SciD: the humble beginning

[Lars T. Kyllingstad]

dsimcha wrote:
> We've got the beginnings of a good matrix/numerics lib in your work.  I believe
> that my dstats lib would provide just about all the statistical functionality a
> good scientific lib would need, and I'm getting close to declaring it
> beta-quality.  I'd say based on a quick look at what scipy has that we also need
> the following for a credible full-fledged scientific lib:

dstats has actually been kind of an inspiration for me. I've never used 
it, because I don't do any statistics, but I've looked through the API 
docs and the examples, and I really like the interface.


> Machine learning, i.e. classification and clustering.  (I'd probably be qualified
> to write that and was halfway thinking of breaking ground on it over Christmas
> break.  However, I'm not committing to this yet, so if someone else already has a
> work in progress, let me know.  Also, there's a Java machine learning library
> called Weka that I've used before.  It's very complete but the API is painful and
> it's GPL, so IDK if it'd be worth it to port to D.)
> 
> Optimization.  (A few people have tried but IDK if they've actually gotten far off
> the ground with it.)
> 
> Basic image I/O and processing.
> 
> Plotting.  I've considered doing this a few times, but I've decided it needs to be
> put off until D2 is stable and the GUI toolkits for it are reasonably stable.  One
> layer of instability (D2 itself) is workable, but two layers (D2 and the GUI libs)
> is not.

A few things that can be added to the list:

- special functions
- Fourier transforms
- Monte Carlo methods
- series
- least-squares fitting
- differential and integral equations

There is a good chance that I will need the latter for work just after 
the holidays, in which case I'll write it myself.

I'll add the above lists to the project home page.

-Lars