matplotlib-devel Mailing List for matplotlib

John Hunter wrote:
>>>>>>"daishi" == daishi <da...@eg...> writes:
> 
> 
> daishi> I've submitted the following:
> daishi> http://sourceforge.net/tracker/index.php?
> daishi> func=detail&aid=1360855&group_id=80706&atid=560722
> 
> daishi> This patch allows one to use matplotlib with (just) the
> daishi> new scipy.
> 
> Just for clarification, when you say "just" the new scipy, you mean
> that it works with Numeric, numarray *and* the new scipy, not that it
> works with the new scipy and only the new scipy.
> 
> I read over the patch and it looks like you did a very thorough job.
> Thanks!
Minor fix needed to avoid unpleasant surprises for users who have the old 
scipy on their import path:
try:
 import scipy
 if hasattr(scipy,'__core_version__'):
 NUMERIX.append('scipy')
except ImportError:
 pass
You want to make sure that you only do this for users of the _new_ scipy, not 
the old one.
Cheers,
f

>>>>> "daishi" == daishi <da...@eg...> writes:
 daishi> I've submitted the following:
 daishi> http://sourceforge.net/tracker/index.php?
 daishi> func=detail&aid=1360855&group_id=80706&atid=560722
 daishi> This patch allows one to use matplotlib with (just) the
 daishi> new scipy.
Just for clarification, when you say "just" the new scipy, you mean
that it works with Numeric, numarray *and* the new scipy, not that it
works with the new scipy and only the new scipy.
I read over the patch and it looks like you did a very thorough job.
Thanks! In the near term, this means that mpl would compile three
shared object files for each of the three array objects for each
extension module, which of course will increase compile times and
binary distribution sizes. Travis, Perry, Todd and I have been
discussing the benefits of changing matplotlib to work *only* with the
new scipy, which include faster build times, smaller binaries, less
complexity and pushing the community to a single array object. Since
the new array interface works with Numeric 24, recent numarray or the
new scipy, *any* of these array packages would work with a matplotlib
compiled just for scipy. We decided to hold off on doing this until
scipy installations issues were sorted out even on semi-obscure
platforms -- Travis, what's your sense of this?
So my inclination is to include your patch now, during a transition
period, and then move over to a new scipy only build, retaining the
numerix layer so Numeric, numarray and (new) scipy users can continue
to use mpl transparently. In particular we need to make sure that
basemap which uses numarray.ndimage continues to work.
Does this sound like the right approach?
JDH

>>>>> "Charlie" == Charlie Moad <cw...@gm...> writes:
 Charlie> Awesome, thanks! Out of curiousity... did you figure
 Charlie> this out visually or by comparing with something?
Let's just say I've encountered the flipy bug before :-)
JDH

Awesome, thanks! Out of curiousity... did you figure this out
visually or by comparing with something?
- Charlie
On 11/18/05, John Hunter <jdh...@ac...> wrote:
> >>>>> "Charlie" =3D=3D Charlie Moad <cw...@gm...> writes:
>
> Charlie> A challenge to the community! ;) Run the current
> Charlie> cursor.py example with the TkAgg backend. (blitting
> Charlie> should be on) i.e. python cursor.py -dTkAgg
>
> Charlie> Why does the blitting not update the entire axis? Any
> Charlie> help on this is greatly appreciated.
>
> THere was a flipy offset needed in _tkagg.cpp
>
> int srcheight =3D (int)aggRenderer->get_height();
> //...
> desty =3D srcheight-(int)t;
>
> I just commited this to CVS -- take it for a test drive.
>
> Checking in src/_tkagg.cpp;
> /cvsroot/matplotlib/matplotlib/src/_tkagg.cpp,v <-- _tkagg.cpp
> new revision: 1.10; previous revision: 1.9
>
> JDH
>

I've submitted the following:
	http://sourceforge.net/tracker/index.php? 
func=detail&aid=1360855&group_id=80706&atid=560722
This patch allows one to use matplotlib with (just)
the new scipy.
The matplotlib built with this patch and just
the new scipy passes the examples/backend_driver.py
test with errors only occuring on those tests which
explicitly includes numarray, and a few others which
i believe are unrelated to the patch.
There are some issues with parallel installation.
I have only tested this with a python installation that
has only the new scipy. In principle, this should be
compatible with a parallel installation of scipy and
numarray, but scipy and Numeric will not work, because
I select to build extensions only for one or the other.
d