Just wondering if anyone knows how to do a pixel offset in matplotlib?
I've tried running the example in http://www.scipy.org/Cookbook/Matplotlib/Transformations#line-58 but
it appears to have been trashed by changes to the api. The functions
in the no-offset_copy function version don't exist any more and their
replacements don't work the same way, and the offset_copy function is
not available. (At least I am assuming it is because of updates rather
then my copy of Matplotlib being out of date: 0.99.1.1) This is a very
useful function if you're doing discrete data plots like I am and you
want uniform clusters of points.
offset_copy is still available, but unfortunately doesn't work with the cookbook example because of a bug that was inadvertently introduced into matplotlib.
The bug is that offset_copy should have been defined as:
That is, the "fig" argument was originally optional, and in July 2008 I accidentally was made it "required".
This will be fixed in the next release of matplotlib -- in the meantime the workaround to get the Cookbook recipe to work is to call offset_copy like this:
If that change doesn't fix the recipe for you, please send a full traceback of the error so we can diagnose the problem. (FWIW -- I don't have edit privileges for the cookbook page, or I would go in and fix this...)
Cheers,
Mike
mikey wrote:
···
Hi there,
Just wondering if anyone knows how to do a pixel offset in matplotlib?
I've tried running the example in http://www.scipy.org/Cookbook/Matplotlib/Transformations#line-58 but
it appears to have been trashed by changes to the api. The functions
in the no-offset_copy function version don't exist any more and their
replacements don't work the same way, and the offset_copy function is
not available. (At least I am assuming it is because of updates rather
then my copy of Matplotlib being out of date: 0.99.1.1) This is a very
useful function if you're doing discrete data plots like I am and you
want uniform clusters of points.
Thanks for your time.
Regards,
Mikey
------------------------------------------------------------------------------
Download Intel® Parallel Studio Eval
Try the new software tools for yourself. Speed compiling, find bugs
proactively, and fine-tune applications for parallel performance.
See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev
_______________________________________________
Matplotlib-users mailing list
Matplotlib-users@lists.sourceforge.net matplotlib-users List Signup and Options
--
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA