simple_cellular_automata.py

"""making conway's game of life. It has the following instructions:

1. Any live cell with fewer than two live neighbors dies, as if by underpopulation.
2. Any live cell with two or three live neighbors lives on to the next generation.
3. Any live cell with more than three live neighbors dies, as if by overpopulation.
4. Any dead cell with exactly three live neighbors becomes a live cell, as if by reproduction."""

import time
import os
import numpy as np
import argparse

# helper functions
def render_board(array):
	val = {1: "*", 0: "-"}
	t = ''
	for row in board:
		t += ' '.join([val[x] for x in row]) + '\n'
		# t += ' '.join([val[x] for x in row]) + '\n'
	return t

def update_board(array):
	live_locations = array == True
	new_board = np.zeros(shape = (args.s, args.s))
	for ridx, row in enumerate(live_locations):
		for cidx, item in enumerate(row):
			if item:
				# this cell is alive; get count of nearby cells
				nearby_cell_count = np.sum(array[
					max(0, ridx-1): min(args.s, ridx+1) + 1,
					max(0, cidx-1): min(args.s, cidx+1) + 1]
				) - 1 # for itself
				# print("nearby_cell_count", nearby_cell_count)

				# if nearby_cell_count < 2:
				# 	# dies of underpopulation

				if int(nearby_cell_count) in [2, 3]:
					# lives
					new_board[ridx, cidx] = 1

				# elif nearby_cell_count > 3:
				# 	# dies of over population

			else:
				nearby_cell_count = np.sum(array[
					max(0, ridx-1): min(args.s, ridx+1) + 1,
					max(0, cidx-1): min(args.s, cidx+1) + 1]
				)
				# print("nearby_cell_count", nearby_cell_count)
				if int(nearby_cell_count) == 3:
					# grows by reproduction
					new_board[ridx, cidx] = 1
	return new_board

if __name__ == '__main__':
	args = argparse.ArgumentParser(description = "simple conway's game of life setup")
	args.add_argument("-s", type = int, default = 32, help = "size of board")
	args.add_argument("-n", type = int, default = 20, help = "number of generations")
	args.add_argument("-t", type = float, default = 0.5, help = "time to sleep (s)")
	args = args.parse_args()

	# main 
	os.system("clear")
	board = np.random.choice([1, 0], args.s * args.s, p=[0.3, 0.7]).reshape(args.s, args.s) 
	board = np.reshape(board, (args.s, args.s))
	print(render_board(board))
	time.sleep(args.t)

	for gen in range(args.n):
		os.system("clear")
		board = update_board(board)
		print(render_board(board))
		time.sleep(args.t)