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> Note that with OPenGL in general, its the transforming that buys you > performance -- when you push brand new data to be rendered, it takes a lot > of time to push that data to the video card, so drawing the first time > doesn't buy you much. But if you need to re-render that same data in a > different view, say zooming in or out, etc, then GL can fly -- if that > transformation can be done on the GPU. > > As far as I understand it, that's what vispy is doing. Exactly. Note that pushing data on the GPU is not that slow: in one second, you can send hundreds of millions of points on a modern GPU. However it would be a bit slow to send large amounts of data at every frame. GPU-based transformations are extremely fast, and you have full control on how they're implemented; in the end, it's just arbitrary C code that runs on the GPU on a per-vertex or per-pixel basis.
On Fri, Mar 13, 2015 at 12:53 PM, Chris Barker <chr...@no...> wrote: > On Fri, Mar 13, 2015 at 10:21 AM, Benjamin Root <ben...@ou...> wrote: > >> Probably what I am most interested in from OpenGL is its transforms >> stack. >> > > OpenGL can't do anything with transforms that you couldn't do in python > (or C, or Cython). What it can do is push the transform computations to the > GPU(s) -- making for monstrously faster performance. > > This is the "problem" with the current MPL architecture. It does all the > transforming outside of the back-ends, and assumes that the backends can > only render in 2-d pixel coordinates. > > If we can re-factor to push the transforms to the back-end, most of them > could use the same generic code, but you'd have the option of the back-end > providing the transforms, which would buy you a LOT with Open GL, and could > maybe by you some with, say, wxAgg, as you could put the transforms in > C/C++ perhaps more efficiently. > > Note that with OPenGL in general, its the transforming that buys you > performance -- when you push brand new data to be rendered, it takes a lot > of time to push that data to the video card, so drawing the first time > doesn't buy you much. But if you need to re-render that same data in a > different view, say zooming in or out, etc, then GL can fly -- if that > transformation can be done on the GPU. > > Don't overestimate the cost of the data transfer, at least for non-millions of points. Even years ago, just doing basic opengl plotting (no sophisticated use of on-GPU memory), was a big win. The other win for mpl + opengl is giving a real rasterizer and depth buffer for the mpl3d package, which is hampered by the per-artist z-ordering. Ryan -- Ryan May
On Fri, Mar 13, 2015 at 10:21 AM, Benjamin Root <ben...@ou...> wrote: > Probably what I am most interested in from OpenGL is its transforms stack. > OpenGL can't do anything with transforms that you couldn't do in python (or C, or Cython). What it can do is push the transform computations to the GPU(s) -- making for monstrously faster performance. This is the "problem" with the current MPL architecture. It does all the transforming outside of the back-ends, and assumes that the backends can only render in 2-d pixel coordinates. If we can re-factor to push the transforms to the back-end, most of them could use the same generic code, but you'd have the option of the back-end providing the transforms, which would buy you a LOT with Open GL, and could maybe by you some with, say, wxAgg, as you could put the transforms in C/C++ perhaps more efficiently. Note that with OPenGL in general, its the transforming that buys you performance -- when you push brand new data to be rendered, it takes a lot of time to push that data to the video card, so drawing the first time doesn't buy you much. But if you need to re-render that same data in a different view, say zooming in or out, etc, then GL can fly -- if that transformation can be done on the GPU. As far as I understand it, that's what vispy is doing. -CHB > While matplotlib's transforms stack is fantastic, it is inherently limited > to 2D operations. Upgrading the transforms stack in some way would be huge > thing to me. > > On Fri, Mar 13, 2015 at 1:08 PM, Nicolas P. Rougier < > Nic...@in...> wrote: > >> >> It might be difficult to stick to matplotlib architecture and still >> benefit from OpenGL speed. >> There are a lot of GL techniques that speed up things a lot but are are >> not really compatible. >> >> For example, isolines, quiver plots, image interpolations and most >> transformations can be handled directly by the GPU >> (see http://glumpy.github.io/gallery.html) >> >> But we'll try to use matplotlib public api such that things will be >> mostly transparent for the user >> >> Nicolas >> >> > On 13 Mar 2015, at 17:33, Benjamin Root <ben...@ou...> wrote: >> > >> > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d >> stuff to it! Does vispy have any plans to eventually bring that into >> mainline matplotlib, or does it break too much with the standard set of >> backends to make sense in matplotlib (or maybe it is too much of a >> maintenance/packaging burden?) >> > >> > Ben Root >> > >> > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant < >> cyr...@gm...