mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 05:21:09 +00:00
75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
"""
|
|
Return an image of 16 generations of one-dimensional cellular automata based on a given
|
|
ruleset number
|
|
https://mathworld.wolfram.com/ElementaryCellularAutomaton.html
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
from PIL import Image # type: ignore
|
|
|
|
# Define the first generation of cells
|
|
# fmt: off
|
|
CELLS = [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1,
|
|
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
|
|
# fmt: on
|
|
|
|
|
|
def format_ruleset(ruleset: int) -> list[int]:
|
|
"""
|
|
>>> format_ruleset(11100)
|
|
[0, 0, 0, 1, 1, 1, 0, 0]
|
|
>>> format_ruleset(0)
|
|
[0, 0, 0, 0, 0, 0, 0, 0]
|
|
>>> format_ruleset(11111111)
|
|
[1, 1, 1, 1, 1, 1, 1, 1]
|
|
"""
|
|
return [int(c) for c in f"{ruleset:08}"[:8]]
|
|
|
|
|
|
def new_generation(cells: list[list[int]], rule: list[int], time: int) -> list[int]:
|
|
population = len(cells[0]) # 31
|
|
next_generation = []
|
|
for i in range(population):
|
|
# Get the neighbors of each cell
|
|
# Handle neighbours outside bounds by using 0 as their value
|
|
left_neighbor = 0 if i == 0 else cells[time][i - 1]
|
|
right_neighbor = 0 if i == population - 1 else cells[time][i + 1]
|
|
# Define a new cell and add it to the new generation
|
|
situation = 7 - int(f"{left_neighbor}{cells[time][i]}{right_neighbor}", 2)
|
|
next_generation.append(rule[situation])
|
|
return next_generation
|
|
|
|
|
|
def generate_image(cells: list[list[int]]) -> Image.Image:
|
|
"""
|
|
Convert the cells into a greyscale PIL.Image.Image and return it to the caller.
|
|
>>> from random import random
|
|
>>> cells = [[random() for w in range(31)] for h in range(16)]
|
|
>>> img = generate_image(cells)
|
|
>>> isinstance(img, Image.Image)
|
|
True
|
|
>>> img.width, img.height
|
|
(31, 16)
|
|
"""
|
|
# Create the output image
|
|
img = Image.new("RGB", (len(cells[0]), len(cells)))
|
|
pixels = img.load()
|
|
# Generates image
|
|
for w in range(img.width):
|
|
for h in range(img.height):
|
|
color = 255 - int(255 * cells[h][w])
|
|
pixels[w, h] = (color, color, color)
|
|
return img
|
|
|
|
|
|
if __name__ == "__main__":
|
|
rule_num = bin(int(input("Rule:\n").strip()))[2:]
|
|
rule = format_ruleset(int(rule_num))
|
|
for time in range(16):
|
|
CELLS.append(new_generation(CELLS, rule, time))
|
|
img = generate_image(CELLS)
|
|
# Uncomment to save the image
|
|
# img.save(f"rule_{rule_num}.png")
|
|
img.show()
|