There are a bunch of points X, given in n-dimensional space (suppose we have two-dimensional, that is, the dimension of the array X is a bunch of x 2),
there is a single point C in the same space (dimension 1x2)
and there is a dist (u, v) metric, defined over a space, which determines the distance between two points (let us have a Euclidean metric, dist () returns a float).
Is there in pure python or in numpy (or somewhere else, to peep) a way to calculate the distances from C to all points X, faster than
[dst(x,C) for x in X]
And it is corny for a very long time in seconds.
In principle, it is also sufficient to obtain only the sum of these distances, if it suddenly turns out to be easier.