Glenn, What version of numpy are you using? What version of matplotlib? And what are the dimensions of your image array?
Eric G Jones wrote: > Thank you for the suggestion. > I now have the update time down to about 70 ms. > When I run the code through the profiler, I see that each plot update > requires a call to matplotlib.colors.Colormap.__call__, and each of > these calls takes 52 ms, 48 ms of which is spent inside the function > itself. This looks like it is the bulk of the delay, so if I can > optimize the Colormap.__call__ function, the performance should be > much improved. Unfortunately I cannot seem to get finer grained > information about what exactly is taking so long inside this function. > Can anyone provide any hints? > Thanks, > Glenn > > On Sat, Apr 12, 2008 at 7:02 PM, hjc520070 <[EMAIL PROTECTED]> wrote: >> I just use blit on imshow map, and work properly. Maybe the following code >> will help you. >> >> def ontimer() >> canvas.restore_region(background) >> im.set_array(Z) >> ax.draw_artist(self.imList[i]) >> canvas.blit(ax.bbox) >> canvas.gui_repaint() >> -- >> View this message in context: >> http://www.nabble.com/speeding-up-imshow-tp16623430p16656693.html >> Sent from the matplotlib - users mailing list archive at Nabble.com. ------------------------------------------------------------------------- This SF.net email is sponsored by the 2008 JavaOne(SM) Conference Don't miss this year's exciting event. There's still time to save $100. Use priority code J8TL2D2. http://ad.doubleclick.net/clk;198757673;13503038;p?http://java.sun.com/javaone _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
