Re: [Matplotlib-users] Keeping several axis scalings in sync?

[Norbert N. <Nor...@gm...>]

Thanks! Perfect! I *love* matplotlib!!!

Darren Dale wrote:
> On Saturday 12 April 2008 7:19:32 am Norbert Nemec wrote:
>   
>> Hi there,
>>
>> I often have the case that I want to view different data sets that share
>> one axis. Imagine, for example, a time series of several different
>> observables. Since all observables may have different units, scales and
>> offsets, I would want to display them as separate subplots that have the
>> same x-axis (time) but indepent y scales.
>>
>> Is there a way to lock the scales of several subplots so that when I
>> zoom into one of the subplots interactively, the scale of the other
>> subplots is automatically adjusted? (Preferably something simple enough
>> to use it in quick-and-dirty scripts or even interactive sessions.)
>>     
>
> I think shared_axis_demo.py, in the examples archive, is what you are looking 
> for. It is well documented, and simple enough to include here in its 
> entirety:
>
> """
> You can share the x or y axis limits for one axis with another by
> passing an axes instance as a sharex or sharey kwarg.
>
> Changing the axis limits on one axes will be reflected automatically
> in the other, and vice-versa, so when you navigate with the toolbar
> the axes will follow each other on their shared axes.  Ditto for
> changes in the axis scaling (eg log vs linear).  However, it is
> possible to have differences in tick labeling, eg you can selectively
> turn off the tick labels on one axes.
>
> The example below shows how to customize the tick labels on the
> various axes.  Shared axes share the tick locator, tick formatter,
> view limits, and transformation (eg log, linear).  But the ticklabels
> themselves do not share properties.  This is a feature and not a bug,
> because you may want to make the tick labels smaller on the upper
> axes, eg in the example below.
>
> If you want to turn off the ticklabels for a given axes (eg on
> subplot(211) or subplot(212), you cannot do the standard trick
>
>    setp(ax2, xticklabels=[])
>
> because this changes the tick Formatter, which is shared among all
> axes.  But you can alter the visibility of the labels, which is a
> property
>
>   setp( ax2.get_xticklabels(), visible=False)
>
>
> """
> from pylab import *
>
> t = arange(0.01, 5.0, 0.01)
> s1 = sin(2*pi*t)
> s2 = exp(-t)
> s3 = sin(4*pi*t)
> ax1 = subplot(311)
> plot(t,s1)
> setp( ax1.get_xticklabels(), fontsize=6)
>
> ## share x only
> ax2 = subplot(312, sharex=ax1)
> plot(t, s2)
> # make these tick labels invisible
> setp( ax2.get_xticklabels(), visible=False)
>
> # share x and y
> ax3 = subplot(313,  sharex=ax1, sharey=ax1)
> plot(t, s3)
> xlim(0.01,5.0)
> show()
>
>
> Darren
>
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