> wrote: >> > Kivy is all built on OpenGL, so it would probably be pretty >> straightforward to generate teh image with AGG, then dump it to the screen >> as an OpenGL texture. But it would be a bit sad to not take advantage of >> OpenGL at all in that process. (and getting AGG to work with Kivy may be >> less than trivial...) >> > >> > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy >> has some stuff to help? >> > >> > Also, the MPL back-end structure wasn't designed to push much of the >> transforming, etc to the back -end, which is too bad, as that's what OpenGL >> does well. >> > >> > But I'd still take a look at the work done to make a real OpenGL >> back-end -- not sure how far that got, but worth a look. >> > >> > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe >> not! form teh vispy docs: >> > >> > "Vispy now ships a very basic and experimental OpenGL backend for >> matplotlib." >> > >> > >> > Yes, and we plan to work on this backend in the next few months. We >> might have a couple of GSoC students working partly on the OpenGL MPL >> backend and possibly on Kivy integration. >> > >> > >> > >> ------------------------------------------------------------------------------ >> > Dive into the World of Parallel Programming The Go Parallel Website, >> sponsored >> > by Intel and developed in partnership with Slashdot Media, is your hub >> for all >> > things parallel software development, from weekly thought leadership >> blogs to >> > news, videos, case studies, tutorials and more. Take a look and join the >> > conversation now. http://goparallel.sourceforge.net/ >> > _______________________________________________ >> > Matplotlib-devel mailing list >> > Mat...@li... >> > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> > >> > >> > >> ------------------------------------------------------------------------------ >> > Dive into the World of Parallel Programming The Go Parallel Website, >> sponsored >> > by Intel and developed in partnership with Slashdot Media, is your hub >> for all >> > things parallel software development, from weekly thought leadership >> blogs to >> > news, videos, case studies, tutorials and more. Take a look and join the >> > conversation now. >> http://goparallel.sourceforge.net/_______________________________________________ >> > Matplotlib-devel mailing list >> > Mat...@li... >> > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> >> > -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception Chr...@no...
I'd be very interested in hearing a "state of matplotlib" talk. On Fri, Mar 13, 2015, 11:29 Phil Elson <pel...@gm...> wrote: > Orchestrating MPL tutorials and talks in this thread would be a good idea. > I'd be happy to help anybody planning on submitting anything relating > specifically to matplotlib, and wonder if we should do a "state of > matplotlib" type talk similar to the one Mike did 2 years ago. > > On 13 March 2015 at 02:05, Benjamin Root <ben...@ou...> wrote: > >> Yes, I plan to submit my time-honored, and requested "Anatomy of >> Matplotlib" tutorial. Now, I am not entirely sure I will be able to attend >> the conference this year, so perhaps someone else might be willing to step >> in and give it this year? >> >> Note that my tutorial is geared for beginners. So there is still plenty >> of opportunity for someone else to submit a tutorial for more advanced >> users! >> >> Cheers! >> Ben Root >> >> On Thu, Mar 12, 2015 at 6:46 PM, Nelle Varoquaux < >> nel...@gm...> wrote: >> >>> Hi everyone, >>> >>> Is someone submitting a tutorial on matplotlib? The call for tutorial is >>> open, and I think it would be nice to have one on matplotlib. >>> >>> Cheers, >>> N >>> >>> ---------- Forwarded message ---------- >>> From: SciPy 2015 Organizers <sci...@sc...> >>> Date: 11 March 2015 at 01:02 >>> Subject: SciPy 2015 CFP Email 2 >>> To: nel...@gm... >>> >>> >>> [image: SciPy 2015 Logo] >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/index.php%7CQ%7Ceventid%7CE%7C115969%7CA%7C> >>> >>> Tick-Tock, Tick-Tock: >>> T-Minus 6 Days for Tutorial Submissions >>> *Due Date: March 16, 2015* >>> >>> The SciPy experience kicks off with two days of tutorials >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/115969/259288/%7CQ%7C> >>> (July 6-7). These sessions provide extremely affordable access to expert >>> training, and consistently receive fantastic feedback from participants. >>> We're looking for submissions on topics from introductory to advanced - >>> we'll have attendees across the gamut looking to learn. Plus, you can earn >>> an instructor stipend to apply towards your conference participation. Visit >>> the SciPy 2015 website for details >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org> >>> or submit a proposal here >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> >>> . >>> >>> Submit a Tutorial Proposal Here >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> Talk >>> and Poster Proposals Due April 1st >>> >>> There's always something new and exciting going on in the world of >>> Science + Python, this is your chance to get up and talk about it! >>> >>> *Visit the SciPy 2015 website >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/index.php%7CQ%7Ceventid%7CE%7C115969%7CA%7C> >>> for full details or click here to submit a proposal >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969>.* >>> Choose a topic in one of the 3 main conference tracks: >>> >>> - Scientific Computing in Python (General track) >>> - Python in Data Science >>> - Quantitative and Computational Social Sciences >>> >>> * And/or submit for one of the 7 domain-specific mini-symposia >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969>:* >>> >>> - Astronomy and astrophysics >>> - Computational life and medical sciences >>> - Engineering >>> - Geographic information systems (GIS) >>> - Geophysics >>> - Oceanography and meteorology >>> - Visualization, vision and imaging >>> >>> Submit a Talk or Poster Proposal Here >>> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> Need >>> some inspiration? 