[SciPy-User] It is quite confusing to use scipy.spatial.distance
江大伟
zw4131 at gmail.com
Sun May 29 12:19:30 EDT 2011
I want to computes euclidean distance between a vector and 2 vector. For
example:
A=numpy.array([0,0])
B= numpy.array([[1,0],[0,1]])
I want to computes euclidean distance between vector A and each vector in
matrix B.
My expected result is the vector [1,1]
So I use scipy.spatial.distance.cdist(A, B ,'euclidean')
But the error said A must be a 2-dimensional array.
So I turned to use scipy.spatial.distance.euclidean(A,B), it worked, but the
result was a value 1.4142.
It was quite confusing!!
So I suggest adopting an uniform function to Computes the distance between
any-dimensional array. Scipy.spatial.distance.cdist() is a very good
function, but 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 !!.
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