Simple implementation of binary, 1D cellular automaton with sample 184 rule (http://en.wikipedia.org/wiki/Rule_184)

cellular.py

from random import uniform
import matplotlib.pyplot as plt
import numpy as np
from random import sample

n = 200 # number of cells in row
num_iters = 200 # number of iterations
density = 0.5 # how many positives

# rule 184
rules = {
	"111" : "1", "110" : "0", "101" : "1",	"100" : "1", 
	"011" : "1", "010" : "0", "001" : "0", "000" : "0"
}

# generating randomized string with fixed number of positives
positives = int(n*density)
initial = ''.join(sample(["1" if i < positives else "0" for i in range(n)],n) )

iterations = [initial]
# generating 
for i in range(num_iters):
	prev,curr = iterations[-1],""

	for j in range(n):
		if (j > 0) and (j < n -1):
			curr += rules[prev[j-1:j+2]]
		elif j == 0:
			curr += rules[prev[-1] + prev[0] + prev[1]]
		elif j == n-1:
			curr += rules[prev[-2] + prev[-1] + prev[0]]

	iterations.append(curr)

# converting to matrix
a = np.zeros(shape=(num_iters,n))
for i in range(n):
	for j in range(num_iters):
		a[j,i] = 1 if iterations[j][i] == "1" else 0

# showing image
plt.imshow(a, cmap="Greys", interpolation="nearest")
plt.show()