Oct. 29, 2014
10:24 a.m.
On 29 October 2014 10:48, Eelco Hoogendoorn <hoogendoorn.eelco@gmail.com> wrote:
My point isn't about speed; its about the scope of numpy. typing np.fft.fft isn't more or less convenient than using some other symbol from the scientific python stack.
The problem is in distribution. For many users, installing a new library is not easy (computing cluster, company regulations...). And this assuming the alternative library is held to the same quality standards as Numpy. Another argument is that this should only be living in Scipy, that is, after all, quite standard; but it requires a FORTRAN compiler, that is quite a big dependency. /David.