[SciPy-User] It is quite confusing to use scipy.spatial.distance

[江大伟]

I am sorry that I did not say clearly.I mean:

Extending Scipy.spatial.distance.cdist() to be an uniform function to
Computes the distance between any-dimensional array.



For example:

A=numpy.array([0,0])

B=numpy.array([1,0])

scipy.spatial.distance.cdist(A, B ,'euclidean')

can return a value 1



A=numpy.array([0,0])

B=numpy.array([[1,0],[0,1]])

scipy.spatial.distance.cdist(A, B ,'euclidean')

can return a vector [1,1]



A=numpy.array([[0,0],[0,1]])

B=numpy.array([[1,0],[0,1]])

scipy.spatial.distance.cdist(A, B ,'euclidean')

can return a matrix[[1,1],[1.414,0]]



2011/5/30 Pauli Virtanen <pav at iki.fi>

> Mon, 30 May 2011 20:26:13 +0800, 江大伟 wrote:
> > Thanks. This is an googd solusion.
> > But it is not the best solusion.
> >
> > Using an uniform function to Computes the distance between
> > any-dimensional array. Scipy.spatial.distance.cdist() is a very good
> > function, and it can be extended to Computes the distance between a
> > vector and a vector as well as between a vector and n vectors. That
> > would be perfect !!.
>
> I do not understand what you exactly mean. The example I gave does
> exactly what you describe.
>
> --
> Pauli Virtanen
>
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