efiring wrote: > > Stop saying you want to avoid show(); (…). You probably *need* to use > show; with 1.0.1 > in interactive mode, it will not block. Your script can close the > windows; your user doesn't have to do so manually. > You are right: your script shows that the latest (1.0.1) show() is great, as it is non-blocking in interactive mode (except with the macosx backend). (It is the pre-1.0.1 blocking show() that was not a solution.)
efiring wrote: > > It sounds like you are indeed talking about a free-standing script, that > is, not involving ipython or other intermediate shell, correct? > Correct. efiring wrote: > > Does the attached > script illustrate something roughly like what you are trying to do? > Yes, it does, thanks. Just a detail: since the interactive mode is on, the plt.draw()s in the second part are not necessary, are they? So, to summarize, the latest 1.0.1 show() does the actual drawing (not draw()), is non-blocking in interactive mode, and can be called multiple times. This is both convenient (no need to manually close umpteen windows one by one), and efficient (non interactive mode can be used up until show() is called). Thus, the practical side of the problem is closed: thanks! I have been asking these questions because I have been using and teaching (Python and) Matplotlib for 3 years, now, to students who use a variety of OSes, so I wanted to get things straight. On the "theoretical" side, draw() is actually rarely used for drawing or refreshing simple figures (including common non-animated figures), but is more for "some more advanced features such as animations and widgets, as well as for internal use.", as Ben was writing, right? And show() is really the function that commonly does the actual display or refresh, right? If this is correct, I will be done with my questions. :-) -- View this message in context: http://old.nabble.com/Exact-semantics-of-ion%28%29---tp31728909p31739359.html Sent from the matplotlib - users mailing list archive at Nabble.com. ------------------------------------------------------------------------------ Simplify data backup and recovery for your virtual environment with vRanger. Installation's a snap, and flexible recovery options mean your data is safe, secure and there when you need it. Data protection magic? Nope - It's vRanger. Get your free trial download today. http://p.sf.net/sfu/quest-sfdev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
