matplotlib-users Mailing List for matplotlib

Hello everybody,
I am trying to write a rule for AwesomeWM, so that all matplotlib
related windows would be floating and not tiled. For this purpose I want
to filter matplotlib windows by some window attribute, like class,
instance or title. Is there a way to modify the window class or instance
easily?
I already know how to modify the title of the window, but this is not
sufficient as any dialogs, which would be created from the toolbar on
the plot window will not have the same title and the filtering can not
be applied to them.
If I have not explained this clearly enough, please let me know, what
I need to clarify.
All best,
Ignas A.

I have an error when running my script using matplotlib using IDLE. I
suspect it is something to do with either numpy or matplotlib and I was
wondering if any other users have had a similar problem. I have recently
installed Python, matplotlib and numpy, I have not had it working correctly
using IDLE on this machine. The error message is:
Runtime Error!
Program: C:\Python27\pythonw.exe
This application has requested the Runtime to terminate it in an unusual
way.
Please contact the application's supporter team for more information.
The window header says Microsoft Visual C++ Runtime Library (which seems to
be about debugging). The error occurs about 50% of the time. When I run my
script in the command line it runs fine everytime. I am using matplotlib
and generating a pdf. If I remove the pdf generation step I still get the
error. But running another script (on the csv module) don't seem to
generate the error. I have searched on the internet without luck
(suggestion of installing visual studio which I have got) or posting to the
scipy list (well Im not using scipy).
I am using Win7 32 bit and matplotlib 1.1 and numpy 1.6.1 and python 2.7.
Has anyone else had similar message?
Catherine

Not sure if this is the right place to post this...please instruct if wrong
I'm plotting some audio data, which can get big, and alongside I have
subplots of barcharts that represent onsets, RMS etc...
Since I have many onsets plotting the whole thing at once results in such
dense barcharts that the 
graph is useless.
So currently I am plotting 5 seconds of audio with the respective barcharts
and use forward/backward buttons to skim through the data. Show next 5
seconds etc. The whole thing is embedded in PyQt.
It works but I just learned about the ScrollArea widget so I thought why not
plot the whole thing and just use scroll to move around the plot.
My main question is which is the common practice for doing this sort of
thing?
I know the data beforehand so I don't need dynamic updating. Seems scrolling
should be the easiest way to do this but I haven't found example and my code
doesn't work yet.
Thanks
Stelios
-- 
View this message in context: http://old.nabble.com/Scrolling-window-tp33477938p33477938.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

One way to use images as a marker would be to use offsetbox module.
Here is an example adopted from
http://matplotlib.sourceforge.net/examples/pylab_examples/demo_annotation_box.html
Regards,
-JJ
import matplotlib.pyplot as plt
from matplotlib.offsetbox import OffsetImage, AnnotationBbox
from matplotlib.cbook import get_sample_data
import numpy as np
if 1:
 fig = plt.gcf()
 fig.clf()
 ax = plt.subplot(111)
 xy = [0.3, 0.55]
 arr = np.arange(100).reshape((10,10))
 im = OffsetImage(arr, zoom=2)
 ab = AnnotationBbox(im, xy,
 xycoords='data',
 pad=0.3,
 )
 ax.add_artist(ab)
 # another image
 from matplotlib._png import read_png
 fn = get_sample_data("lena.png", asfileobj=False)
 arr_lena = read_png(fn)
 imagebox = OffsetImage(arr_lena, zoom=0.1)
 xy = (0.7, 0.4)
 ab = AnnotationBbox(imagebox, xy,
 xycoords='data',
 pad=0.5,
 )
 ax.add_artist(ab)
 ax.set_xlim(0, 1)
 ax.set_ylim(0, 1)
 plt.draw()
 plt.show()
On Thu, Mar 8, 2012 at 4:25 AM, Michael Droettboom <md...@st...> wrote:
> It would be a nice idea. I'm not sure it's something that would work
> terribly well in vector backends as the images may not scale well. I should
> mention that there is already support to use arbitrary Unicode characters or
> math expressions as markers already, which does work well in vector
> backends.
>
> Mike
>
>
> On 03/07/2012 01:59 PM, C M wrote:
>
> I've for now taken a different approach that means I won't need custom
> markers from images.
>
> But I'm just curious: is there any wish/plans in Matplotlib to add support
> for this? I think it could do a lot to expand what's possible in terms of
> the look and feel of plots (even without things drifing into USA Today
> territory!).
>
> Just my 0ドル.02
>
> Che
>
>
> ------------------------------------------------------------------------------
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>
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>
>
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> Cloud computing makes use of virtualization - but cloud computing
> also focuses on allowing computing to be delivered as a service.
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>

