So in a figure
where three vertical subplots have been added with add_subplot
, how can I select let's say the middle one?
Right now I do this list comprehension:
[r[0] for r in sorted([[ax, ax.get_geometry()[2]] for ax in self.figure.get_axes()], key=itemgetter(1))]
where I can simply select the index I want, with the corresponding axes
. Is there a more straightforward way of doing this?
All you need to do is assign an integer to number_of_plots variable. If the X and Y values are different for each plot you will need to assign them for each plot. subplot works as follows, if for example I had a subplot values of 3,1,1 . This creates a 3x1 grid and places the plot in the 1st position.
The tight_layout() function in pyplot module of matplotlib library is used to automatically adjust subplot parameters to give specified padding.
Using subplots_adjust() method to set the spacing between subplots. We can use the plt. subplots_adjust() method to change the space between Matplotlib subplots. The parameters wspace and hspace specify the space reserved between Matplotlib subplots.
Subplots mean groups of axes that can exist in a single matplotlib figure. subplots() function in the matplotlib library, helps in creating multiple layouts of subplots. It provides control over all the individual plots that are created. Matplotlib Subplots in Python.
From the matplotlib documentation:
If the figure already has a subplot with key (args, kwargs) then it will simply make that subplot current and return it.
Here's an example:
import matplotlib.pyplot as plt
fig = plt.figure()
for vplot in [1,2,3]:
ax = fig.add_subplot(3,1,vplot)
ax.plot(range(10),range(10))
ax_again = fig.add_subplot(3,1,2)
ax_again.annotate("The middle one",xy=(7,5),xytext=(7,5))
plt.show()
The middle plot is called again so that it can be annotated.
What if I set the background with my original call, do I need to set it again when I get the subplot the second time?
Yes. The arguments and keywords for the original call are used to make a unique identifier. So for the figure to generate this unique identifier again, you need to pass the same arguments (grid definition, position) and keywords again. For example:
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(2,1,1,axisbg='red')
ax.plot(range(10),range(10))
ax = fig.add_subplot(2,1,2)
ax.plot(range(10),range(10))
ax_again = fig.add_subplot(2,1,1,axisbg='red')
ax_again.annotate("The top one",xy=(7,5),xytext=(7,5))
plt.show()
What if I use ax_again.change_geometry()
?
You would think change_geometry, e.g. from a 312 to a 422, would change how you use add_subplot, but it doesn't. There appears to be a bug or undefined behavior when you call change_geometry. The unique key that was original generated using the arguments and keywords, to the first add_subplot call, does not get updated. Therefore, if you want to get an axis back with an add_subplot call, you need to call add_subplot with the original arguments and keywords. For more info, follow this issue report: https://github.com/matplotlib/matplotlib/issues/429
My guess for now is that if you change any property of the subplot after generating it with add_subplot call, the unique will not be adjusted. So just use the original arguments and keywords, and hopefully this will work out.
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