On Monday, 9 November 2015 at 19:31:14 UTC, Márcio Martins wrote:
I have been running some MCMC simulations in Python and it's
hard to cope with how unbelievably slow it is.
Takes me almost a minute to run a few hundred thousand samples
on my laptop whereas I can run the same simulation with a
million samples in under 100ms, on my phone with JavaScript on
a browser.
Then, you spend a minute waiting for the simulation to finish,
to find out you had an error in your report code that would
have been easily caught with static typing. So annoying...
Is anyone doing similar stuff with D? Unfortunately, I couldn't
find any plotting libraries nor MATLAB-like numerical/stats
libs in dub.
dlangscience has some energy and people behind it. John Colvin
is heavily involved with it, but it's a joint project, and there
are others too. He wrote a draft white paper really thinking
through the best design approach, and that will pay dividends
over time, but in the meantime it's a central point for different
scientific computing libraries.
plotting is a work in progress, I think. there are some options.
for my stuff, it's not particularly clever so I use the D
bindings to mathgl (a nice and simple C library), but depending
on what you want to do, other choices may be more suitable.
it's pretty easy to call python libraries from D, and I have done
that initially for plotting using bokeh. the only problem was
for callbacks that then meant potentially dealing with javascript
as well, and I drew the line at three languages for such a simple
thing.
This seems like another area where D could easily pick up
momentum with RDMD and perhaps an integration with Jupyter
which is becoming very very popular.
Actually John Colvin has written an extension called pydmagic
that allows you to write D code within a Jupyter notebook - it
integrates with PyD so you can call D from python and call python
from D (even embedded as a string if you like). It's not yet
highly-polished, but it works, and I have used it to get work
done.
