On Sep 14, 4:54 pm, Gregory Ewing <greg.ew...@canterbury.ac.nz> wrote: > Suppose I have two N+2 dimensional arrays, representing > N-d arrays of 2-d matrices. I want to perform matrix > multiplication between corresponding matrices in these > arrays. > > I had thought that dot() might do this, but it appears > not, because e.g. applying it to two 3-d arrays gives > a 4-d array, not another 3-d array. > > I'd also like to be able to find the inverse of each > matrix in one of these arrays, but again, inv() doesn't > do what I want -- it only works on 2-d arrays. > > Any thoughts on how to achieve these things using numpy > functions?
I find for situations like this the best thing I can do is hand code the bounded operation and use the slicing to handle the arbitrarily large stuff with slicing. So, r[:,:,1,1] = a[:,:,1,1]*b[:,:,1,1] + a[:,:,2,1]*b[:,:,1,2] r[:,:,1,2] = a[:,:,1,2]*b[:,:,1,1] + a[:,:,2,2]*b[:,:,1,2] etc. Carl Banks -- http://mail.python.org/mailman/listinfo/python-list
