创建和引用单独的 matplotlib 图

Question

What's the best practice to create multiple separate plots using matplotlib, so they can be called later or output into a pdf report? I'm a bit unclear as to how to do this in a way that retains each plot in memory (like we could with dataframes) for later reference.

Suppose we have this code:

%pylab inline
x1 = np.random.randn(50)*100
y1 = np.random.randn(50)*100
x2 = np.random.randn(50)*100
y2 = np.random.randn(50)*100

and the intent is to create 2 separate plots of (x1,y1) and (x2,y2) and 'save' them in some way to be referenced later. the intent is to be able to output these into a PDF (perhaps via reportlab). the relationship between "figures", "subplots" and "axes" is confusing to me and not sure what is optimal for this purpose. i started with an approach like:

plt.figure(1, figsize=(8, 6))
plt.subplot(211)
plt.scatter(x1, y1, c = 'r', alpha = 0.3)

plt.subplot(212)
plt.scatter(x2, y2, c = 'k', alpha = 0.7)
plt.show()

which does technically work, but i'm not sure how i can refer to these later. also, i am using a small example here for illustration, but in practice i may have many more of these.

Answer 1

With the implicit style that the question uses (where the figure object is not saved in a variable, and where plotting commands apply to the current figure), you can easily make a previous figure the current figure:

plt.figure(1)

will thus reactivate figure 1. plt.savefig() can then be used, additional plots can be made in it, etc.

Furthermore, you can also give a name to your figure when you create it, and then refer to it:

plt.figure("growth", figsize=…)
…
plt.figure("counts", figsize=…)
…
plt.figure("growth")  # This figure becomes the active one again

(the figure reference parameter is called num , but it doesn't have to be a number and can be a string , which makes for a clearer code).

Answer 2

Things might make more sense if you start to use the object-oriented interface to matplotlib. In that case, you could do something like:

import matplotlib.pyplot as plt

fig = plt.figure(figsize=(8, 6))
ax1 = fig.add_subplot(211)
ax1.scatter(x1, y1, c = 'r', alpha = 0.3)

ax2 = fig.add_subplot(212)
ax2.scatter(x2, y2, c = 'k', alpha = 0.7)

plt.show()

In this way, its easy to see that ax1 and ax2 belong to the figure instance, fig . You can then later refer back to ax1 and ax2 , to plot more data on them, or adjust the axis limits, or add labels, etc., etc.

You can also add another figure, with its own set of subplots:

fig2 = plt.figure(figsize=(8, 6))
ax3 = fig2.add_subplot(211)

and then you can save the given figures at any point, and know that you are always referring to the correct figure:

fig.savefig('figure1.png')
fig2.savefig('figure2.png')