[Numpy-discussion] performance matrix multiplication vs. matlab
Sun Jan 17 11:36:53 CST 2010
On Sun, Jan 17, 2010 at 08:52, Benoit Jacob <firstname.lastname@example.org> wrote:
> 2010/1/17 David Cournapeau <email@example.com>:
>> 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.
> But the LGPL doesn't impose restrictions on the usage of binaries, so
> how does it matter? The LGPL and the BSD licenses are similar as far
> as the binaries are concerned (unless perhaps one starts disassembling
> The big difference between LGPL and BSD is at the level of source
> code, not binary code: one modifies LGPL-based source code and
> distributes a binary form of it, then one has to release the modified
> source code as well.
This is not true. Binaries that contain LGPLed code must be able to be
relinked with a modified version of the LGPLed component. This is
technically non-trivial. In addition, binaries containing an LGPLed
component must still come with the source of the LGPLed component (or
come with a written offer to distribute via the same mechanism ...
yada yada yada). These are non-trivial restrictions above and beyond
the BSD license that we, as a matter of policy, do not wish to impose
on numpy users.
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
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