Hi, JJ,
I wonder why the simple text command does not work for you? e.g.,
>
> def add_center_text(ax):
> ax.text(0.5, 0.9075, "Centered Title", ha='center', va='center',
> fontsize=18,
> bbox=dict(boxstyle='round, pad=0.5, rounding_size=0.25',
> fc="white",
> ec="k", lw=2),
> transform=ax.transAxes)
>
>
The simple answer here is that I didn't understand what the transform
keyword argument was doing. I'm not entirely sure, still, but I gather it
has something to do with handling the changing of the axes coordinates.
 Man, I still have so much to learn about MPL....
Also, annotate command gives you more flexibility in text positioning.
>
> The axes location is supposed to be known during the drawing time. To
> get the axes position, you may do something like
>
> ax1._axes_locator(ax1, fig._cachedRenderer)
>
> Of course, this need to be done after the figure is properly drawn
> (e.g., after calling draw()) or during the drawing time.
>
>
Excellent. Thank you fot taking the time to explain how this works.
Although your first suggestion is what I need for the moment, I'm glad to
know how to get the axes positions, should I ever need them.
Thanks again!
Patrick

I wonder why the simple text command does not work for you? e.g.,
def add_center_text(ax):
 ax.text(0.5, 0.9075, "Centered Title", ha='center', va='center',
fontsize=18,
 bbox=dict(boxstyle='round, pad=0.5, rounding_size=0.25', fc="white",
 ec="k", lw=2),
 transform=ax.transAxes)
Also, annotate command gives you more flexibility in text positioning.
The axes location is supposed to be known during the drawing time. To
get the axes position, you may do something like
 ax1._axes_locator(ax1, fig._cachedRenderer)
Of course, this need to be done after the figure is properly drawn
(e.g., after calling draw()) or during the drawing time.
Regards,
-JJ
On Sat, Mar 10, 2012 at 1:00 PM, Patrick Marsh <pat...@gm...> wrote:
> Hi, All,
>
> Here's an update to the problem I submitted last night.
>
> I was able to utilize anchored text to work for centering a title, which is
> ultimately what I'm wanting to do now. (Although, I'd still like to know the
> proper way to get the axes bounds when using axes_divider). The new problem
> lies how to horizontally align the text inside the anchored box. When the
> horizontal alignment is "left", the text lines up in the anchored box.
> However, as the updated example below shows, then you use "center" or
> "right", the text is now positioned outside the anchored box. Is this a bug
> in how the text is aligned? If so, how might I go about tracking it down?
>
>
> https://gist.github.com/2004869 (rev: b984ca)
>
>
> Cheers,
> Patrick
> ---
> Patrick Marsh
> Ph.D. Student / Liaison to the HWT
> School of Meteorology / University of Oklahoma
> Cooperative Institute for Mesoscale Meteorological Studies
> National Severe Storms Laboratory
> http://www.patricktmarsh.com
>
>
>
> On Fri, Mar 9, 2012 at 12:12 AM, Patrick Marsh <pat...@gm...>
> wrote:
>>
>> Greetings,
>>
>> Let me begin by saying that I've fallen in love with ImageGrid. I love the
>> control it gives me in setting up plots, and I really like the control it
>> offers for setting up a colorbar. Unfortunately, like all relationships,
>> ImageGrid and I have hit a rough patch.
>>
>> I like to manually place titles and other boxes of texts on plots that I
>> make using ImageGrid. However, to center things I have to know what the axes
>> bounds are so I can do the centering calculations. Unfortunately, when using
>> ImageGrid, or axes_divider, I have yet to find a way to get the axes bounds
>> that are actually used to do the plotting. When I try to use
>>
>> ax.get_position().bounds
>>
>> I get the pre-adjusted bounds, even if I use plt.draw() before requesting
>> the axes_positions. This means the only way I can center the text is by
