matplotlib-devel Mailing List for matplotlib

Hi,
When improving the performance of plotting high-dimensional data using 
faceted scatter plots, I noticed that much of time was spent on the axis 
creation (even 50%!).
On my machine creating 20x20 array of subplots without actually plotting 
anything takes about 11 seconds (for comparison plotting 5000 points on 
all of them takes only 0.6s!):
import matplotlib
matplotlib.interactive(True)
import matplotlib.pyplot as plt
fig, axes = plt.subplots(20,20)
plt.show()
Profiling shows that 50% of computation time is spent on axis/ticks 
creation [1], which I have to remove anyways. Is there any easy way of 
creating thinned axes without ticks and spines?
So far I solved the problem by subclassing Axes class (see this gist 
[2]) and removing all spines and ticks. Running the above example gives 
a 10x boost in performance (from 11s to 0.9s).
import thin_axes
fig, axes = plt.subplots(20,20, subplot_kw=dict(projection='thin'))
plt.show()
Profiling results show more uniform distribution of computing time 
across functions (most time is spent on creating and applying transforms 
[3]).
The thinned class seems a bit hacky. Is there any other way to create a 
raw Axes object without spines, ticks, labels etc., just pure canvas 
with appropriate transforms?
Yours,
Bartosz
[1] profiling results of vanilla Axes: http://pbrd.co/1jlovoo
[2] https://gist.github.com/btel/a6b97e50e0f26a1a5eaa
[3] profiling results of thined Axes: