[SciPy-dev] scipy.distance

Damian Eads eads@soe.ucsc....
Sun Nov 2 23:47:52 CST 2008

Excellent Anne. Please incorporate the code into the spatial/
directory at your convenience.



On Sun, Nov 2, 2008 at 9:03 PM, Anne Archibald
<aarchiba@physics.mcgill.ca> wrote:
> 2008/11/2 Jarrod Millman <millman@berkeley.edu>:
>> On Sun, Nov 2, 2008 at 4:47 PM, Damian Eads <damian.eads.lists@gmail.com> wrote:
>>> 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.
>> +1
>> I think that it would be better to get the kd-tree code out in this
>> release, but clearly mark it as a technology preview.  This will give
>> us the opportunity to get more feedback and testing without any major
>> restrictions on improving the API.  I know that there was some
>> concerns that including new code could slow down the release of 0.7,
>> but I don't think that has to be the case.  Since it is a technology
>> preview and isn't changing current behavior; as long as it compiles
>> and doesn't create a lot of noise for testing, I don't think I will be
>> necessary to delay the release for it.
>> Thoughts?
> I think for computing nearest neighbors of points, the code is
> basically done. For other applications, well, it's not yet clear what
> other applications people want. One aspect I do expect will change is
> the API: there are many applications where a kd-tree is a useful data
> structure (beyond simple point nearest neighbor), but for most of them
> one needs to write a custom tree traversal and possibly annotate the
> tree. I'm not sure how to set the kd-tree code up so that it can
> easily (and efficiently) be used for that, but I think the only way to
> find out is for users to actually go ahead and try to do it.
> So I think as long as it's clear to users that the API may still
> change, it will actually help to put the code in 0.7.
> Anne
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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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