On Thu, Mar 18, 2010 at 7:46 PM, Fernando Perez <fperez....@gmail.com> wrote: > On Thu, Mar 18, 2010 at 3:49 PM, Christopher Barker > <chris.bar...@noaa.gov> wrote: >> >> >> Good solution, and thanks for working on this! > > Thanks. > > I have one more question on this feature. I personally think that > this should be the way to use mpl in general when scripting, and the > way I want to teach, because it's easy and short while encouraging > access to more robust patterns (figure/axes handing instead of the > stateful pyplot). For this reason, I think the name should be really > well chosen, and I'm not convinced fig_subplot is a very good one. > > I know naming discussions can be annoying, but if this ends up being > the most popular/common entry point for making plots, it may be worth > spending a moment on picking it right. Ideas (I'm *awful* at naming)? > > - plot_array? > - plots? > - subplots? > - parray? > - plotarr? > > - something actually good from someone else? > > I'll finish the patch tonight, we can always fix the name later as > it's a trivial search/replace on fig_subplots -> new_great_name.
I also think the name should be changed, and there should be an entry in the matplotlib.figure.Figure API. One additional suggestion is "subarray" and matplotlib.pyplot.subarray would be a thin wrapper to matplotlib.figure.Figure.add_subarray. The former would return (fig, axarray) using gcf() to get the current figure, and the latter would simply create the subarray and return it. The would break a bit with the pyplot "axes" and "subplot" commands that only return the Axes and Subplot instances (and not the implicit Figure instance created/used) but I can live with that because part of the goal here is to give easy access to axes and figure creation so the user can get in the habit of using the API directly for most things. As for the other name suggestions, I like "subplots". JDH ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Matplotlib-devel mailing list Matplotlib-devel@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-devel
