[Numpy-discussion] performance matrix multiplication vs. matlab

[Benoit Jacob]

>> Hi,
>>
>> I while back, someone talked about aigen2(http://eigen.tuxfamily.org/). In
>> their benchmark they give info that they are competitive again mkl and goto
>> on matrix matrix product. They are not better, but that could make a good
>> default implementation for numpy when their is no blas installed. I think
>> the license would allow to include it in numpy directly.
>
>It is licensed under the LGPLv3, so it is not compatible with the numpy license.

Hi,

I'm one of Eigen's authors. Eigen is indeed LGPL3 licensed. Our intent
and understanding is that this makes Eigen usable by virtually any
software, whence my disappointment to learn that LGPL3 software can't
be used by NumPy.

Just for my information, could you tell my why NumPy can't use
LGPL3-licensed libraries?

I found this page:
http://www.scipy.org/License_Compatibility

It does say that LGPL-licensed code can't be added to NumPy, but
there's a big difference between adding LGPL code directly into NumPy,
and just letting NumPy _use_ LGPL code. 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?

FYI, several BSD-licensed projects are using Eigen ;)

Thanks for your consideration
Benoit