matt at virtualspectator.com
Sat Sep 30 00:51:54 CEST 2000
Thanks, that's nice to know.
On Sat, 30 Sep 2000, Travis Oliphant wrote:
> > 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?
> Numerical Python uses references to matrix regions, so you could store all
> of your matrices into one big 3-D array and use indexing to access the
> "slice" of interest.
> The thing to watch out for with large matrices is "slient upcasting" from
> single precision to double precision because python scalars are
> interpreted as double precision objects.
> Copying large chunks of data (especially if it means swapping to disk)
> will slow you down. If you steer clear of such things, Numeric Python
> is very fast.
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