matplotlib-users Mailing List for matplotlib

This matplotlib release will be included in enthought's next release
of enthought python, which is widely used by windows users for
scientific computing. I'd like to get an stable-as-possible release
in, since enthought python is released very infrequently. Joe Cooper,
who is handling the release, says we can get fixes in until sometime
on Monday, so I'd be much obliged if you all could stress test this
release in case I need to get a bug-fix in. There have been some
potentially script breaking substantial changes to the numerix module
described below, so these tests are doubly important.
What's new in matplotlib 0.71
numerix refactor
 The organization of the numerix module was refactored to be mindful
 of namespaces. See http://matplotlib.sf.net/API_CHANGES. pylab no
 longer overrides the built-ins min, max, and sum, and provides amin,
 amax and asum as the numerix/mlab versions of these. pylab defines
 __all__ to prevent surprises when doing from pylab import *. To see
 the complete list of symbols provided
 >>> import matplotlib.pylab
 >>> matplotlib.pylab.__all__
contour zigzag bug fixed
 Thanks Nadia for the blood, sweat and tears, and Dominique for the
 report.
contour colormaps
 Contour now uses the current colormap if colors is not provided, and
 works with colorbars. See examples/contour_demo2.py
colorbar enhancements
 Horizontal colorbars supported with keyword arg
 orientation='horizontal' and colorbars can be placed in an arbitrary
 axes with keyword arg cax.
accents in mathtext
 Added accents to mathtext: \hat, reve, \grave, ar, cute, ilde, ec,
 \dot, \ddot. All of them have the same syntax, eg to make an overbar
 you do ar{o} or to make an o umlaut you do \ddot{o}. The shortcuts
 are also provided, eg: "o 'e \`e \~n \.x \^y . See
 examples/accent_demo.py
fixed super/subscript parsing in mathtext
 Widowed superscripts now work, eg r'$^12 m{CO}$'
little bugs and enhancements
 Plugged some memory leaks in wx and image module, fixed x,y args in
 contour, added latex symbol kappa, fixed a yticklabel problem under
 change in clim, fixed colorbar number of color bug, fixed
 set_clip_on bug, reverted pythoninspect in tkagg, fixed event
 handling bugs, fixed matlab-compatible load function, exposed vbox
 attr in FigureManagerGTK.
I did not get a chance to get the aspect=preserve imshow bugs fixed on
this iteration. Something for next time!
 http://matplotlib.sourceforge.net
JDH

>>>>> "Dominique" == Dominique Orban <Dom...@po...> writes:
 Dominique> Results seem inconsistent; if i replace the
 Dominique> 'rosenbrock' function in my previous script with
The bug resulted from improperly initializing an array used in the
contour extension code. Fortunately Nadia has found and fixed it.
The changes are in CVS (colormaps and colorbars for contour too!) and
will be out in the next release, coming soon to theaters
everywhere.....
JDH

>>>>> "Simon" == Simon Burton <si...@ar...> writes:
 Simon> add/remove methods ? Or is the (recently changed)
 Simon> collections attribute the Right Way (TM) to do this kind of
 Simon> thing ?
Yes, I you're doing it the right way. I decided to make these
attributes "public" when working on the figures for the "Matplotlib
API" chapter of the users guide, eg Figure 7.4, which shows the Artist
containment hierarchy and the respective attribute names. 
 http://matplotlib.sourceforge.net/users_guide_0.70.pdf
I've historically been reluctant to publicize the API in order to
leave wiggle room for refactoring the internals, but now I'm
reasonably satisfied and the API has been mostly stable for several
releases. The choice to remove the underscore on these attribute
names was an unheralded decision that the basic API / containment
hierarchy is stable for the foreseeable future.
You can safely use the list remove method w/o breaking anything. If
you want to manually add an artist to the Axes, you should use the
Axes add_patch, add_line, add_collection, etc, methods rather than the
list append method, unless you really know what you are doing. These
add_* methods set some default attributes of the artist, eg they call
the set_figure, set_transform, and update the data limits for viewport
autoscaling. So you either need to use the add_* methods to add
artists or call these methods yourself.
JDH

Hi,
I've been working on a data entry app: the user clicks on a canvas to place scatter plot items.
The app also has an "eraser" to remove points. So, I'm having to get the collections attribute
from the axes, look at offsets, and remove items etc. It all feels like a real hack, eg.
the (older) installed version of matplotlib uses ._collections instead of (the newer) .collections attribute.
Well, I'd like to suggest adding a method or three to the axes class that allows a client
to get/change these items. It doesn't look like it would take much code.
Alternatively, I guess the app could just clear the axes and scatter down the points again, minus the
deleted point. This is not so clever though: as more items are added to the axes (lines/images etc.)
it would get more difficult to manage these. And since the axes already manages these items,
why not expose some kind of list-like add/remove methods ? Or is the (recently changed) collections attribute
the Right Way (TM) to do this kind of thing ?
ciao, (and by the way, I am immensly impressed with the matplotlib code)
Simon.
--
Simon Burton, B.Sc.
Licensed PO Box 8066
ANU Canberra 2601
Australia
Ph. 61 02 6249 6940
http://arrowtheory.com