Fast weighted euclidean distance between points in arrays

Question

I need to efficiently calculate the euclidean weighted distances for every x,y point in a given array to every other x,y point in another

Answer 1

You can avoid looping by using code that looks like the following:

def compute_distances(A, B, W):
    Ax = A[:,0].reshape(1, A.shape[0])
    Bx = B[:,0].reshape(A.shape[0], 1)
    dx = Bx-Ax

    # Same for dy
    dist = np.sqrt(dx**2 + dy**2) * W
    return dist

That will run a lot faster in python that anything that loops as long as you have enough memory for the arrays.