>>>>> "Kevin" == Kevin Horton <[EMAIL PROTECTED]> writes:
Kevin> I was doing some Googling to look for a way to solve a
Kevin> problem controlling sharex, and came across an example
Kevin> using axprops. This solved my problem, but now I wonder
Kevin> what other aspects I can control with axprops, or other
Kevin> similar methods. Where is axprops documented? I've looked
Kevin> via pydoc, and in the pdf documentation, but no dice.
axprops is simply a dictionary holding key/value pairs. It is not
part of the matplotlib API. Any function that takes keyword
arguments, such as the Axes constructor, can take a dictionary with
keyword/value pairs using the following syntax
a = Axes(fig, rect, **d)
where d is a dictionary. This is part of python, not matplotlib
proper, but because matplotlib makes extensive use of keyword
arguments, it is a handy trick to remember. When I am creating
several axes with shared properties, I often use it to have a single
customization point
axprops = dict(axisbg='yellow', xlim=(0,1))
for i in range(N):
fig.add_subplot(N,1,i+1, **axprops)
or something like that.
But I don't think this solves your problem: you can use this to turn
on the sharex feature but not to turn it off once it is already on.
As for your question about where to find the aspects of the Axes that
can be controlled this way, you can do it by consulting the class
documentation at http://matplotlib.sf.net/matplotlib.axes.html and
looking for methods that start with "set_" or by firing up an
interactive shell (see http://matplotlib.sf.net/interactive.html) and
using setp introspection
In [2]: ax = subplot(111)
In [3]: setp(ax)
adjustable: ['box' | 'datalim']
alpha: float
anchor: ['C', 'SW', 'S', 'SE', 'E', 'NE', 'N', 'NW', 'W']
animated: [True | False]
aspect: ['auto' | 'equal' | aspect_ratio]
autoscale_on: True|False
axis_bgcolor: any matplotlib color - see help(colors)
axis_off: void
axis_on: void
axisbelow: True|False
clip_box: a matplotlib.transform.Bbox instance
clip_on: [True | False]
cursor_props: a (float, color) tuple
figure: a Figure instance
frame_on: True|False
label: any string
lod: [True | False]
navigate: True|False
navigate_mode: unknown
position: len(4) sequence of floats
title: str
transform: a matplotlib.transform transformation instance
visible: [True | False]
xlabel: str
xlim: len(2) sequence of floats
xscale: ['log' | 'linear' ]
xticklabels: sequence of strings
xticks: sequence of floats
ylabel: str
ylim: len(2) sequence of floats
yscale: ['log' | 'linear']
yticklabels: sequence of strings
yticks: sequence of floats
zorder: any number
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