Personally, I think traits must be kept out of MPL, for three main reasons:
1. As Eric Bruning points out, while traits is a very powerful tool, it also closes a lot of doors by forcing everything to be written in a trait-like fashion for it to play nice with everything else. While this is great for many applications, I think it does not necessarily belong everywhere, particularly given a tendancy to quickly snowball in complexity (not to mention any new people that want to contribute code have an extra thick manual to read). 2. Installation of traits or traitsgui should not be a necessity for MPL... perhaps this will change in the future, but it's currently a far bigger task to get traits and traits UI working on an arbitrary system than it is to get MPL up and running (at least, that's been my experience in a number of different settings). 3. Chaco - my general mindset on this is that Chaco is great for plotting any and everything in a traits gui, but MPL is much better for the quickcalculations and plots that I make every day as a scientist. When a critical mass is reached it becomes better to integrate a tool into a GUI app, MPL becomes more difficult to manage and chaco is a better tool. But I think it makes a lot of sense to leverage MPL most as the wonderful "quick-and-dirty" command-line interactive plotting environment that it is rather than making it application-centric, which is where I can envision it going as soon as it has to run with traits. Now a great idea would be to include optional support for things like setting configuration files from a traits interface - I know I've seen talk of doing this for matplotlibrc at some point, and I'd definitely use that. Simlarly, some sort of traits-level extension to support more interactive plots and better layout seems like it could be done without requiring the core to use traits. As for the question of new directions to go: One thing I would like to see is a decent, simple 3D package in the core - nothing fancy (mayavi is great if you want to get fancy), but just something that makes great publication-quality figures with a quick and simple pylab-like interface. That's the main thing I have no good response for when people are contemplating switching to python/numpy/MPL. I also think it might be neat to implement auto-generating function plots - that is, plots where one of the axes is generated by a function at a resolution that scales as you change the plot. I've seen some chaco demos of something like this, but it's rather complicated to implement - a function like pyplot.plotfunc(func,'--b',initialrange=(-1,1)) that does exactly this would be a wonderful capability. This may be more a user perspective than a "dev" perspective, but still, there it is. On Thu, Jul 2, 2009 at 10:45 AM, Eric Bruning<eric.brun...@gmail.com> wrote: > On Wed, Jul 1, 2009 at 9:51 PM, Andrew Straw<straw...@astraw.com> wrote: >> Gael Varoquaux wrote: >>> On Wed, Jul 01, 2009 at 08:39:30AM -0500, John Hunter wrote: >>> >>>> Anyone interested? And if so, feel free to suggest topics or weigh in >>>> on some I listed. >>>> >>> >>> Actually, I have something I would like to discuss, but never really >>> could pull myself together to do it. I don't have time right now, but I >>> am still going to jot down the ideas. >>> >>> The axes and figure paradigm inherited from matlab works well for simple >>> things, but when I want to more complex layouts, I actually end up >>> struggling with calls to axes with numerical parameters to adjust. In >>> addition, if I have a function that creates a plot with multiple axes, >>> like the figure on: >>> http://neuroimaging.scipy.org/site/doc/manual/html/neurospin/activation_map.html >>> I may want to reuse that function to create more complex figures, >>> stacking several of these views, with possibly other plots. >>> >>> It seems to me having a level of granularity between the figure, and the >>> axes would help me a lot achieving these goals. I haven't had time to >>> hash out an API, or even solid concepts. For people who know LaTeX well, >>> let me draw an analogy: the figure is the page, the axis is the >>> character, what we are lacking in a 'minipage'. I would like a container >>> that can be stacked into a figure, and that can either hold axes, or >>> similar containers. That way, I could specify subplot, or axis relative >>> to this container, rather than relative to the whole figure, and it makes >>> it really easy for me to insert figures in larger figures. >>> >>> One possible API would be 'subfigure', which would have a signature >>> similar to 'axes', but of course things would need to be thought a bit >>> more in detail: do we want clf to erase the figure and not the subfigure? >>> I believe so. Do we want subplot to divide the subfigure, rather than the >>> figure? I believe so too. How do we go back to full figure without >>> erasing the subfigures it contains? I think subfigure(None) might work. >>> How do I select a subfigure I already created? Maybe by passing it a >>> subfigure instance, like the way axes work. >>> >>> Also, Chaco has the notion of containers, in which you can stack plots or >>> other containers. They have an additional feature which is that they >>> enable you to stack plot (these would be axes, in matplotlib terms) and >>> do an automatic layout of the plots. Very handy to have an extensible >>> canvas to display information on. Some sparse documentation: >>> http://code.enthought.com/projects/chaco/docs/html/api/containers.html >>> >>> I have been trying to find time to think about this for more than a year, >>> and haven't. This is why I am sending unfinished thoughts. I do believe >>> more thinking has to be done, and the subfigure proposition may not hold >>> at all. Also, I fear I do not have time to implement this. >>> >> I also have some not very fleshed out thoughts: my main feeling about >> MPL is that there's just too much layout happening to keep using the >> non-systematic delegation/notification "system" currently in place while >> allowing the devs to maintain their sanity and day jobs. I don't mean to >> disparage MPL -- it is quite a fantastic piece of code -- but there is a >> lack of abstraction of layout hierarchies and layout dependencies that >> makes development difficult. >> >> Therefore, I'd suggest that before adding on too many more nice >> features, we revisit the core layout and delegation system -- in the end >> it will make everything much easier. So, perhaps a useful thing would be >> for as many MPL devs as possible to sit together and discuss how we >> could do this. My thought right now would be to investigate the use of >> traits to codify the layout abstractions. >> >> Any effort like this will also obviously benefit from having an >> extensive test suite. I think all that's needed to get the tests at >> http://mpl-buildbot.code.astraw.com/waterfall to pass is that someone >> checks in new images made with the current MPL. I'd like to do this, but >> I'm really short on time at the moment. So, please, someone -- beat me >> to it -- it won't be hard! >> >> Those are my 2 cents. Hope to see you all at SciPy 2009! >> >> -Andrew > > > While we're dreaming big re-architecting dreams, I'll throw out an > idea related to Gael's suggestion: artist containers at the sub-axis > level. This would be a drawable / hideable container for an arbitrary > grouping of Artists that could be directly added to one (or more) > Axes. For those familiar with IDL, the IDLgrContainer in their object > graphics system is what I have in mind. > > I also concur with Andrew's assessment that interactive and layout > event handling is holding back some extra fun in interactive apps. I > have mixed feelings about using Traits; in my experience with writing > (only one) app, I felt like I had to subsume everything, my data > modeling included, under the Traits paradigm, such that I was no > longer writing Python but Traits. I found it very hard to include > other data objects created by other libraries without making them > Traitified, too. This could be a knowledge gap on my part, of course. > > David Beazley's course on coroutines > (http://www.dabeaz.com/coroutines/index.html, see esp. Part 3) and > this talk (http://carlfk.blip.tv/file/2232349) on asynchronous vs. > threaded multitasking both have some interesting thoughts on > standard-library ways to model OS-like behaviors such as event > handling. > > Thanks, > Eric > > ------------------------------------------------------------------------------ > _______________________________________________ > Matplotlib-devel mailing list > Matplotlib-devel@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > ------------------------------------------------------------------------------ Enter the BlackBerry Developer Challenge This is your chance to win up to $100,000 in prizes! 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