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Showing 7 results of 7

From: Filipe P. A. F. <oc...@gm...> - 2010年11月15日 23:02:25
Since you are using OpenSuse, (and If you are brave enough) you can
add my REPO and use the latest version of matplolib:
http://download.opensuse.org/repositories/home:/ocefpaf/openSUSE_11.3/
I compile the svn version every week there.
Filipe.
On Mon, Nov 15, 2010 at 13:45, Michael Droettboom <md...@st...> wrote:
> Since their package is crashing, I would report this bug against OpenSUSE's python-matplotlib package.
>
> If that doesn't get you any response, it would be helpful to get a better idea of where it is failing. Can you provide a gdb backtrace?
>
> Mike
>
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>
From: Chloe L. <ch...@be...> - 2010年11月15日 20:10:48
I think the pretty-fying done in the Colorbar class will make this 
harder; at least, twiny on an existing colorbar doesn't work 
(overwrites original ticks); having two colorbars works fine but 
wastes space; and adding a spine had surprising side-effects (changed 
the color range!).
I would guess that you want a custom Colorbar class, with a different 
offset for a second set of ticks.
note that in colorbar.py, there's some code specific to CountourSets.
&C
On Nov 15, 2010, at 15 Nov, 8:22 AM, Daniel Welling wrote:
> Greetings.
>
> I am making some contour plots and in my field for this particular 
> value, there are two widely used units. As such, it is very useful 
> to have both units listed on the colorbar. To clarify: the 
> colorbar's normal ticks would be facing to the right and labeled 
> with Unit Type 1, which was the units that the data were in when 
> they were plotted. Unit Type 2 is simply a factor of X different 
> than unit type two. It would be nice if I could add a second set of 
> ticks to the color bar using a different locator and have them face 
> left. Is this possible? Is there another way to display two values 
> for each tick such that the colorbar shows both units?
>
> Thanks.
> -dw
> ------------------------------------------------------------------------------
> Centralized Desktop Delivery: Dell and VMware Reference Architecture
> Simplifying enterprise desktop deployment and management using
> Dell EqualLogic storage and VMware View: A highly scalable, end-to-end
> client virtualization framework. Read more!
> http://p.sf.net/sfu/dell-eql-dev2dev_______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Chloe Lewis
Ecosystem Sciences, Policy and Management, UC Berkeley
137 Mulford Hall
Berkeley, CA 94720-3114
http://nature.berkeley.edu/~chlewis
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From: Michael D. <md...@st...> - 2010年11月15日 18:45:32
Since their package is crashing, I would report this bug against OpenSUSE's python-matplotlib package.
If that doesn't get you any response, it would be helpful to get a better idea of where it is failing. Can you provide a gdb backtrace?
Mike
From: Kurt M. <kur...@su...> - 2010年11月15日 18:28:48
Hi,
Since upgrading to SUSE 11.3 matplotlib simply craches
(segfault on dlopen("/usr/lib/python2.6/site-packages/matplotlib/_path.so", 2);
> python -V
Python 2.6.5
> uname -a
Linux mcp20 2.6.34.7-0.5-default #1 SMP 2010年10月25日 08:40:12 +0200 i686 i686 i386 GNU/Linux
I did a 1-Click Installation from http://software.opensuse.org.
http://software.opensuse.org/search/download?base=openSUSE%3A11.3&file=devel%3A%2Flanguages%3A%2Fpython%2FopenSUSE_11.3%2Fi586%2Fpython-matplotlib-1.0.0-2.9.i586.rpm&query=python-matplotlib
So I have python-matplotlib-1.0.0-2.9.i586.rpm
When I do:
python -v -c "import matplotlib.figure"
...
import matplotlib.docstring # precompiled from /usr/lib/python2.6/site-packages/matplotlib/docstring.pyc
# /usr/lib/python2.6/site-packages/matplotlib/transforms.pyc matches /usr/lib/python2.6/site-packages/matplotlib/transforms.py
import matplotlib.transforms # precompiled from /usr/lib/python2.6/site-packages/matplotlib/transforms.pyc
dlopen("/usr/lib/python2.6/site-packages/matplotlib/_path.so", 2);
Speicherzugriffsfehler
(means "Segfault")
The same is when I do:
python -v -c "from pylab import *"
mport matplotlib.docstring # precompiled from /usr/lib/python2.6/site-packages/matplotlib/docstring.pyc