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Take a look and join the >>> conversation now. http://goparallel.sourceforge.net/ >>> _______________________________________________ >>> Matplotlib-devel mailing list >>> Mat...@li... >>> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >>> >>> >> >> >> ------------------------------------------------------------------------------ >> Dive into the World of Parallel Programming The Go Parallel Website, >> sponsored >> by Intel and developed in partnership with Slashdot Media, is your hub >> for all >> things parallel software development, from weekly thought leadership >> blogs to >> news, videos, case studies, tutorials and more. Take a look and join the >> conversation now. http://goparallel.sourceforge.net/ >> _______________________________________________ >> Matplotlib-devel mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> >> > ------------------------------------------------------------ > ------------------ > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for > all > things parallel software development, from weekly thought leadership blogs > to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >
Orchestrating MPL tutorials and talks in this thread would be a good idea. I'd be happy to help anybody planning on submitting anything relating specifically to matplotlib, and wonder if we should do a "state of matplotlib" type talk similar to the one Mike did 2 years ago. On 13 March 2015 at 02:05, Benjamin Root <ben...@ou...> wrote: > Yes, I plan to submit my time-honored, and requested "Anatomy of > Matplotlib" tutorial. Now, I am not entirely sure I will be able to attend > the conference this year, so perhaps someone else might be willing to step > in and give it this year? > > Note that my tutorial is geared for beginners. So there is still plenty of > opportunity for someone else to submit a tutorial for more advanced users! > > Cheers! > Ben Root > > On Thu, Mar 12, 2015 at 6:46 PM, Nelle Varoquaux < > nel...@gm...> wrote: > >> Hi everyone, >> >> Is someone submitting a tutorial on matplotlib? The call for tutorial is >> open, and I think it would be nice to have one on matplotlib. >> >> Cheers, >> N >> >> ---------- Forwarded message ---------- >> From: SciPy 2015 Organizers <sci...@sc...> >> Date: 11 March 2015 at 01:02 >> Subject: SciPy 2015 CFP Email 2 >> To: nel...@gm... >> >> >> [image: SciPy 2015 Logo] >> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/index.php%7CQ%7Ceventid%7CE%7C115969%7CA%7C> >> >> Tick-Tock, Tick-Tock: >> T-Minus 6 Days for Tutorial Submissions >> *Due Date: March 16, 2015* >> >> The SciPy experience kicks off with two days of tutorials >> <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/115969/259288/%7CQ%7C> >> (July 6-7). These sessions provide extremely affordable access to expert >> training, and consistently receive fantastic feedback from participants. >> We're looking for submissions on topics from introductory to advanced - >> we'll have attendees across the gamut looking to learn. Plus, you can earn >> an instructor stipend to apply towards your conference participation. 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Take a look and join the >> conversation now. http://goparallel.sourceforge.net/ >> _______________________________________________ >> Matplotlib-devel mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> >> > > > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for > all > things parallel software development, from weekly thought leadership blogs > to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >
I'm pleased to announce that cartopy v0.12.0rc1 has been tagged. This release has focused on improving the geometry projection stability, improving interfaces for data ingestion, rounding off Python 3 support, and generally improving the breadth of the gallery. A full overview of what's new in this release can be found at http://scitools.org.uk/cartopy/docs/v0.12/whats_new.html. About cartopy -------------- Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy. It features: - object-oriented projection definitions - point, line, polygon, vector and image transformations between projections - integration to expose advanced mapping in matplotlib with a simple and intuitive interface - powerful vector data handling by integrating shapefile reading with Shapely capabilities Installing cartopy ----------------- Installation of the release candidate and its dependencies with conda: *conda install cartopy** --channel scitools/channel/dev* Installing cartopy using pip requires GEOS and proj4 to be installed prior to running: *pip install cartopy* Thanks to everybody who contributed towards this release, Best, Phil Elson (github: @pelson | twitter: @pypelson)
2015年03月13日 18:21 GMT+01:00 Benjamin Root <ben...@ou...>: > Quite honestly, I am not all that concerned about speed (at least, I am > not talking about achieving gaming level performance). I am most concerned > about compatibility, quality of the image rendering, quality of the text > rendering, and consistency across platforms. Probably what I am most > interested in from OpenGL is its transforms stack. While matplotlib's > transforms stack is fantastic, it is inherently limited to 2D operations. > Upgrading the transforms stack in some way would be huge thing to me. > Modern shader-based OpenGL no longer has transform stacks: we need to implement GPU transforms ourselves. This is all handled by VisPy, and we have total control on that architecture. We do want to support 2D and 3D simultaneously. We are still in the process of designing this architecture though, and I guess it would certainly make sense for matplotlib devs to be involved in the discussions...
