I think there is something to be said for not starting from pylab. Answering questions on SO, a good chunk of them (by volume) can be traced back to not understanding the magic that pylab is doing for you in the background or not even knowing magic is being done for you. Starting from pylab makes easy stuff trivial, but slightly more complicated things a much bigger lift to figure out how to do (as compared to the conceptual difference in how hard they are).
A tutorial that starts from the POV of building the figure out of parts sounds like a good idea to me. At a minimum, a key with the different parts of the figure labeled with what family of classes control them would be great (or if something like that already exists make it easier to find;)) Tom On Mon, Mar 25, 2013 at 12:03 PM, Benjamin Root <ben.r...@ou.edu> wrote: > > On Mon, Mar 25, 2013 at 12:46 PM, Phil Elson <pelson....@gmail.com> wrote: >> >> >I am putting together a beginners tutorial proposal that I will submit >> > soon >> >> That's great to hear! Are you planning on making the tutorial material >> part of mpl's docs or using the content that is already out there? >> >> > > It is all new stuff, but I have been taking inspirations from other > tutorials I have seen and said to myself "You are all teaching it wrong!" > :-P > > I am ignoring pylab (risky, I know), starting with a *very* basic NumPy > primer, and then moving on to teach matplotlib from the perspective of "here > are what the parts of a plot are called and what they are for, and see what > happens when we put those parts together". It is an ingredients approach, > essentially. > > Hopefully, aspects of it will be useful for the docs when it is finished. I > am also hoping that having a ipython notebook version of it will help others > to improve it for future conferences (there should always be an intro to > matplotlib tutorial at SciPy). > > Ben Root > > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://p.sf.net/sfu/appdyn_d2d_mar > _______________________________________________ > Matplotlib-devel mailing list > Matplotlib-devel@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > -- Thomas A Caswell PhD Candidate University of Chicago Nagel and Gardel labs tcasw...@uchicago.edu jfi.uchicago.edu/~tcaswell o: 773.702.7204 ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_mar _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
