I'm trying to draw the axes from one figure directly over the axes for
another figure, in a sense, combining the two axes as two layers on one
figure.
So, first I get an axes instance, "ax".
import matplotlib.pyplot as plt
fig=plt.figure()
fig.add_subplot(111)
plt.plot(range(10), [i^2 for i in range(10)])
ax=fig.axes[0]
plt.savefig('test.png')
Okay, now I have the axes "ax". I want to draw ax directly on top of
the following figure, and get a result that would be the same as if I
had called the plot command above directly in the following code. All
I'm passed in my real code is the newax variable below, which is why I
use newax.get_figure()).
fig=plt.figure()
newax=fig.add_subplot(111)
ax.set_figure(newax.get_figure())
newax.get_figure().add_axes(ax,label="newax")
plt.savefig('test2.png')
However, the result of test2.png is not very pretty and definitely not
what I want. The tick labels for the y-axis are all scrunched up, for
example.
Can anyone help?
For those curious, what I'm doing is working on getting the Sage
graphics code to be able to wrap and intelligently display matplotlib
axes objects, so that a person could easily create a matplotlib axes,
wrap it in the Sage graphics class, and then be able to manipulate it in
Sage. In order for this to work, it seems like I need to save the axes
object I care about, and then when Sage composes it's final figure
(using matplotlib), it passes me an AxesSubplot object. I need to
somehow take that subplot object and draw my saved axes on it in the
most intelligent way possible. In the code above, I try taking the
given AxesSubplot object, getting the figure from that, and then just
adding my saved axes to that figure. Is there a better way to do this?
Thanks,
Jason
--
Jason Grout
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