By speed I meant to be able to render "big" plot (like a million point scatter plot or having 10 000 isolines, etc.) Concerning output quality, I think we're almost done. We have antialiases lines, markers and polygons (equivalent to agg), 2D agg-quality text (same techniques) and 3D decent text quality (see http://glumpy.github.io/_static/screenshots/lorenz.png). It is now a matter of integrating all this together and of course to debug it... Nicolas > On 13 Mar 2015, at 18:21, Benjamin Root <ben...@ou...> wrote: > > Quite honestly, I am not all that concerned about speed (at least, I am not talking about achieving gaming level performance). I am most concerned about compatibility, quality of the image rendering, quality of the text rendering, and consistency across platforms. Probably what I am most interested in from OpenGL is its transforms stack. While matplotlib's transforms stack is fantastic, it is inherently limited to 2D operations. Upgrading the transforms stack in some way would be huge thing to me. > > On Fri, Mar 13, 2015 at 1:08 PM, Nicolas P. Rougier <Nic...@in...> wrote: > > It might be difficult to stick to matplotlib architecture and still benefit from OpenGL speed. > There are a lot of GL techniques that speed up things a lot but are are not really compatible. > > For example, isolines, quiver plots, image interpolations and most transformations can be handled directly by the GPU > (see http://glumpy.github.io/gallery.html) > > But we'll try to use matplotlib public api such that things will be mostly transparent for the user > > Nicolas > > > On 13 Mar 2015, at 17:33, Benjamin Root <ben...@ou...> wrote: > > > > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d stuff to it! Does vispy have any plans to eventually bring that into mainline matplotlib, or does it break too much with the standard set of backends to make sense in matplotlib (or maybe it is too much of a maintenance/packaging burden?) > > > > Ben Root > > > > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant <cyr...@gm...> wrote: > > Kivy is all built on OpenGL, so it would probably be pretty straightforward to generate teh image with AGG, then dump it to the screen as an OpenGL texture. But it would be a bit sad to not take advantage of OpenGL at all in that process. (and getting AGG to work with Kivy may be less than trivial...) > > > > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy has some stuff to help? > > > > Also, the MPL back-end structure wasn't designed to push much of the transforming, etc to the back -end, which is too bad, as that's what OpenGL does well. > > > > But I'd still take a look at the work done to make a real OpenGL back-end -- not sure how far that got, but worth a look. > > > > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! form teh vispy docs: > > > > "Vispy now ships a very basic and experimental OpenGL backend for matplotlib." > > > > > > Yes, and we plan to work on this backend in the next few months. We might have a couple of GSoC students working partly on the OpenGL MPL backend and possibly on Kivy integration. > > > > > > ------------------------------------------------------------------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub for all > > things parallel software development, from weekly thought leadership blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. http://goparallel.sourceforge.net/ > > _______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > > > > ------------------------------------------------------------------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub for all > > things parallel software development, from weekly thought leadership blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. http://goparallel.sourceforge.net/_______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >
Quite honestly, I am not all that concerned about speed (at least, I am not talking about achieving gaming level performance). I am most concerned about compatibility, quality of the image rendering, quality of the text rendering, and consistency across platforms. Probably what I am most interested in from OpenGL is its transforms stack. While matplotlib's transforms stack is fantastic, it is inherently limited to 2D operations. Upgrading the transforms stack in some way would be huge thing to me. On Fri, Mar 13, 2015 at 1:08 PM, Nicolas P. Rougier < Nic...@in...> wrote: > > It might be difficult to stick to matplotlib architecture and still > benefit from OpenGL speed. > There are a lot of GL techniques that speed up things a lot but are are > not really compatible. > > For example, isolines, quiver plots, image interpolations and most > transformations can be handled directly by the GPU > (see http://glumpy.github.io/gallery.html) > > But we'll try to use matplotlib public api such that things will be mostly > transparent for the user > > Nicolas > > > On 13 Mar 2015, at 17:33, Benjamin Root <ben...@ou...> wrote: > > > > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d > stuff to it! Does vispy have any plans to eventually bring that into > mainline matplotlib, or does it break too much with the standard set of > backends to make sense in matplotlib (or maybe it is too much of a > maintenance/packaging burden?) > > > > Ben Root > > > > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant < > cyr...