[Numpy-discussion] Which dtype are supported by numexpr ?
Francesc Altet
faltet@carabos....
Wed Mar 14 07:02:10 CDT 2007
A Divendres 09 Març 2007 18:56, Francesc Altet escrigué:
> A Divendres 09 Març 2007 18:40, Sebastian Haase escrigué:
> > Which dtypes are supported by numexpr ?
>
> Well, numexpr does support any dtype that is homogeneous, except 'uint64'.
> This is because internally all the unsigned types are upcasted to the
> smallest *signed* integer that can fit the info for it. As it happens
> that 'uint64' doesn't have a standard signed type above that is able to
> keep its info: this is why it is unsupported.
>
> Besides, there is the limitation that Win32 doesn't have such a 'uint64',
> and computations in numpy or python are normally done by converting them to
> python long integers (correct me if I'm wrong here), whose arithmetic is
> very slow compared with the types supported by the compiler. So, the best
> approach is to avoid 'uint64' types in general.
The info above is somewhat inexact. I was talking about the enhanced numexpr
version included in PyTables 2.0 (see [1]). The original version of numexpr
(see [2]) doesn't have support for int64 on 32-bit platforms and also neither
does for strings. Sorry for the confusion.
[1] http://www.pytables.org/trac/browser/trunk/tables/numexpr
[2] http://projects.scipy.org/scipy/scipy/browser/trunk/Lib/sandbox/numexpr
> > We are very interested in numexpr !
> > Where is the latest / most-up-to-date documentation ?
>
> At the moment, I think documentation is reduced at some docstrings. If you
> want more, you will have to look at the sources.
Ups, I spoke too fast. David Cooke kindly added this page:
http://www.scipy.org/SciPyPackages/NumExpr
Actually, numexpr doesn't need many more info that this as it is pretty
straighforward to use already.
Cheers,
--
>0,0< Francesc Altet http://www.carabos.com/
V V Cárabos Coop. V. Enjoy Data
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