Python-matplotlib: how to reshow a figure of subplots after having called plt.show()?

Question

I am working on jupyter notebook and I am using matplotlib.pyplot.subplot() inside a for loop. In the same cell of the for loop, I called plt.show() to show the graphs. However, they are too small, so I am looking to replot them on another notebook cell without having to repeat the loop, which is time-consuming.

So basically I ran the cell with a code that looks like this:

import matplotlib.pyplot as plt
import numpy as np
fig, axs = plt.subplots(5,1)
for ii in range(5):
    #some time consuming operations
    axs[ii].plot(np.random.randn(10))
plt.show()

I realise that the figure is too small so in the subsequent cell I would like to reshow the previous plots on a larger figure. Since all the information is contained in fig and axs I am assuming that I do not have to repeat the loop but just to tell matplotlib to show again the plots whose information should already be in the axs variable.

Answer 1

You can extract matplotlib artists from the original Figure and Axes and create new Figures and Axes using Matplotlib's oop features.

This mre creates a new Figure and Axes; gets the x and y data from each Line2D of the original axes and uses it to plot with the new Axes.

fig, ax = plt.subplots()  # Create a figure containing a single axes.
ax.plot([1, 2, 3, 4], [1, 4, 2, 3])  # Plot some data on the axes.
ax.plot([1, 2, 3, 4], [2,4,6,8])  # Plot some data on the axes.
plt.show()

fig1,ax1 = plt.subplots()
for line in ax.get_lines():
    x,y = line.get_data()
    ax1.plot(x,y)
fig1.show()

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whose information should already be in the axs variable

There is indeed a lot of stuff in those objects. It is informative to see what is in there. Try:

>>> from pprint import pprint
>>> pprint(fig.properties())

and

>>> pprint(ax.properties())

and

>>> for line in ax.get_lines():
...     pprint(line.properties())

I recommend working through the Matplotlib Tutorials , sometimes using the OOP features are the best/easiest way to really fine-tune your plots. Even after that you'll need to consult the documentation for the Artists to look for specific methods and attribute.

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Anatomy of a Figure