On Sunday, 13 March 2016 at 18:42:59 UTC, Bastien wrote:
The sticking point is unless I commit the rest of my life to
maintaining this software, I can't write it all in D. The
algorithms change/are improved yearly; the output format from
the instrument changes once in a while and therefore these need
to be easily scripted/modified by other (non-programming)
scientists and the community that only really know python and
octave.
It's pretty easy to use D from python and python from D. The
documentation for PyD isn't so great, but once you have figured
it out, it's easy. Start with something very small (the examples
and tests in the PyD repo are the best documentation) and work up
from there.
You can even embed D in a Jupyter/iPython notebook, and write
some cells in D and some in python and have them call each other.
See PydMagic by John Colvin.
https://github.com/DlangScience/PydMagic
D can talk to Julia via C linkage already. Just extern(C) when
you declare your D function, and I guess use C style arrays.
I started porting julia.h to D, but didn't get have time to
finish. Ilya Yaroshenko, who created the ndslice library in
std.experimental, will be working on julia integration in coming
months.
By the way, you can also embed R in D and call D from R - see
work by bachmeier on bitbucket. That's very important because of
the huge numbers of R libraries. Although R is slow, there
apparently shouldn't be so much overhead in calling a C library
written for R from D.
I guess my resilience to using D for the algorithms is because
with python, I have access to numpy and matplotlib. There do
seem to be some ongoing developments though:
http://forum.dlang.org/post/mailman.4923.1434903477.7663.digitalmar...@puremagic.com
You already have access to matplotlib from D - see here (and
scroll down or search for matplotlib):
https://d.readthedocs.org/en/latest/examples.html
And you can call numpy from D, but there is some overhead, and I
wouldn't want to do it inside a tight loop.
From PyD unit tests:
InterpContext context = new InterpContext();
context.py_stmts(outdent("
import numpy
a = numpy.eye(2, dtype='complex128')
"));
context.a.to_d!(Complex!double[][] )();
