matplotlib-devel Mailing List for matplotlib

The present NavigationToolbar2 is very nice, but I am thinking about an 
improvement: adding a button that would rotate a constraint among three 
possibilities, so that pan/zoom and rectangle select could be set to 
affect only X, only Y, or be left unconstrained as at present.
The problem with the present system is that often one really wants to 
pan and zoom in only one direction, or at least one direction at a time. 
 For example, I have a dataset consisting of 10000 profile measurements 
(increasing with time on the X-axis) with 20 vertical bins. I want to 
display the whole thing with pcolorfast, and then zoom in on particular 
sections to the point where the individual profiles can be seen clearly. 
 Doing this with the present pan/zoom and rectangle tools is awkward--I 
am not coordinated enough to move the cursor perfectly horizontally, or 
to select a rectangle that goes exactly from top to bottom. I suspect 
that there are many data analysis applications like this, where one 
wants to vary only one dimension at a time.
Although there might be more elegant ways to do it, I think the simplest 
way to get this functionality across backends would be to add a single 
button that rotates a variable among values of 'X', 'Y', and 'XY', and 
then let that variable constrain the effects of pan/zoom and 
rectangle-select. It would be nicer, but more work, to have the 
variable change the rubberband to a span-select in the latter case; I am 
inclined to start with the easiest implementation I can come up with. I 
think the simple approach can be done with only a little bit of change 
in the backends.
Comments? Objections?
This could also be done by making a NavigationToolbar3, but I think that 
even with inheritance from NavigationToolbar2, this would require more work.
Eric

On Sat, Apr 12, 2008 at 3:24 PM, John Hunter <jd...@gm...> wrote:
> On Sat, Apr 12, 2008 at 2:19 PM, Eric Firing <ef...@ha...> wrote:
> > and then this was added, as something else that had been agreed at the
> > same sprint:
> > import pylab as plt
> > I think this is a mistake, and it should have been
> >
> > import matplotlib.pyplot as plt
>
> This is what we agreed to (import matplotlib.pyplot as plt) during the
> numpy sprint (I was on google chat remotely but participated in the
> discussion). I agree that pylab as plt would just add to the
> confusion. We agreed on promoting (and I currently use)
>
>
> import numpy as np
> import scipy as sp
>
> import matplotlib.pyplot as plt
Sorry, that was my mistake. Thanks for clearing it up.
-- 
Jarrod Millman
Computational Infrastructure for Research Labs
10 Giannini Hall, UC Berkeley
phone: 510.643.4014
http://cirl.berkeley.edu/