Python - matplotlib.pyplot ion() 慢

Question

我正在尝试更新我的迷宫，因为对解决方案的搜索是连续的(这是一个简单的迷宫统一成本搜索)。我正在使用 pyplots ion() 在每次节点访问后更新我的图形。我的问题是该图更新非常慢，大约迭代 20 次。我尝试减小 pause() 的值，但似乎没有效果。我很确定这不是我的电脑。

import matplotlib.pyplot as plt
from matplotlib import colors as c
import math
import numpy as np

class Queue:
    def __init__(self):
        self.items = []

    def isEmpty(self):
        return self.items == []

    def enqueue(self, item):
        self.items.insert(0,item)

    def dequeue(self):
        return self.items.pop()

    def size(self):
        return len(self.items)

def euclideanDistance(pos1, pos2):
    return math.sqrt(math.pow((pos2[0]-pos1[0]),2) + math.pow((pos2[1]-pos1[1]),2))

def getChildren(node, maze):
    children = []
    y = node[0]
    x = node[1]
    i = 0
    if y-1 != -1 and maze[y-1][x] != 1 and maze[y-1][x] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x)
        i += 1
    if y-1 != -1 and x+1 != 12 and maze[y-1][x+1] != 1 and maze[y-1][x+1] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x+1)
        i += 1
    if x+1 != 12 and maze[y][x+1] != 1 and maze[y][x+1] != '.':
        children.append([])
        children[i].append(y)
        children[i].append(x+1)
        i += 1
    if y+1 != 12 and x-1 != -1 and maze[y+1][x-1] != 1 and maze[y+1][x-1] != 2:
        children.append([])
        children[i].append(y+1)
        children[i].append(x-1)
        i += 1
    if y+1 != 12 and maze[y+1][x] != 1 and maze[y+1][x] != '.':
        children.append([])
        children[i].append(y+1)
        children[i].append(x)
        i += 1
    if y+1 != 12 and x+1 != 12 and maze[y+1][x+1] != 1 and maze[y+1][x+1] != 2:
        children.append([])
        children[i].append(y+1)
        children[i].append(x+1)
        i += 1
    if x-1 != -1 and maze[y][x-1] != 1 and maze[y][x-1] != 2:
        children.append([])
        children[i].append(y)
        children[i].append(x-1)
        i += 1
    if y-1 != -1 and x-1 != -1 and maze[y-1][x-1] != 1 and maze[y-1][x-1] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x-1)
        i += 1
    return children

def uniformCostSearch(root, goal, maze):
    q = Queue()
    path = maze
    root.append(0)
    q.enqueue(root)
    while not q.isEmpty():
        temp = q.dequeue()
        printMaze(path)
        path[temp[0]][temp[1]] = 2
        if temp[0] == goal[0] and temp[1] == goal[1]:
            return path
        else:
            children = getChildren(temp, path)
            cArray = []
            if len(children) != 0:
                for child in children:
                    child.append(temp[2]+euclideanDistance(temp, child))
                    cArray.append(child)
                cArray.sort(key=lambda x:x[2])
                for child in cArray:
                    q.enqueue(child)

def printMaze(maze):
    y = [12,11,10,9,8,7,6,5,4,3,2,1,0]
    x = [0,1,2,3,4,5,6,7,8,9,10,11,12]
    x, y = np.meshgrid(x, y)
    maze = np.array(maze)
    plt.ion()
    cMap = c.ListedColormap(['w','grey','green','red'])
    plt.xticks([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], [0,1,2,3,4,5,6,7,8,9,10,11])
    plt.yticks([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], [0,1,2,3,4,5,6,7,8,9,10,11])
    plt.pcolormesh(x, y, maze, edgecolor='k',cmap=cMap)
    plt.pause(0.000000001)
    plt.show()

maze = [[0,0,0,0,0,0,0,0,0,0,0,0],
        [0,1,1,1,1,1,1,1,1,1,1,0],
        [0,1,1,1,1,1,1,1,0,3,1,0],
        [0,0,0,0,0,0,1,1,0,0,1,0],
        [0,1,1,0,0,0,1,1,0,0,1,0],
        [0,1,1,0,0,0,1,1,0,0,1,0],
        [0,1,0,0,0,0,1,1,0,0,1,0],
        [0,0,0,0,0,1,1,1,0,0,1,0],
        [0,0,0,0,1,1,1,1,0,0,1,0],
        [0,0,0,1,1,1,1,1,0,0,1,0],
        [0,0,1,1,1,1,1,1,0,0,0,0],
        [0,0,0,0,0,0,0,0,0,0,0,0]]

root = []
root.append(11)
root.append(0)

goal = []
goal.append(2)
goal.append(9)

printMaze(maze)
uniformCostSearch(root, goal, maze)

Answer 1

这是一个基本示例，展示了如何为 Quadmesh(例如 pcolormesh 返回的那个)设置动画。您需要做的就是(哈!)修改 step 以生成您希望显示的迷宫。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.animation as animation

def step():
    while True:
        yield np.random.randint(4, size=(N, N))

def animate(data, quadmesh):
    quadmesh.set_array(data.ravel())
    return [quadmesh]

N = 12
maze = np.random.randint(4, size=(N, N))

fig, ax = plt.subplots()
cmap = mcolors.ListedColormap(['w','grey','green','red'])
x, y = np.meshgrid(np.arange(N), np.arange(N))
quadmesh = ax.pcolormesh(x, y, maze, edgecolor='k',cmap=cmap)

ani = animation.FuncAnimation(
    fig, animate, step, 
    interval=10, fargs=(quadmesh,), repeat=True, blit=True)
plt.show()

减少FuncAnimation中的interval参数以减少之间的延迟帧。这将使动画播放得更快。你会发现没有使动画运行得很快的问题。

尽管更新单个quadmesh(如上所述)比调用更快pcolormesh 多次且 plt.ion 打开，这是您的主要原因动画进展缓慢是因为 printMaze(path) 被多次调用相同的路径。

您可以通过将 printMaze 修改为

来确认此声明

def printMaze(maze):
    print(maze)
    print('-'*80)

您会在终端中看到迷宫通常是同一个迷宫次。因此，为了让你的动画更快，你需要让你的uniformCostSearch 更智能。也许使用一组来记住具有以下特征的迷宫已经显示，在这种情况下不要再次调用 printMaze:

import math
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.animation as animation

class Queue:
    def __init__(self):
        self.items = []

    def isEmpty(self):
        return self.items == []

    def enqueue(self, item):
        self.items.insert(0,item)

    def dequeue(self):
        return self.items.pop()

    def size(self):
        return len(self.items)

def euclideanDistance(pos1, pos2):
    return math.sqrt(math.pow((pos2[0]-pos1[0]),2) + math.pow((pos2[1]-pos1[1]),2))

def getChildren(node, maze):
    children = []
    y = node[0]
    x = node[1]
    i = 0
    if y-1 != -1 and maze[y-1][x] != 1 and maze[y-1][x] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x)
        i += 1
    if y-1 != -1 and x+1 != 12 and maze[y-1][x+1] != 1 and maze[y-1][x+1] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x+1)
        i += 1
    if x+1 != 12 and maze[y][x+1] != 1 and maze[y][x+1] != '.':
        children.append([])
        children[i].append(y)
        children[i].append(x+1)
        i += 1
    if y+1 != 12 and x-1 != -1 and maze[y+1][x-1] != 1 and maze[y+1][x-1] != 2:
        children.append([])
        children[i].append(y+1)
        children[i].append(x-1)
        i += 1
    if y+1 != 12 and maze[y+1][x] != 1 and maze[y+1][x] != '.':
        children.append([])
        children[i].append(y+1)
        children[i].append(x)
        i += 1
    if y+1 != 12 and x+1 != 12 and maze[y+1][x+1] != 1 and maze[y+1][x+1] != 2:
        children.append([])
        children[i].append(y+1)
        children[i].append(x+1)
        i += 1
    if x-1 != -1 and maze[y][x-1] != 1 and maze[y][x-1] != 2:
        children.append([])
        children[i].append(y)
        children[i].append(x-1)
        i += 1
    if y-1 != -1 and x-1 != -1 and maze[y-1][x-1] != 1 and maze[y-1][x-1] != 2:
        children.append([])
        children[i].append(y-1)
        children[i].append(x-1)
        i += 1
    return children

def step():
    seen = set()
    q = Queue()
    path = maze
    root.append(0)
    q.enqueue(root)
    while not q.isEmpty():
        temp = q.dequeue()
        frozen = tuple(map(tuple, path))
        if frozen not in seen:
            seen.add(frozen)
            yield path
        path[temp[0]][temp[1]] = 2
        if temp[0] == goal[0] and temp[1] == goal[1]:
            return path
        else:
            children = getChildren(temp, path)
            cArray = []
            if len(children) != 0:
                for child in children:
                    child.append(temp[2]+euclideanDistance(temp, child))
                    cArray.append(child)
                cArray.sort(key=lambda x:x[2])
                for child in cArray:
                    q.enqueue(child)


def animate(data, quadmesh):
    quadmesh.set_array(data.ravel())
    return [quadmesh]

maze = np.array([[0,0,0,0,0,0,0,0,0,0,0,0],
                 [0,1,1,1,1,1,1,1,1,1,1,0],
                 [0,1,1,1,1,1,1,1,0,3,1,0],
                 [0,0,0,0,0,0,1,1,0,0,1,0],
                 [0,1,1,0,0,0,1,1,0,0,1,0],
                 [0,1,1,0,0,0,1,1,0,0,1,0],
                 [0,1,0,0,0,0,1,1,0,0,1,0],
                 [0,0,0,0,0,1,1,1,0,0,1,0],
                 [0,0,0,0,1,1,1,1,0,0,1,0],
                 [0,0,0,1,1,1,1,1,0,0,1,0],
                 [0,0,1,1,1,1,1,1,0,0,0,0],
                 [0,0,0,0,0,0,0,0,0,0,0,0]])
root = [11, 0]
goal = [2, 9]

fig, ax = plt.subplots()
x = np.arange(13)
y = x[::-1]
X, Y = np.meshgrid(x, y)
plt.xticks([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], [0,1,2,3,4,5,6,7,8,9,10,11])
plt.yticks([0.5,1.5,2.5,3.5,4.5,5.5,6.5,7.5,8.5,9.5,10.5,11.5], [0,1,2,3,4,5,6,7,8,9,10,11])

cmap = mcolors.ListedColormap(['w','grey','green','red'])
quadmesh = ax.pcolormesh(X, Y, maze, edgecolor='k',cmap=cmap)

ani = animation.FuncAnimation(
    fig, animate, step, 
    interval=10, fargs=[quadmesh], repeat=False, blit=True)
plt.show()