@gm...> wrote: > > Kivy is all built on OpenGL, so it would probably be pretty > straightforward to generate teh image with AGG, then dump it to the screen > as an OpenGL texture. But it would be a bit sad to not take advantage of > OpenGL at all in that process. (and getting AGG to work with Kivy may be > less than trivial...) > > > > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy > has some stuff to help? > > > > Also, the MPL back-end structure wasn't designed to push much of the > transforming, etc to the back -end, which is too bad, as that's what OpenGL > does well. > > > > But I'd still take a look at the work done to make a real OpenGL > back-end -- not sure how far that got, but worth a look. > > > > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! > form teh vispy docs: > > > > "Vispy now ships a very basic and experimental OpenGL backend for > matplotlib." > > > > > > Yes, and we plan to work on this backend in the next few months. We > might have a couple of GSoC students working partly on the OpenGL MPL > backend and possibly on Kivy integration. > > > > > > > ------------------------------------------------------------------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub > for all > > things parallel software development, from weekly thought leadership > blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. http://goparallel.sourceforge.net/ > > _______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > > > > > ------------------------------------------------------------------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub > for all > > things parallel software development, from weekly thought leadership > blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. > http://goparallel.sourceforge.net/_______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >
MEP 25 is working towards providing a way to serialize the contents of a figure in a more controlled way. The main target of this is saving/reopening figures and export to bokeh/plotly/d3, but I think this would also work well for exporting everything off to an opengl backend. Tom On Fri, Mar 13, 2015 at 1:09 PM Nicolas P. Rougier <Nic...@in...> wrote: > > It might be difficult to stick to matplotlib architecture and still > benefit from OpenGL speed. > There are a lot of GL techniques that speed up things a lot but are are > not really compatible. > > For example, isolines, quiver plots, image interpolations and most > transformations can be handled directly by the GPU > (see http://glumpy.github.io/gallery.html) > > But we'll try to use matplotlib public api such that things will be mostly > transparent for the user > > Nicolas > > > On 13 Mar 2015, at 17:33, Benjamin Root <ben...@ou...> wrote: > > > > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d > stuff to it! Does vispy have any plans to eventually bring that into > mainline matplotlib, or does it break too much with the standard set of > backends to make sense in matplotlib (or maybe it is too much of a > maintenance/packaging burden?) > > > > Ben Root > > > > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant < > cyr...@gm...> wrote: > > Kivy is all built on OpenGL, so it would probably be pretty > straightforward to generate teh image with AGG, then dump it to the screen > as an OpenGL texture. But it would be a bit sad to not take advantage of > OpenGL at all in that process. (and getting AGG to work with Kivy may be > less than trivial...) > > > > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy > has some stuff to help? > > > > Also, the MPL back-end structure wasn't designed to push much of the > transforming, etc to the back -end, which is too bad, as that's what OpenGL > does well. > > > > But I'd still take a look at the work done to make a real OpenGL > back-end -- not sure how far that got, but worth a look. > > > > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! > form teh vispy docs: > > > > "Vispy now ships a very basic and experimental OpenGL backend for > matplotlib." > > > > > > Yes, and we plan to work on this backend in the next few months. We > might have a couple of GSoC students working partly on the OpenGL MPL > backend and possibly on Kivy integration. > > > > > > ------------------------------------------------------------ > ------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub > for all > > things parallel software development, from weekly thought leadership > blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. http://goparallel.sourceforge.net/ > > _______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > > > > ------------------------------------------------------------ > ------------------ > > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > > by Intel and developed in partnership with Slashdot Media, is your hub > for all > > things parallel software development, from weekly thought leadership > blogs to > > news, videos, case studies, tutorials and more. Take a look and join the > > conversation now. http://goparallel.sourceforge. > net/_______________________________________________ > > Matplotlib-devel mailing list > > Mat...@li... > > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > ------------------------------------------------------------ > ------------------ > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for > all > things parallel software development, from weekly thought leadership blogs > to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >
