On Wed, Jul 20, 2011 at 5:52 PM, srean <srean.l...@gmail.com> wrote:
> >> I think this is essential to speed up numpy. Maybe numexpr could handle
> this in the future? Right now the general use of numexpr is result =
> numexpr.evaluate("whatever"), so the same problem seems to be there.
> >>
> >> With this I am not saying that numpy is not worth it, just that for many
> applications (specially with huge matrices/arrays), pre-allocation does make
> a huge difference, especially if we want to attract more people to using
> numpy.
> >
> > The ufuncs and many scipy functions take a "out" parameter where you
> > can specify a pre-allocated array. It can be a little awkward writing
> > expressions that way, but the capability is there.
>
> This is a slight digression: is there a way to have a out parameter
> like semantics with numexpr. I have always used it as
>
> a[:] = numexpr(expression)
>
> But I dont think numexpr builds the value in place. Is it possible to
> have side-effects with numexpr as opposed to obtaining values, for
> example
>
> "a= a * b + c"
>
> The documentation is not clear about this. Oh and I do not find the
> "out" parameter awkward at all. Its very handy. Furthermore, if I may,
> here is a request that the Blitz++ source be updated. Seems like there
> is a lot of activity on the Blitz++ repository and weave is very handy
> too and can be used as easily as numexpr.
>
In order to make sure the 1.6 nditer supports multithreading, I adapted
numexpr to use it. The branch which does this is here:
http://code.google.com/p/numexpr/source/browse/#svn%2Fbranches%2Fnewiter
This supports out, order, and casting parameters, visible here:
http://code.google.com/p/numexpr/source/browse/branches/newiter/numexpr/necompiler.py#615
It's pretty much ready to go, just needs someone to do the release
management.
-Mark
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