Jupyter：在不同的单元格中重新绘制

我想做这样的事情：

import matplotlib.pyplot as plt
%matplotlib inline
fig1 = plt.figure(1)
plt.plot([1,2,3],[5,2,4])
plt.show()

在一个单元格中，然后在另一个单元格中重新绘制完全相同的图，如下所示：

plt.figure(1) # attempting to reference the figure I created earlier...
# four things I've tried:
plt.show() # does nothing... :(
fig1.show() # throws warning about backend and does nothing
fig1.draw() # throws error about renderer
fig1.plot([1,2,3],[5,2,4]) # This also doesn't work (jupyter outputs some 
# text saying matplotlib.figure.Figure at 0x..., changing the backend and 
# using plot don't help with that either), but regardless in reality
# these plots have a lot going on and I'd like to recreate them 
# without running all of the same commands over again.

我也尝试过这些东西的一些组合，但没有任何效果。

这个问题类似于IPython：如何在不同的单元格中显示相同的图？ https://stackoverflow.com/questions/38754107/ipython-how-to-show-the-same-plot-in-different-cells但我并不是特别想update我的情节，我只是想重画它。

我找到了一个解决方案来做到这一点。诀窍是创建一个带有轴的图形fig, ax = plt.subplots()并使用轴进行绘图。然后我们就可以调用fig在任何其他单元格的末尾，我们想要重新绘制该图形。

import matplotlib.pyplot as plt
import numpy as np

x_1 = np.linspace(-.5,3.3,50)
y_1 = x_1**2 - 2*x_1 + 1

fig, ax  = plt.subplots()
plt.title('Reusing this figure', fontsize=20)
ax.plot(x_1, y_1)
ax.set_xlabel('x',fontsize=18)
ax.set_ylabel('y',fontsize=18, rotation=0, labelpad=10)
ax.legend(['Eq 1'])
ax.axis('equal');

This produces

现在我们可以使用添加更多东西ax object:

t = np.linspace(0,2*np.pi,100)
h, a = 2, 2
k, b = 2, 3
x_2 = h + a*np.cos(t)
y_2 = k + b*np.sin(t)
ax.plot(x_2,y_2)
ax.legend(['Eq 1', 'Eq 2'])
fig

Note how I just wrote fig in the last line, making the notebook output the figure once again.

我希望这有帮助！