It might be difficult to stick to matplotlib architecture and still benefit from OpenGL speed. There are a lot of GL techniques that speed up things a lot but are are not really compatible. For example, isolines, quiver plots, image interpolations and most transformations can be handled directly by the GPU (see http://glumpy.github.io/gallery.html) But we'll try to use matplotlib public api such that things will be mostly transparent for the user Nicolas > On 13 Mar 2015, at 17:33, Benjamin Root <ben...@ou...> wrote: > > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d stuff to it! Does vispy have any plans to eventually bring that into mainline matplotlib, or does it break too much with the standard set of backends to make sense in matplotlib (or maybe it is too much of a maintenance/packaging burden?) > > Ben Root > > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant <cyr...@gm...> wrote: > Kivy is all built on OpenGL, so it would probably be pretty straightforward to generate teh image with AGG, then dump it to the screen as an OpenGL texture. But it would be a bit sad to not take advantage of OpenGL at all in that process. (and getting AGG to work with Kivy may be less than trivial...) > > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy has some stuff to help? > > Also, the MPL back-end structure wasn't designed to push much of the transforming, etc to the back -end, which is too bad, as that's what OpenGL does well. > > But I'd still take a look at the work done to make a real OpenGL back-end -- not sure how far that got, but worth a look. > > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! form teh vispy docs: > > "Vispy now ships a very basic and experimental OpenGL backend for matplotlib." > > > Yes, and we plan to work on this backend in the next few months. We might have a couple of GSoC students working partly on the OpenGL MPL backend and possibly on Kivy integration. > > > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for all > things parallel software development, from weekly thought leadership blogs to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > > > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for all > things parallel software development, from weekly thought leadership blogs to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/_______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
I don't think it would work like the other backends. Last time I checked, the MPL backend system would not let us achieve high performance. Currently we use Jake Vanderplas' mplexporter system that was developed for mpld3. Eventually, I guess we could expose the same interface as mpld3, i.e. replace `plt.show()` by something like `vispy.show()`. This would display a matplotlib figure with VisPy (which supports Qt, wx, and other GUI toolkits) instead of one of matplotlib's backends. In the notebook, something like `vispy.enable_notebook()` could replace matplotlib's inline PNG by a dynamic WebGL canvas. 2015年03月13日 17:33 GMT+01:00 Benjamin Root <ben...@ou...>: > +1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d > stuff to it! Does vispy have any plans to eventually bring that into > mainline matplotlib, or does it break too much with the standard set of > backends to make sense in matplotlib (or maybe it is too much of a > maintenance/packaging burden?) > > Ben Root > > On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant < > cyr...@gm...> wrote: > >> Kivy is all built on OpenGL, so it would probably be pretty >>> straightforward to generate teh image with AGG, then dump it to the screen >>> as an OpenGL texture. But it would be a bit sad to not take advantage of >>> OpenGL at all in that process. (and getting AGG to work with Kivy may be >>> less than trivial...) >>> >>> Note that vector graphics in OpenGL is a serious pain, but maybe Kivy >>> has some stuff to help? >>> >>> Also, the MPL back-end structure wasn't designed to push much of the >>> transforming, etc to the back -end, which is too bad, as that's what OpenGL >>> does well. >>> >>> But I'd still take a look at the work done to make a real OpenGL >>> back-end -- not sure how far that got, but worth a look. >>> >>> Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! >>> form teh vispy docs: >>> >>> "Vispy now ships a very basic and experimental OpenGL backend for >>> matplotlib." >>> >>> >> Yes, and we plan to work on this backend in the next few months. We might >> have a couple of GSoC students working partly on the OpenGL MPL backend and >> possibly on Kivy integration. >> >> >> >> ------------------------------------------------------------------------------ >> Dive into the World of Parallel Programming The Go Parallel Website, >> sponsored >> by Intel and developed in partnership with Slashdot Media, is your hub >> for all >> things parallel software development, from weekly thought leadership >> blogs to >> news, videos, case studies, tutorials and more. Take a look and join the >> conversation now. http://goparallel.sourceforge.net/ >> _______________________________________________ >> Matplotlib-devel mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel >> >> >
