James K. Gruetzner wrote: >>> I'm running Fedora 8, python 2.5.1, and matplotlib 0.91.2-1.fc8 from >>> the yum repository. Backend is set to GTKAgg in my matplotlibrc file. >> (On this list top-posting is frowned upon -- it makes the conversation >> difficult to follow.) > > I understand. Sorry. Each list is different: I'm new here, and will try > remember.
No problem. Also, don't forget reply-to-all, so that the whole of the list can chime in here. :) >> Your analysis is correct, the call to show() activates the GUI mainloop >> and does not return until the window is closed. Within ipython there is >> some magic that occurs that runs the mainloop in a separate thread. >> What do you need to do after the call to show()? > > In my current situation, I need to extract and display data (images) > independently from several different files as part of debugging a larger > application. (I'm really not reading a file into the original array, but > running some shell commands using os.popen2(...) to eventually populate the > array: that part works.) The upshot is that in the course of a few hours, > I may have to display (and kill) a large number of images. > > The current "hang" means that I have an effective memory leak, and I'd have > to > keep track of Process IDs and manually kill them every so often. Were the > pylab.show() command to return after closing the window (clicking on the X), > then a backgrounded or daemon process should terminate. But it doesn't. > This seems to be the same problem causing Dragan S.'s problem. > > I'm not sure if this is a bug or a feature, but would assuredly like to find > a > way to kill the leak. > I'm not sure about the lack of returning after the call show(), though it does sound like a bug. What I *do* know is that multiple calls to show() is frowned upon (if not just completely unsupported). What you probably want to look at is the dynamic_image_gtkagg.py example (in the examples/ directory). Since you're already using GtkAgg, it should be *really* easy to adapt the example to fit your needs. I've personally adapted it to do a live data display of a simulation run. If you *need* it to wait for user interaction before continuing, there might be a little bit more work, but I don't think it'd be much. You could probably instead look at some of the Matplotlib UI widgets, like in the buttons.py example. Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma ------------------------------------------------------------------------- Sponsored by: SourceForge.net Community Choice Awards: VOTE NOW! Studies have shown that voting for your favorite open source project, along with a healthy diet, reduces your potential for chronic lameness and boredom. Vote Now at http://www.sourceforge.net/community/cca08 _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
