Yes, that makes it work.
Thank you JJ.
On Tue, Mar 23, 2010 at 10:58 AM, Jae-Joon Lee <lee.j.j...@gmail.com> wrote:
> In the current implementation, sharing the axis does not mean sharing its
> scale.
> This is not a subplots-specific issue, but applies to all kind of axes
> sharing.
>
> So you need to change the scale of all the axes even though they have
> shared axis.
> What seems to be a better approach to me is to initialize "subplots"
> with proper scale.
>
> f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2,2, sharey=True,
> subplot_kw=dict(yscale="log"))
>
> Regards,
>
> -JJ
>
>
> On Mon, Mar 22, 2010 at 1:18 PM, Gökhan Sever <gokhanse...@gmail.com>
> wrote:
> > Hello,
> >
> > I am testing the newly added subplots function in ipython -pylab with the
> > following code:
> >
> > f, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2,2, sharey=True)
> > ax1.plot(np.random.random(20))
> > ax2.plot(np.random.random(20))
> > ax3.plot(np.random.random(20))
> > ax4.plot(np.random.random(20))
> >
> > For some reason scaling the y-axes logaritmically works only on the
> focused
> > figure canvas, the rest of the subplots are scaled in a distorted
> fashion.
> > Axes labels change to proper notation but the scaling stays as if linear
> > along with the data. See for better description:
> > http://img408.imageshack.us/img408/7149/logscale.png
> >
> > Any ideas?
> >
> > --
> > Gökhan
> >
> >
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--
Gökhan
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