Where do two 2-D arrays begin to overlap each other?
Can you say more? What model are you using? What are you modelling? How is it computed?
Can you make the dimensions match to avoid the fit? (i.e. if B doesn't depend on all of A, only plug in the part of A that B models, or compute boring values for the parts of B that wouldn't overlap A and drop those values later)
I'm working with model output at the moment, and I can't seem to come up with a nice way of combining two arrays of data.  Arrays A and B store different data, and the entries in each correspond to some spatial (x,y) point -- A holds some parameter, and B holds model output.  The problem is that B is a spatial subsection of A -- that is, if the model were for the entire world, A would store the parameter at each point on the earth, and B would store the model output only for those points in Africa.
So I need to find how much B is offset from A -- put another way, I need to find the indexes at which they start to overlap.  So if A.shape=(1000,1500), is B the (750:850, 200:300) part of that, or the (783:835, 427:440) subsection?  I have arrays associated with both A and B which store the (x,y) positions of the gridpoints for each.
This would seem to be a simple problem -- find where the two arrays overlap.  And I can solve it with scipy.spatial's KDTree simply enough, but it's very slow.  Anyone have any better ideas?