For an interactive use, you may use callbacks to update the visibility
of ticks automatically.
Regards,
-JJ
import matplotlib.transforms as mtransforms
def update_yticks(ax):
axis = ax.yaxis
interval = axis.get_view_interval()
# get visible ticks
myticks = [t for t in axis.iter_ticks() \
if mtransforms.interval_contains(interval, t[1])]
# make all ticks visible again
for mytick in myticks: mytick[0].label1.set_visible(True)
# make first tick invisible
myticks[0][0].label1.set_visible(False)
# make last tick invisible
myticks[-1][0].label1.set_visible(False)
import matplotlib.pyplot as plt
ax = plt.subplot(111)
update_yticks(ax)
cid = ax.callbacks.connect('ylim_changed', update_yticks)
On Sun, Feb 6, 2011 at 5:17 PM, Paul Ivanov <pivanov...@gmail.com> wrote:
> Francesco Montesano, on 2011-02-04 17:01, wrote:
>> Dear all again,
>>
>> I've tried to play with it again, but I couldn't find a
>> solution for the problem. For clarity I report an example of
>> what each of the subplots looks like:
>
> Hi Francesco,
>
> thanks for the clarification, here are two ways to get the look
> you want. I added some comments to help you understand what was
> going on before. (The resulting figure is attached, just in case).
>
> import numpy as np
> import matplotlib.pyplot as plt
> mean=np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184,
> -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379])
> stddev= np.array([0.16351397,0.15075966,0.13413909,0.15404823,0.13559582,
> 0.13109754,0.12128598,0.11589682,0.11921571,0.10866761])
>
> ax = plt.figure().add_axes([0.1,0.1,0.8,0.8])
> ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev)
>
> ax.set_xlim([0.095, 0.195])
>
> lab = ax.get_ymajorticklabels()
> plt.draw() # ticks only get text assigned during a call to draw
> print lab
> for i in lab:
> print i # note that \u2212 is a unicode minus sign
>
> # this work for the first draw - relies on l.get_text() returning
> # nothing for labels which aren't used/drawn - which isn't the
> # case in general after panning and zooming interactively
> shown_lab = [l for l in lab if l.get_text()]
> shown_lab[0].set_visible(False)
> shown_lab[-1].set_visible(False)
>
> ## alternative solution without extra draw(). more robust, can be
> ## used even after initial draw.
> #ymin,ymax = ax.get_ylim()
> #tl = ax.yaxis.get_majorticklocs()
> #lab[(tl<ymin).sum()].set_visible(False)
> #lab[-(tl>ymax).sum()-1].set_visible(False)
>
> ## hybrid of the two.
> #ymin,ymax = ax.get_ylim()
> #tl = ax.yaxis.get_majorticklocs()
> #shown_lab = [l for l,t in zip(lab,tl) if t>ymin and t<ymax)
> #shown_lab[0].set_visible(False)
> #shown_lab[-1].set_visible(False)
>
> plt.show()
>
>
> best,
> --
> Paul Ivanov
> 314 address only used for lists, off-list direct email at:
> http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
>
> -----BEGIN PGP SIGNATURE-----
> Version: GnuPG v1.4.10 (GNU/Linux)
>
> iEYEARECAAYFAk1OWQMACgkQe+cmRQ8+KPekfgCfcY+R1vb2i/l/AoVsFZwsyqCC
> ihoAn1uni4kEu4Kq+B0IdCu26Kw1aA9Q
> =B6ZO
> -----END PGP SIGNATURE-----
>
> ------------------------------------------------------------------------------
> The modern datacenter depends on network connectivity to access resources
> and provide services. The best practices for maximizing a physical server's
> connectivity to a physical network are well understood - see how these
> rules translate into the virtual world?
> http://p.sf.net/sfu/oracle-sfdevnlfb
> _______________________________________________
> Matplotlib-users mailing list
> Matplotlib-users@lists.sourceforge.net
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>
------------------------------------------------------------------------------
The modern datacenter depends on network connectivity to access resources
and provide services. The best practices for maximizing a physical server's
connectivity to a physical network are well understood - see how these
rules translate into the virtual world?
http://p.sf.net/sfu/oracle-sfdevnlfb
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/matplotlib-users
