What's the best way of assembling a big matrix from parts? I'm using lagrange multipliers to enforce constraints and this kind of matrix comes up a lot:
[[ K, G], [ G.T , 0]] In matlab you can use the syntax [K G; G' zeros(nc)] In numpy I'm using vstack([ hstack([ K,G ]), hstack([ G.T, zeros((nc,nc)) ]) ]) Which has a lot of excess verbiage and parentheses that make it hard to type and hard to parse what's going on. It would be a little nicer if there were some kind of function like 'arraystack': arraystack( [ [K, G], [G.T, zeros((nc,nc)) ]] ) Is there anything like this already? I haven't found anything in the example list like that. But maybe concatenate() is flexible enough --bb _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
