python - 加速元胞自动机的绘图

Question

我正在实施 Biham-Middleton-Levine 交通模型进行测试，但在实施速度方面遇到了问题。

import matplotlib.pyplot as plt
from matplotlib import colors
import numpy as np
import random

data = np.random.rand(10, 10) * 20

# create discrete colormap
cmap = colors.ListedColormap(['white','red', 'blue'])
bounds = [-0.5,0.5,1.5,2.5]
norm = colors.BoundaryNorm(bounds, cmap.N)

p = 0.5
iter = 1000

sizex = 10
sizey = 10

road = np.zeros((sizex,sizey))
for posx in range(np.shape(road)[0]):
    for posy in range(np.shape(road)[1]):
        if random.uniform(0,1)<p:
            if random.uniform(0,1)<0.5:
                road[posx][posy] = 1
            else:
                road[posx][posy] = 2

road[1][1]=1
road[1,2]=2
print(road)

def check(posx, posy, surf):
    type = surf[posx][posy]
    
    if type == 1:
        posx, posy = posy, posx
        surf = np.transpose(surf)   
    
    if posx+1<np.shape(surf)[0]:
            
        if surf[posx+1][posy] == 0:
            surf[posx][posy] = 0
            surf[posx+1][posy] = type

    elif posx+1 == np.shape(surf)[0]:

        if surf[0][posy] == 0:
            surf[0][posy] = type
            surf[posx][posy] = 0

fig, ax = plt.subplots()
ax.grid(which='major', axis='both', linestyle='-', color='k', linewidth=1)
ax.set_xticks(np.arange(-.5, sizex, 1));
ax.set_yticks(np.arange(-.5, sizey, 1));
ax.set_xticklabels([])
ax.set_yticklabels([])
                                                                                                
for iteration in range(iter):
    
    checklist_x = []
    checklist_y = []
    
    for posx in range(np.shape(road)[0]):
        for posy in range(np.shape(road)[1]):
            if road[posx][posy] == 1:
                checklist_x.append((posx,posy))             
                
    for posx in range(np.shape(road)[0]):
        for posy in range(np.shape(road)[1]):
            if road[posx][posy] == 2:
                checklist_y.append((posx,posy))
                
    for car in checklist_x:
        check(car[0],car[1],road)
        
    for car in checklist_y:
        check(car[0],car[1],road)
                
    
    ax.imshow(road, cmap=cmap, norm=norm)

    plt.show()
print('done')

我的实现运行非常缓慢，虽然这主要是由于我绘制单元格网格的方式，

fig, ax = plt.subplots()
ax.grid(which='major', axis='both', linestyle='-', color='k', linewidth=1)
ax.set_xticks(np.arange(-.5, sizex, 1));
ax.set_yticks(np.arange(-.5, sizey, 1));
ax.set_xticklabels([])
ax.set_yticklabels([])
                                                                                                
for iteration in range(iter):
    
    checklist_x = []
    checklist_y = []
    
    for posx in range(np.shape(road)[0]):
        for posy in range(np.shape(road)[1]):
            if road[posx][posy] == 1:
                checklist_x.append((posx,posy))             
                
    for posx in range(np.shape(road)[0]):
        for posy in range(np.shape(road)[1]):
            if road[posx][posy] == 2:
                checklist_y.append((posx,posy))
                
    for car in checklist_x:
        check(car[0],car[1],road)
        
    for car in checklist_y:
        check(car[0],car[1],road)
                
    
    ax.imshow(road, cmap=cmap, norm=norm)

    plt.show()
print('done')

每次迭代都会重新绘制单元格网格，这是非常密集的，并且大大超过了以数组形式计算下一次迭代应该是什么的计算时间。有没有办法缓存或避免每一步都重绘整个东西？

标签： pythonmatplotliboptimizationcellular-automata