Sun Nov 2 18:47:14 CST 2008
Thanks. I created a spatial and spatial/tests directory in the SciPy
trunk. This should not pose an issue when merging the kd-tree code
from the spatial branch into the trunk, just change the setup.py and
__init__.py accordingly. After fixing a few minor import bugs caused
by the move, I am pleased to report all the cluster and distance tests
I had a chance to peruse the code in the spatial branch, and it looks
like there are a considerable number of tests for the kd-tree code. It
seems mature enough for it to be incorporated into the 0.7 release as
a technology preview. I think we should move that code over into the
trunk too, since this will give us more feedback from early adopters
and testers so we can better refine. It should also be noted, we are
changing the module index in the documentation to indicate those
modules/packages that are part of the technology preview.
Would others care to comment?
On Sun, Nov 2, 2008 at 11:01 AM, Anne Archibald
> 2008/11/2 Jarrod Millman <email@example.com>:
>> Damian Eads is joining the Berkeley sprint today and we were hoping to
>> make a change that was discussed at the SciPy conference and on the
>> list a few times. As part of his hierarchical clustering work, Damian
>> wrote a module for a bunch of different distance functions:
>> This is obviously much more generic and useful than the domain of
>> clustering. So we were proposing to make distance a top-level
>> subpackage called:
>> Before he made the change, I wanted to run it by the list one last
>> time and see if anyone had any thoughts, comments, or suggestions.
> Very nice code!
> It seems closely related to scipy.spatial. It was agreed, fairly
> reasonably, that the new code in scipy.spatial wouldn't go into 0.7,
> but this could quite reasonably go into scipy.spatial now, I think.
> Just where to put it isn't so clear - if scipy.spatial already existed
> and were populated, I would be tempted to put this as
> Scipy-dev mailing list
Damian Eads Ph.D. Student
Jack Baskin School of Engineering, UCSC E2-489
1156 High Street Machine Learning Lab
Santa Cruz, CA 95064 http://www.soe.ucsc.edu/~eads
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