如何在 python 中使用带有 matplotlib 的 for 循环创建多个视图？

Question

我需要在 python 中使用 matplotlib 制作 100 个视图。起点总是随机的。我知道如何生成 100 个图，但我想使用“前进到下一个视图”箭头。

这是我的代码：

import matplotlib.pyplot as plt


for i in range (1,3):

    Startx = [randrange(1, 19)]  # x axis values
    Starty = [randrange(1, 8)]  # y axis values

    plt.plot(Startx, Starty, color='black', linestyle='solid', linewidth=3,  # plotting the points
             marker='o', markerfacecolor='green', markersize=8)

    ##########################################################################################################
    Endx = [16.5]
    Endy = [7.5]

    plt.plot(Endx, Endy, color='black', linestyle='solid', linewidth=3,
             marker='o', markerfacecolor='red', markersize=8)

    ##########################################################################################################

    Ax = [5, 2.5, 3, 5, 6, 5]
    Ay = [7.5, 6, 3.5, 3, 5.5, 7.5]

    plt.plot(Ax, Ay, color='black', linestyle='solid', linewidth=3,
             marker='o', markerfacecolor='blue', markersize=8)

    ##########################################################################################################

    Bx = [8, 6.5, 7.25, 8]
    By = [3, 3, 5.5, 3]

    plt.plot(Bx, By, color='black', linestyle='solid', linewidth=3,
             marker='o', markerfacecolor='blue', markersize=8)

    plt.xlim(0, 19)
    plt.ylim(0, 8)  # setting x and y axis range

    plt.xlabel('x - axis')  # naming the x axis
    plt.ylabel('y - axis')  # naming the y axis

    plt.show()  # function to show the plot

Answer 1

您可以尝试本文中提到的这种方法 matplotlib hooking in to home/back/forward button events 不要覆盖“主页”按钮，而是使用“前进”按钮。

另见这个小例子。每次按下“前进到下一个视图”按钮，绘图都会更新一些随机数据。

from matplotlib.backends.backend_tkagg import NavigationToolbar2Tk
import matplotlib.pyplot as plt
from random import randint

#new forward button callback => gets triggered, when forward button gets pushed
def customForward(*args):
    ax = plt.gca()
    fig = plt.gcf()
    
    #get line object...
    line = ax.get_lines()[0]
    
    #...create some new random data...
    newData = [randint(1, 10), randint(1, 10), randint(1, 10)]
    
    #...and update displayed data
    line.set_ydata(newData)
    ax.set_ylim(min(newData), max(newData))
    #redraw canvas or new data won't be displayed
    fig.canvas.draw()

#monkey patch forward button callback
NavigationToolbar2Tk.forward = customForward

#plot first data
plt.plot([1, 2, 3], [1, 2, 3])
plt.show()