numerical python

[matt]

I was wondering if anyone had some pointers to articles on "efficient use of
numerical python".  I have used in the past for some smallish stuff ... spline
interpolations over spacial grids of 244x244 and temporal grids of around 100,
and it seemed kind of slow.  I guess all up I had about 120MB of data in
memory.  I haven't used it much so i assume that there may be good ways to have
large arrays of data and not so good ways.

More specifically I need to store objects and use their elements in large
matrix calculations.  I don't really want to go loading a matrix each time I
need to use one.  The two possibilities I thought of was storing just the
references to the object elements within the matricies(so I can keep them all
in memory), or instead using matrix stacks, keeping track of them, an if
necessary, comiiting them to a database in case of failure somewhere or memory
problems.  How does numerical python best handle large matricies?

regards
Matt