as input file the config.dat file, which defines the initial configuration of the simulation.
• This config.dat file was written through an auxiliar script called write-config-test.py, that writes every 'alive' cell as j i grid coordinates on a single line each, where j (x) and i (y) are separated by spaces. If you have a i j format file it's ok, your example will only be rotated 90°.
• Optional: You can create your own initial config by changing the choice list inside the write-config-test.py script. Then, open Powershell and type:

$: python write-config-test.py

Or you can write the file manually following the format.

• After running the simulation, the program writes an output file called report.txt.The file report.txt contains:
  • All the number of Life beings detected during each generation by their category.
  • Beings out of the Life patterns are detected during each generation and counted under 'Others' category.
  • The percentage of appearance throughout the simulation. Logically, this percentage is computed after all generations are counted, and therefore can be found at the end of the file.

Important: the report file reaches information until the N-1 frame, where N is the input number given in -s argument.

This simulation reports at every generation how many Life seed patterns are found by its category, and also other entities are counted as 'Others'. At the end of the simulation, a report with such information can be found.

Seeds are defined following Conway's standards, but the program also generates all their possible rotations and transposed positions, so that the report identifies rotated seeds as well.

For example, the following configuration will be identified by the program as two beehives, even though one is rotated.

Initial Configuration Example