On Mon, Mar 25, 2013 at 12:17 PM, Thomas A Caswell <tcasw...@uchicago.edu> wrote: > 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
That seems like a good approach to me. Thanks for doing this. I just submitted a tutorial, but it assumes people know how to make a line plot already. Perhaps I should learn from this assumption and communicate better on this list and garner interest about what people would like to see a priori. Thanks for putting this together, Ben. Out of interest, are you diving straight into the pyplot state machine, or are you taking the more object oriented approach of setting up the canvas and figure object explicitly? I use the OO approach all the time, but I only use the non-interactive backends like Agg and PDF. On a not-too-orthogonal note, I'd personally like to see a tutorial on hooking in mpl into other GUI-like applications. Paraview seems to do this a little, but I'd like to see someone do a soup-to-nuts walkthrough for it, just because I have no experience doing this; I'm a terminal hermit. Best wishes, Damon -- Damon McDougall http://www.damon-is-a-geek.com Institute for Computational Engineering Sciences 201 E. 24th St. Stop C0200 The University of Texas at Austin Austin, TX 78712-1229 ------------------------------------------------------------------------------ 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
