I'm going to be tagging the tree for the NumPy 1.0.2 release tomorrow
evening in preparation for the release on Monday. I've closed several
bugs. Are there any show-stoppers remaining to be fixed?
-Travis
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