+1 on an OpenGL backend! Especially if I can off-load a lot of mplot3d stuff to it! Does vispy have any plans to eventually bring that into mainline matplotlib, or does it break too much with the standard set of backends to make sense in matplotlib (or maybe it is too much of a maintenance/packaging burden?) Ben Root On Fri, Mar 13, 2015 at 12:12 PM, Cyrille Rossant <cyr...@gm... > wrote: > Kivy is all built on OpenGL, so it would probably be pretty >> straightforward to generate teh image with AGG, then dump it to the screen >> as an OpenGL texture. But it would be a bit sad to not take advantage of >> OpenGL at all in that process. (and getting AGG to work with Kivy may be >> less than trivial...) >> >> Note that vector graphics in OpenGL is a serious pain, but maybe Kivy has >> some stuff to help? >> >> Also, the MPL back-end structure wasn't designed to push much of the >> transforming, etc to the back -end, which is too bad, as that's what OpenGL >> does well. >> >> But I'd still take a look at the work done to make a real OpenGL back-end >> -- not sure how far that got, but worth a look. >> >> Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! >> form teh vispy docs: >> >> "Vispy now ships a very basic and experimental OpenGL backend for >> matplotlib." >> >> > Yes, and we plan to work on this backend in the next few months. We might > have a couple of GSoC students working partly on the OpenGL MPL backend and > possibly on Kivy integration. > > > > ------------------------------------------------------------------------------ > Dive into the World of Parallel Programming The Go Parallel Website, > sponsored > by Intel and developed in partnership with Slashdot Media, is your hub for > all > things parallel software development, from weekly thought leadership blogs > to > news, videos, case studies, tutorials and more. Take a look and join the > conversation now. http://goparallel.sourceforge.net/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > >
> > Kivy is all built on OpenGL, so it would probably be pretty > straightforward to generate teh image with AGG, then dump it to the screen > as an OpenGL texture. But it would be a bit sad to not take advantage of > OpenGL at all in that process. (and getting AGG to work with Kivy may be > less than trivial...) > > Note that vector graphics in OpenGL is a serious pain, but maybe Kivy has > some stuff to help? > > Also, the MPL back-end structure wasn't designed to push much of the > transforming, etc to the back -end, which is too bad, as that's what OpenGL > does well. > > But I'd still take a look at the work done to make a real OpenGL back-end > -- not sure how far that got, but worth a look. > > Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not! > form teh vispy docs: > > "Vispy now ships a very basic and experimental OpenGL backend for > matplotlib." > > Yes, and we plan to work on this backend in the next few months. We might have a couple of GSoC students working partly on the OpenGL MPL backend and possibly on Kivy integration.
.){kind=link}
On Sat, Mar 7, 2015 at 4:17 PM, Thomas Caswell <tca...@gm...> wrote:
> Thank your for your interest, mpl on touch devices sounds super cool!
>
Indeed!
> The easiest course is probably to develop a backend modeled after the
> {qt,wx,gtk}Agg backends which embed an Agg backend into the gui framework
> of choice. In those cases we rely on Agg to handle the mpl specific
> drawing tasks and then embed the resulting bitmap into the GUI.
>
Kivy is all built on OpenGL, so it would probably be pretty straightforward
to generate teh image with AGG, then dump it to the screen as an OpenGL
texture. But it would be a bit sad to not take advantage of OpenGL at all
in that process. (and getting AGG to work with Kivy may be less than
trivial...)
Note that vector graphics in OpenGL is a serious pain, but maybe Kivy has
some stuff to help?
Also, the MPL back-end structure wasn't designed to push much of the
transforming, etc to the back -end, which is too bad, as that's what OpenGL
does well.
But I'd still take a look at the work done to make a real OpenGL back-end
-- not sure how far that got, but worth a look.
Or look at http://vispy.org/ -- and give up in MPL :-( -- or maybe not!
form teh vispy docs:
"Vispy now ships a very basic and experimental OpenGL backend for
matplotlib."
HTH,
-Chris
> A majority of the work in the gui backends deals window/widget creation
> and the plumbing required to convert interaction events from the GUI into
> the internal events mpl uses.
>
> Tom
>
> On Sat, Mar 7, 2015 at 4:15 PM Achyut Rastogi <ras...@gm...>
> wrote:
>
>> Hello , I am a novice gsoc aspirant and I want to write a backend for
>> kivy, I read some of the other conversations on the mailing list and I know
>> about the template you guys provide but I am having trouble getting
>> started, can you please help me get up-to speed. I would be great help if
>> you could tell me what all I need to know of matplotlib to write a good
>> backend.
