Scientific computing in D

[jmh530 via Digitalmars-d]

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...

No matter how interested I am in Bayesian statistics, I would 
think that an MCMC library is relatively lower in importance than 
a number of other libraries.

I've written some Gibbs samplers in Matlab and Python. They are 
quite slow in those languages, but I didn't notice that the 
Python code was more than 2X or so slower than the Matlab code, 
and I believe that was almost entirely due to Matlab using Intel 
MKL and Numpy using a slightly less efficient implementation.

While I learned a lot about MCMC by writing my own Gibbs 
samplers, I don't write them much anymore. I make more use of MC 
Stan, which can be called from Python with PyStan (maybe easier 
if you're on Linux than Windows, I tend to use rstan more which 
works easily with Windows). PyMC is another option that I've 
heard good things about, but I haven't tried it.

I think the simplest way forward would be something like wrappers 
to functionality in other languages. With PyD, it shouldn't be 
inconceivable to have a wrapper to PyMC. Alternately, MC Stan is 
written in C++ and has interfaces to a number of languages. Being 
able to call Stan from D would be cool, especially since I don't 
even think there's a C++ interface yet (you have to use the 
command line or R or whatever). I have essentially no idea how to 
do that.

> Is anyone doing similar stuff with D? Unfortunately, I couldn't 
> find any plotting libraries nor MATLAB-like numerical/stats 
> libs in dub.

My attitude is the more the better.

> 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.

That would be interesting, but I'm not sure how high a priority 
it is.