> What would be great is if you could refactor the basic functionality > into a matplotlib.Axes.breaky method (and possibly breakx but most > people request a broken y axis), which would resize the "self" axes > and return the broken compliment which could be plotted onto. Then > you could provide a thin pyplot wrapper much like pyplot.twinx, so > that pyplot as well as API users could benefit.
I can try to do this. I think I would prefer, however, not to resize the "self" axes and continue with my current approach of creating two new axes within the original axes. On the user end, I think it makes more sense to set the title and ylabel of the main axes, rather than setting them for the individual upper and lower axes. More on that below. >> The only real problems here is that you need to >> explicitly plot things on both the upper and lower axes, and then I haven't >> figured out how to push out the y-axis label of the main axes object so it >> doesn't overlap with the tick labels of the upper and lower axes. So, I >> instead moved the y-labels of the upper and lower axes so that they appear >> at the center of the axis, but this is problematic. Any thoughts on how to >> do that part better? > > klukas, I'm afraid I don't understand your issue... Can you explain using it > differently? In my approach, you end up with a main axes object that is invisible, and then two visible axes objects (upper and lower) within the main axes. I would ideally like to have the y label display in the middle of the main y-axis, independent of where the break lies. If I place a y label on the main axes (which has ticks or tick labels), though, it appears right up against the axis line. I'd like it to be placed further to the left, clear of the tick labels that appear on the upper and lower axes. So, I'd like to be able to access whatever algorithm is used to choose the offset of the axis label, and explicitly set the offset of the ylabel for the main axes so that it clears the tick labels. // Jeff ------------------------------------------------------------------------------ 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
