[SciPy-dev] Implementing a distance matrix between two sets of vectors concept
Bill Baxter
wbaxter@gmail....
Tue Jul 3 04:36:16 CDT 2007
I would use it.
I only need Euclidean distance,
Python API only is ok.
Data-types: float and double would do it for me. Double only if it's too
much effort to do both.
Order -- all combos of F and C both would be nice, but not critical
Strides -- with strides better than without, but not critical
nan -- don't need it.
--bb
On 7/3/07, David Cournapeau <david@ar.media.kyoto-u.ac.jp> wrote:
>
> Hi,
>
> for my machine learning toolbox, I need the concept of distance
> matrix, that is for two sets of vectors v and u (N u and M v), of
> dimension d, I want to compute the matrix D such as d(i,j) =
> distance(v_i, u_j). This is easy to do in numpy, but for big datasets,
> this becomes difficult without a significance loss of efficiency or big
> memory consumption.
> So I am thinking about implementing it in C. I think the overall
> concept is useful for other people, so before implementing something, I
> was wondering if other people would need/use it, and what would they need:
> - several distance (Euclidian, Mahalanobis, etc...), which would be
> a separate object to handle different sets of parameters.
> - C Api ?
> - datatypes ? Layout ? Contiguity ?
> - handling Nan ?
>
> cheers,
>
> David
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