# /usr/lib/python2.6/site-packages/matplotlib/transforms.pyc matches /usr/lib/python2.6/site-packages/matplotlib/transforms.py
import matplotlib.transforms # precompiled from /usr/lib/python2.6/site-packages/matplotlib/transforms.pyc
dlopen("/usr/lib/python2.6/site-packages/matplotlib/_path.so", 2);
Speicherzugriffsfehler
I googled around.
Some Chaco users seems to have similar problems.
But for now I have no idea what to do next.
Please, somebody be so kind and give me some hint.
Have a nice day.
-- 
Kurt Müller, mu...@pr...
From: Daniel W. <dan...@gm...> - 2010年11月15日 16:23:07
Greetings.
I am making some contour plots and in my field for this particular value,
there are two widely used units. As such, it is very useful to have both
units listed on the colorbar. To clarify: the colorbar's normal ticks would
be facing to the right and labeled with Unit Type 1, which was the units
that the data were in when they were plotted. Unit Type 2 is simply a
factor of X different than unit type two. It would be nice if I could add a
second set of ticks to the color bar using a different locator and have them
face left. Is this possible? Is there another way to display two values for
each tick such that the colorbar shows both units?
Thanks.
-dw
From: Guy G. <guy...@re...> - 2010年11月15日 10:14:50
On Friday 12 Nov 2010 15:20:43 Ryan May wrote:
> On Fri, Nov 12, 2010 at 8:40 AM, Benjamin Root <ben...@ou...> wrote:
> > On Fri, Nov 12, 2010 at 5:11 AM, Guy Griffiths
> > <guy...@re...>
> > 
> > wrote:
> >> Hi,
> >> 
> >> I've been using matplotlib for a while for plotting scientific data, and
> >> recently upgraded from version 0.99.1.1 to 1.0.0. Primarily I use
> >> pcolor to
> >> produce plots of concentration in 2D space. I use reasonably fine
> >> meshes, and
> >> in v0.99.1.1 the output looked great.
> >> 
> >> In v1.0.0, all of my plots (using the same code) have faint gridlines
> >> visible.
> >> Since the mesh I am using is quite fine, this makes the plots look
> >> terrible
> >> (i.e. more gridlines than actual data). This seems to be controlled by
> >> the
> >> "edgecolors" keyword, but even when set to 'none' they are still there.
> >> Is
> >> there any way to remove them completely without reverting back to
> >> 0.99.1.1 (which I'd prefer not to do, since some of the API changes are
> >> really useful
> >> for creating very polished graphs suitable for publication)?
> >> 
> >> imshow seems to have closer results to what I want (i.e. no gridlines),
> >> but
> >> with imshow, the axes denote the pixel position, and there is no option
> >> to display on polar axes (which is essential).
> >> 
> >> Any help would be much appreciated.
> >> 
> >> Regards,
> >> 
> >> Guy Griffiths
> > 
> > Guy, I have noticed something similar a few months ago with pcolor, but I
> > am not certain if it is the same problem as yours. First, which backend
> > are you using? Second, are you seeing the grid lines in both the figure
> > window and the saved output? Also, what format are you saving your
> > output to? Lastly, which pcolor function are you using (pcolor(),
> > pcolormesh(), pcolorfast())?
> > 
> > If you could include a screenshot or the saved file, I could see if it is
> > similar to my problem.
> 
> Yeah, I had noticed a problem with pcolor too. You can see the problem
> I've been seeing here:
> 
> http://matplotlib.sourceforge.net/examples/pylab_examples/pcolor_demo.html
> 
> Calling pcolor with antialiased=False removes the lines, but that's
> just a workaround, not a solution. I'm not really sure where to start
> to track this down, so if anyone has a suggestion, I'm all ears.
> 
> Ryan
Hi,
Thanks for the help. The problem I'm seeing is as Ryan describes (same effect 
as in the screenshot, but let me know if you still want me to provide an 
example), and appears in both the figure window and saved output (at least png 
and pdf). The backend I am using is Qt/Agg. I was using pcolor(), but it 
appears that pcolormesh() doesn't (always) have this problem. Setting 
antialiased=False removes some of the problems. In summary:
pcolor(), antialiased=True - lines on screen, png, pdf
pcolor(), antialiased=False - lines on pdf, fine on png/screen
pcolormesh() - lines on pdf, fine on png/screen
Regards,
Guy

Showing 7 results of 7

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