matplotlib-users Mailing List for matplotlib

Hi Daniel,
For what it's worth, the code runs perfectly for me as-is on matplotlib
1.3.1 with python 2.7 on linux.
However, based on your description, I'd guess that the second call to
`twinx` is returning the same axes object.
What happens when you do:
print id(axes[1]), id(axes[2])
Are the id numbers the same or different?
If they're the same, there may have been a regression/change that causes
`twinx` to return the same object instead of creating a new axes.
Cheers!
-Joe
On Wed, Nov 27, 2013 at 5:08 PM, dodermat <dan...@gm...> wrote:
> Dear all
>
> What I want to accomplish was produced two years ago in a stackoverflow
> snippet by Joe Kington
> <
> http://stackoverflow.com/questions/7733693/matplotlib-overlay-plots-with-different-scales
> >
> , and shown in the first figure below. However, when I use his snippet in
> matplotlib 1.3.x, I get an output where the third axis replaces the second
> axis, and the blue dots are accordingly distributed in only the lower half
> of the plot (see second figure below). I considered downdating to an older
> version of matplotlib, but then I came across a remark in the matplotlib
> FAQ <http://matplotlib.org/faq/howto_faq.html#multiple-y-axis-scales> .
> According to this remark, such a feature for twinx is on the wish list and
> thus not very likely to be available in an older version.
>
> Can someone please explain the Kington magic to me?
>
>
> <http://matplotlib.1069221.n5.nabble.com/file/n42556/ksRXk.png>
> <http://matplotlib.1069221.n5.nabble.com/file/n42556/figure_1.png>
>
>
>
> --
> View this message in context:
> http://matplotlib.1069221.n5.nabble.com/Plotting-with-more-than-two-y-axes-with-twinx-tp42556.html
> Sent from the matplotlib - users mailing list archive at Nabble.com.
>
>
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Dear all
What I want to accomplish was produced two years ago in a stackoverflow
snippet by Joe Kington
<http://stackoverflow.com/questions/7733693/matplotlib-overlay-plots-with-different-scales> 
, and shown in the first figure below. However, when I use his snippet in
matplotlib 1.3.x, I get an output where the third axis replaces the second
axis, and the blue dots are accordingly distributed in only the lower half
of the plot (see second figure below). I considered downdating to an older
version of matplotlib, but then I came across a remark in the matplotlib
FAQ <http://matplotlib.org/faq/howto_faq.html#multiple-y-axis-scales> .
According to this remark, such a feature for twinx is on the wish list and
thus not very likely to be available in an older version.
Can someone please explain the Kington magic to me?
<http://matplotlib.1069221.n5.nabble.com/file/n42556/ksRXk.png> 
<http://matplotlib.1069221.n5.nabble.com/file/n42556/figure_1.png> 
--
View this message in context: http://matplotlib.1069221.n5.nabble.com/Plotting-with-more-than-two-y-axes-with-twinx-tp42556.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Hi,
when running basic_example_writer.py, I get *.mp4 files with a canvas
size of 800x600 pixels (at least that's what mplayer tells me). However,
I have trouble understanding where this canvas size comes from. The
example does not explicitly set the dpi or the figure size, and I don't
have a matplotlibrc which changes these settings. So figure.dpi is 80,
and the fig.size_inches is (8, 6). So how come this translates to a
800x600 pixel movie?
Thanks for you insight :)
-- Andreas.

The gist here is that `subplot` doesn't really know when the new subplot 
exactly overlaps another -- it's essentially unaware of what's already 
there. We could do some deduplication there. However, it's also a 
completely legitimate use case to create two subplots in the same 
location, and then change the location of the ticks, formatting and 
scale on one of them and not the other. And we can't really guess which 
the user intends to do. Your workaround seems like a good one, in the 
absence of really changing the API here so matplotlib can know the 
user's intent.
Mike
On 11/26/2013 08:23 PM, John Gu wrote:
> Hello,
>
> I had submitted a similar issue back in October of 2011. I'm using 
> matplotlib 1.3.1. Here's the code to produce the issue:
>
> f = figure()
> for i in xrange(9): subplot(3,3,i+1)
> f.axes[0].plot(range(100))
>
> Now try to drag the line in the first subplot around. It's extremely 
> slow. Now do the following:
>
> for ax in f.axes[1:]: ax.axison=False
>
> Now, when you drag the line around in the first subplot, there's a 
> huge difference. Basically, it seems like that matplotlib is 
> attempting to redraw a lot of unnecessary things on the figure. Is 
> there an easy fix to this?
>
> Thanks,
> John
>
>
> ------------------------------------------------------------------------------
> Rapidly troubleshoot problems before they affect your business. Most IT
> organizations don't have a clear picture of how application performance
> affects their revenue. With AppDynamics, you get 100% visibility into your
> Java,.NET, & PHP application. Start your 15-day FREE TRIAL of AppDynamics Pro!
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>
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Hello,
I had submitted a similar issue back in October of 2011. I'm using
matplotlib 1.3.1. Here's the code to produce the issue:
f = figure()
for i in xrange(9): subplot(3,3,i+1)
f.axes[0].plot(range(100))
Now try to drag the line in the first subplot around. It's extremely slow.
 Now do the following:
for ax in f.axes[1:]: ax.axison=False
Now, when you drag the line around in the first subplot, there's a huge
difference. Basically, it seems like that matplotlib is attempting to
redraw a lot of unnecessary things on the figure. Is there an easy fix to
this?
Thanks,
John