game of life Algorithm
It was created and co-designed by toy and game designer Reuben Klamer and was" heartily endorsed" by art Linkletter. It is now part of the permanent collection of the Smithsonian's National Museum of American history and an inductee into the National Toy Hall of Fame. The game was originally created in 1860 by Milton Bradley as The Checkered game of life, and was the first game created by Bradley, a successful lithographer. like many 19th-century games, such as The Mansion of Happiness by S. B. Ives in 1843, it had a strong moral message. instead of dice – which were associated with gambling – players used a six-sided top named a teetotum.
"""Conway's Game Of Life, Author Anurag Kumar(mailto:anuragkumarak95@gmail.com)
Requirements:
- numpy
- random
- time
- matplotlib
Python:
- 3.5
Usage:
- $python3 game_o_life <canvas_size:int>
Game-Of-Life Rules:
1.
Any live cell with fewer than two live neighbours
dies, as if caused by under-population.
2.
Any live cell with two or three live neighbours lives
on to the next generation.
3.
Any live cell with more than three live neighbours
dies, as if by over-population.
4.
Any dead cell with exactly three live neighbours be-
comes a live cell, as if by reproduction.
"""
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
usage_doc = "Usage of script: script_nama <size_of_canvas:int>"
choice = [0] * 100 + [1] * 10
random.shuffle(choice)
def create_canvas(size):
canvas = [[False for i in range(size)] for j in range(size)]
return canvas
def seed(canvas):
for i, row in enumerate(canvas):
for j, _ in enumerate(row):
canvas[i][j] = bool(random.getrandbits(1))
def run(canvas):
""" This function runs the rules of game through all points, and changes their status accordingly.(in the same canvas)
@Args:
--
canvas : canvas of population to run the rules on.
@returns:
--
None
"""
canvas = np.array(canvas)
next_gen_canvas = np.array(create_canvas(canvas.shape[0]))
for r, row in enumerate(canvas):
for c, pt in enumerate(row):
# print(r-1,r+2,c-1,c+2)
next_gen_canvas[r][c] = __judge_point(
pt, canvas[r - 1 : r + 2, c - 1 : c + 2]
)
canvas = next_gen_canvas
del next_gen_canvas # cleaning memory as we move on.
return canvas.tolist()
def __judge_point(pt, neighbours):
dead = 0
alive = 0
# finding dead or alive neighbours count.
for i in neighbours:
for status in i:
if status:
alive += 1
else:
dead += 1
# handling duplicate entry for focus pt.
if pt:
alive -= 1
else:
dead -= 1
# running the rules of game here.
state = pt
if pt:
if alive < 2:
state = False
elif alive == 2 or alive == 3:
state = True
elif alive > 3:
state = False
else:
if alive == 3:
state = True
return state
if __name__ == "__main__":
if len(sys.argv) != 2:
raise Exception(usage_doc)
canvas_size = int(sys.argv[1])
# main working structure of this module.
c = create_canvas(canvas_size)
seed(c)
fig, ax = plt.subplots()
fig.show()
cmap = ListedColormap(["w", "k"])
try:
while True:
c = run(c)
ax.matshow(c, cmap=cmap)
fig.canvas.draw()
ax.cla()
except KeyboardInterrupt:
# do nothing.
pass
