Alan G Isaac wrote: > Hi Zach, > > The use case I requested was for iteration over a > matrix where it is desirable that matrices are yielded. > That is not what you offered. > > The context for this request is my own experience: > whenever I have needed to iterate over matrices, > I have always wanted the arrays. So I am simply > interested in seeing an example of the opposite desire.
Gram-Schmidt orthogonalization. ortho = [mat[0] / sqrt(mat[0] * mat[0].T)] for rowv in mat[1:]: for base in ortho: rowv = rowv - base * float(rowv * base.T) rowv = rowv / sqrt(rowv * rowv.T) ortho.append(rowv) -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion