On Wednesday, 14 March 2018 at 20:21:15 UTC, Sam Potter wrote:
Sure. The key word in my statement was "ideally". :-)
For what it's worth, there is already an "informal spec" in the
form of the high-level interface for numerical linear algebra
and sci. comp. that has been developed (over three decades?) in
MATLAB. This spec has been replicated (more or less) in Julia,
Python, Octave, Armadillo/Eigen, and others. I'm not aware of
all the subtleties involved in incorporating it into any
standard library, let alone D's, but maybe this is an
interesting place where D could get an edge over other
competing languages. Considering that people in Python land
have picked up D as a "faster Python", there might be more
traction here than is readily apparent
[snip]
libmir [1] originally started as std.experiemental.ndslice (that
component is now mir-algorithm). They had removed it from the
std.experimental because it wasn't stable enough yet and needed
to make breaking changes. I think it's doing just fine as a
standalone library, rather than part of the standard library. As
this thread makes clear, there's certainly more work to be done
on it, but I'm sure Ilya would appreciate any feedback or
assistance.
I'm sympathetic to your point about D getting an edge by having a
better linear algebra experience. I came to D for faster
Python/R/Matlab (and not C++), though if I need to do something
quickly, I still defer to Python/R. However, if you look at the
TIOBE index, R and Matlab are at 18/20. Python is quite a bit
higher, but it's growth in popularity was not largely due to the
Numpy/Scipy ecosystem. So while I think that D could get more
traction if libmir turns itself into a premiere linear algebra
library, we should be realistic that linear algebra is a
relatively small segment of how people use programming languages.
Maybe these firms might be willing to pay up for more support
though...(if a user could replace pandas with libmir, I would
imagine some financial firms might be interested).
[1] https://github.com/libmir