>> Thank You
>> Achyut Rastogi
>> ------------------------------------------------------------
>> ------------------
>> Dive into the World of Parallel Programming The Go Parallel Website,
>> sponsored
>> by Intel and developed in partnership with Slashdot Media, is your hub
>> for all
>> things parallel software development, from weekly thought leadership
>> blogs to
>> news, videos, case studies, tutorials and more. Take a look and join the
>> conversation now. http://goparallel.sourceforge.net/
>> _______________________________________________
>> Matplotlib-devel mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>>
>
>
> ------------------------------------------------------------------------------
> Dive into the World of Parallel Programming The Go Parallel Website,
> sponsored
> by Intel and developed in partnership with Slashdot Media, is your hub for
> all
> things parallel software development, from weekly thought leadership blogs
> to
> news, videos, case studies, tutorials and more. Take a look and join the
> conversation now. http://goparallel.sourceforge.net/
> _______________________________________________
> Matplotlib-devel mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
>
>
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Yes, I plan to submit my time-honored, and requested "Anatomy of Matplotlib" tutorial. Now, I am not entirely sure I will be able to attend the conference this year, so perhaps someone else might be willing to step in and give it this year? Note that my tutorial is geared for beginners. So there is still plenty of opportunity for someone else to submit a tutorial for more advanced users! Cheers! Ben Root On Thu, Mar 12, 2015 at 6:46 PM, Nelle Varoquaux <nel...@gm...> wrote: > Hi everyone, > > Is someone submitting a tutorial on matplotlib? The call for tutorial is > open, and I think it would be nice to have one on matplotlib. > > Cheers, > N > > ---------- Forwarded message ---------- > From: SciPy 2015 Organizers <sci...@sc...> > Date: 11 March 2015 at 01:02 > Subject: SciPy 2015 CFP Email 2 > To: nel...@gm... > > > [image: SciPy 2015 Logo] > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/index.php%7CQ%7Ceventid%7CE%7C115969%7CA%7C> > > Tick-Tock, Tick-Tock: > T-Minus 6 Days for Tutorial Submissions > *Due Date: March 16, 2015* > > The SciPy experience kicks off with two days of tutorials > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/115969/259288/%7CQ%7C> > (July 6-7). These sessions provide extremely affordable access to expert > training, and consistently receive fantastic feedback from participants. > We're looking for submissions on topics from introductory to advanced - > we'll have attendees across the gamut looking to learn. Plus, you can earn > an instructor stipend to apply towards your conference participation. Visit > the SciPy 2015 website for details > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org> > or submit a proposal here > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> > . > > Submit a Tutorial Proposal Here > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> Talk > and Poster Proposals Due April 1st > > There's always something new and exciting going on in the world of Science > + Python, this is your chance to get up and talk about it! > > *Visit the SciPy 2015 website > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/index.php%7CQ%7Ceventid%7CE%7C115969%7CA%7C> > for full details or click here to submit a proposal > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969>.* > Choose a topic in one of the 3 main conference tracks: > > - Scientific Computing in Python (General track) > - Python in Data Science > - Quantitative and Computational Social Sciences > > * And/or submit for one of the 7 domain-specific mini-symposia > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969>:* > > - Astronomy and astrophysics > - Computational life and medical sciences > - Engineering > - Geographic information systems (GIS) > - Geophysics > - Oceanography and meteorology > - Visualization, vision and imaging > > Submit a Talk or Poster Proposal Here > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.scipy2015.scipy.org/eselectv2/frontend/index/115969> Need > some inspiration? Follow @SciPy on Twitter > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=https://twitter.com/scipyconf> > for highlights from previous SciPy conferences and all of the latest 2015 > updates. > > - Previous year's conferences with talk information > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://conference.scipy.org/past.html> > - SciPy 2014 Talk & Tutorial Video playlist > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.youtube.com/playlist%7CQ%7Clist%7CE%7CPLYx7XA2nY5GfuhCvStxgbynFNrxr3VFog> > - SciPy 2013 Talk & Tutorial Video playlist > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://www.youtube.com/playlist%7CQ%7Clist%7CE%7CPLYx7XA2nY5GeTWcUQTbXVdllyp-Ie3r-y> > > Financial Scholarship Applications Now Being Accepted > > With the support of our sponsors, the SciPy conference provides financial > assistance to attendees based on both community contribution and financial > need. > > In 2014 we were able to support 19 applicants, including 5 diversity aid > recipients, selected for their outstanding contributions to open source > scientific Python projects. *If you'd like to be considered for financial > scholarship, please apply here > <https://www.eiseverywhere.com/emarketing/go.php?i=182077&e=bmVsbGUudmFyb3F1YXV4QGdtYWlsLmNvbQ==&l=http://scipy2015.scipy.org/ehome/115969/259279/?&> > before April 15, 2015.* > Sponsor Thank Yous! 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