The original notes were takenon etherpad. @mdboom has reorganized them and summarized them here.

MEP17

• Interactive modification of plots would address the issues on tweaking commented on at the plotting competition

• Need a way to write out the tweaks "as code" afterward to paste back into a script (or into the IPython notebook)

• Igor Pro has a good track record of having 1-1 correspondence between image and code

• Veusz can also produce code from a manually tweaked plot

• vispy: High performance plotting project (in early days)

• We should create a MEP on openGL (and more generally for high performance plotting)

• An analysis of performance bottlenecks should be done, perhaps a standard set of benchmarks to track over time (#2188)

  • in general, this kind of a benchmarking of the fall-off of performance would be useful to point users to.

  • Experiment with reducing quality during panning/zooming, and then going back to full quality on idle (much like older 3D packages used to show only a bounding box during rotation). (#2189)

• We should add built-in instrumentation of matplotlib methods -- this would allow us to collect statistics about performance as well as more easily help users debug problems when they are hard to reproduce. (#2190)

MEP19

• Use something we either rent or control instead of travis in order to collect more data on different platforms.

• We need a larger test matrix -- Python, Numpy, GUI framework, Freetype and libpng versions. From this we can keep on top of our version requirements.

• In a follow-up breakout session, we thought the minimum requirements would be:

  • Mac and Linux virtual machines that a number of core developers can log into

  • Windows virtual machines if feasible

  • Github integration (like what Travis does)

  • The ability for other machines with different configurations to publish their results to a public web server

  • Saving the output of the tests

  • Saving build products ("daily", or more often)

  • Auto-building the docs

• We have Launchpad daily buildshttps://code.launchpad.net/~takluyver/+recipe/matplotlib-daily

MEP20

• use notebook output and potentially store the output in the notebook to store the image output in the repo

• have an interactive plotting documentation system in which you can edit plots online (Google App engine)

MEP16

• Enthought uses the casuarius constraint solver for their (Enaml)[http://docs.enthought.com/enaml/index.html] layout engine -- steal or borrow?

• Tight-layout goes a long way already - thank you jae-joon

• See #1109 for earlier (and continued) discussion

• There is disagreement about whether constrained layout and plot editor are orthogonal and whether we could pursue both in parallel or should pick one or the other as a focus

We should revive this.

surveyresults

MEP18

• Plot method could take "plottable" objects (rather than just Numpy arrays), and those objects could obtain or generate data in other ways (such as for functional plotting)

• This lead to a discussion about 2.0 (i.e. breaking some backward compatibility). However, it was noted that we were a room full of developers, not users.

• We should keep track of the versions of Numpy and other dependencies in the major long-term-release Linux distributions (Debian, RedHat, Ubuntu) and ensure (probably though better CI) that we continue to support them. (#2191) The census (above) may help us with this kind of thing as well.