Python-Timing.py

#Written by David Butts
#This code is an implementation of a Rule 30 Wolfram model written in Python.
import numpy as np
import time
def Rule30_code():
    Rule30 = np.zeros((1000,100000)) #initilize an array to run on (timesteps, width)
    Rule30[0,50] = 1
    for y in range(Rule30.shape[0]-1): #iterate through grid
        for x in range(Rule30.shape[1]):
            #update the next rows values according to neighbor & self value
            right = x + 1
            down = y + 1
            left = x - 1
            if right >= Rule30.shape[1]:
                right = 0
            if Rule30[y,right] == 1 and Rule30[y,left] == 0:
                Rule30[down,x] = 1
            elif Rule30[y,x] == 0 and Rule30[y,right] == 0 and Rule30[y,left] == 1:
                Rule30[down,x] = 1
            elif Rule30[y,x] == 1 and Rule30[y,right] == 0 and Rule30[y,left] == 0:
                Rule30[down,x] = 1
            else:
                Rule30[down,x] = 0
#average run time for 10 runs
av_time = 0
for run in range(10):
    start = time.time()
    Rule30_code()
    end = time.time()
    av_time += (end-start)
print(av_time/10.0, 'seconds for 10 runs')