forked from TheAlgorithms/Python
-
Notifications
You must be signed in to change notification settings - Fork 0
/
game_of_life.py
129 lines (104 loc) · 2.96 KB
/
game_of_life.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
"""Conway's Game Of Life, Author Anurag Kumar(mailto:[email protected])
Requirements:
- numpy
- random
- time
- matplotlib
Python:
- 3.5
Usage:
- $python3 game_of_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_name <size_of_canvas:int>"
choice = [0] * 100 + [1] * 10
random.shuffle(choice)
def create_canvas(size: int) -> list[list[bool]]:
canvas = [[False for i in range(size)] for j in range(size)]
return canvas
def seed(canvas: list[list[bool]]) -> None:
for i, row in enumerate(canvas):
for j, _ in enumerate(row):
canvas[i][j] = bool(random.getrandbits(1))
def run(canvas: list[list[bool]]) -> list[list[bool]]:
"""
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:
--
canvas of population after one step
"""
current_canvas = np.array(canvas)
next_gen_canvas = np.array(create_canvas(current_canvas.shape[0]))
for r, row in enumerate(current_canvas):
for c, pt in enumerate(row):
next_gen_canvas[r][c] = __judge_point(
pt, current_canvas[r - 1 : r + 2, c - 1 : c + 2]
)
return next_gen_canvas.tolist()
def __judge_point(pt: bool, neighbours: list[list[bool]]) -> bool:
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 in {2, 3}:
state = True
elif alive > 3:
state = False
elif 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