[Numpy-discussion] performance matrix multiplication vs. matlab

[David Cournapeau]

On Sun, Jan 17, 2010 at 2:20 PM, Benoit Jacob <jacob.benoit.1 at gmail.com> wrote:

> Couldn't you simply:
>  - either add LGPL-licensed code to a third_party subdirectory not
> subject to the NumPy license, and just use it? This is common
> practice, see e.g. how Qt puts a copy of WebKit in a third_party
> subdirectory.
>  - or use LGPL-licensed code as an external dependency?

There are several issues with eigen2 for NumPy usage:
 - using it as a default implementation does not make much sense IMHO,
as it would make distributed binaries non 100 % BSD.
 - to my knowledge, eigen2 does not have a BLAS API, so we would have
to write specific wrappers for eigen2, which is undesirable.
 - eigen2 is C++, and it is a stated goal to make numpy depend only on
a C compiler (it may optionally uses fortran to link against
blas/lapack, though).

As I see it, people would be able to easily use eigen2 if there was a
BLAS API for it. We still would not distribute binaries built with
eigen2, but it means people who don't care about using GPL code could
use it.

Independently of NumPy, I think a BLAS API for eigen2 would be very
beneficial for eigen2 if you care about the numerical scientific
community.

David