>> guessing what the final axes bounds will be. Is there any way of getting
>> the final bounds? It appears anchored text is able to do it, but I haven't
>> been able to...
>>
>>
>> Here's a self-contained example script that demonstrates the problem. I
>> don't use ImageGrid, instead using axes_divider, however this is the same
>> problem that AxesGrid has. (I'm guessing this is because ImageGrid
>> ultimately does what I did here behind the scenes.)
>>
>> https://gist.github.com/2004869
>>
>>
>> Thanks for any help!
>>
>>
>> Patrick
>> ---
>> Patrick Marsh
>> Ph.D. Student / Liaison to the HWT
>> School of Meteorology / University of Oklahoma
>> Cooperative Institute for Mesoscale Meteorological Studies
>> National Severe Storms Laboratory
>> http://www.patricktmarsh.com
>>
>>
>
>
> ------------------------------------------------------------------------------
> Virtualization & Cloud Management Using Capacity Planning
> Cloud computing makes use of virtualization - but cloud computing
> also focuses on allowing computing to be delivered as a service.
> http://www.accelacomm.com/jaw/sfnl/114/51521223/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Hi, All,
Here's an update to the problem I submitted last night.
I was able to utilize anchored text to work for centering a title, which is
ultimately what I'm wanting to do now. (Although, I'd still like to know
the proper way to get the axes bounds when using axes_divider). The new
problem lies how to horizontally align the text inside the anchored box.
When the horizontal alignment is "left", the text lines up in the anchored
box. However, as the updated example below shows, then you use "center" or
"right", the text is now positioned outside the anchored box. Is this a
bug in how the text is aligned? If so, how might I go about tracking it
down?
https://gist.github.com/2004869 (rev: b984ca)
Cheers,
Patrick
---
Patrick Marsh
Ph.D. Student / Liaison to the HWT
School of Meteorology / University of Oklahoma
Cooperative Institute for Mesoscale Meteorological Studies
National Severe Storms Laboratory
http://www.patricktmarsh.com
On Fri, Mar 9, 2012 at 12:12 AM, Patrick Marsh <pat...@gm...>wrote:
> Greetings,
>
> Let me begin by saying that I've fallen in love with ImageGrid. I love the
> control it gives me in setting up plots, and I really like the control it
> offers for setting up a colorbar. Unfortunately, like all relationships,
> ImageGrid and I have hit a rough patch.
>
> I like to manually place titles and other boxes of texts on plots that I
> make using ImageGrid. However, to center things I have to know what the
> axes bounds are so I can do the centering calculations. Unfortunately, when
> using ImageGrid, or axes_divider, I have yet to find a way to get the axes
> bounds that are actually used to do the plotting. When I try to use
>
> ax.get_position().bounds
>
> I get the pre-adjusted bounds, even if I use plt.draw() before requesting
> the axes_positions. This means the only way I can center the text is by
> guessing what the final axes bounds will be. Is there any way of getting
> the final bounds? It appears anchored text is able to do it, but I haven't
> been able to...
>
>
> Here's a self-contained example script that demonstrates the problem. I
> don't use ImageGrid, instead using axes_divider, however this is the same
> problem that AxesGrid has. (I'm guessing this is because ImageGrid
> ultimately does what I did here behind the scenes.)
>
> https://gist.github.com/2004869
>
>
> Thanks for any help!
>
>
> Patrick
> ---
> Patrick Marsh
> Ph.D. Student / Liaison to the HWT
> School of Meteorology / University of Oklahoma
> Cooperative Institute for Mesoscale Meteorological Studies
> National Severe Storms Laboratory
> http://www.patricktmarsh.com
>
>
>