Eric Firing, on 2011-01-22 17:49, wrote: > >> Paul Ivanov, on 2011-01-22 18:28, wrote: > > Paul, > > Your example below is nice, and this question comes up quite often. If > we don't already have a gallery example of this, you might want to add > one. (Probably better to use deterministic fake data rather than random.) > > >> > >> import numpy as np > >> import matplotlib.pylab as plt > >> pts = np.random.rand(30)*.2 > >> pts[[7,11]] += .8 > >> f,(ax,ax2) = plt.subplots(2,1,sharex=True) > >> > >> ax.plot(pts) > >> ax2.plot(pts) > >> ax.set_ylim(.78,1.) > >> ax2.set_ylim(0,.22) > >> > >> ax.xaxis.tick_top() > >> ax.spines['bottom'].set_visible(False) > >> ax.tick_params(labeltop='off') > >> ax2.xaxis.tick_bottom() > >> ax2.spines['top'].set_visible(False)
Done in r8935, see examples/pylab_examples/broken_axis.py I documented the above, used deterministic fake data, as Eric suggested, and added the diagonal cut lines that usually accompany a broken axis. Here's the tail end of the script which creates that effect (see updated attached image). # This looks pretty good, and was fairly painless, but you can # get that cut-out diagonal lines look with just a bit more # work. The important thing to know here is that in axes # coordinates, which are always between 0-1, spine endpoints # are at these locations (0,0), (0,1), (1,0), and (1,1). Thus, # we just need to put the diagonals in the appropriate corners # of each of our axes, and so long as we use the right # transform and disable clipping. d = .015 # how big to make the diagonal lines in axes coordinates # arguments to pass plot, just so we don't keep repeating them kwargs = dict(transform=ax.transAxes, color='k', clip_on=False) ax.plot((-d,+d),(-d,+d), **kwargs) # top-left diagonal ax.plot((1-d,1+d),(-d,+d), **kwargs) # top-right diagonal kwargs.update(transform=ax2.transAxes) # switch to the bottom axes ax2.plot((-d,+d),(1-d,1+d), **kwargs) # bottom-left diagonal ax2.plot((1-d,1+d),(1-d,1+d), **kwargs) # bottom-right diagonal # What's cool about this is that now if we vary the distance # between ax and ax2 via f.subplots_adjust(hspace=...) or # plt.subplot_tool(), the diagonal lines will move accordingly, # and stay right at the tips of the spines they are 'breaking' best, -- Paul Ivanov 314 address only used for lists, off-list direct email at: http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
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