[SciPy-dev] Implementing a distance matrix between two sets of vectors concept

[Bill Baxter]

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 at 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
> _______________________________________________
> Scipy-dev mailing list
> Scipy-dev at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-dev
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scipy-dev/attachments/20070703/1d58780d/attachment.html>