Thanks for posting the link to glumpy.
As Benjamin explained, glumpy servers as a testbed for various technics that could be implemented later in matplotlib. The main problem today is that if you want to benefit from hardware acceleration, you have to use some GL features that are not compatible with he whole matplotlib framework (and we need to ensure some degree of compatibilty). I do not have yet a clean solution and I'm still experimenting.
For your tricontourf problem, I think it might be solved quite easily with the proper GL shader but I would need a complete (and basic) matplotlib script example to check if this is actually the case.
On Jan 27, 2012, at 23:12 , Benjamin Root wrote:
On Fri, Jan 27, 2012 at 10:06 AM, Howard <firstname.lastname@example.org>
On 1/27/12 3:39 AM, Ian Thomas wrote:
On 26 January 2012 19:36, Howard <email@example.com>
I'm rendering some
images with about 3.5 million triangles into a 512x512 png
file using tricontourf. I'm running this in a virtual
machine, and I'm pretty sure that there is no graphics
rendering hardware being used. Is it possible, assuming the
hardware was available, to make tricontourf use the
rendering hardware? Will that happen by default?
You are correct, there is no graphics hardware rendering.
Rendering is controlled by the various matplotlib backends,
and to my knowledge there are no backends currently available
that use hardware rendering.
There has been some work done on an OpenGL backend, but I am
not sure of the status of this. The last time I checked it
was pretty experimental. Perhaps someone involved with it can
comment on its current status.
Thanks very much for the reply. If it helps whoever is doing the
OpenGL backend, I may be able to play with it a bit.
That would be the Glumpy project.http://code.google.com/p/glumpy/
As stated in an email response a while back, glumpy is intended to be a testbed for developing the OpenGL backend for future inclusion into matplotlib.
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