Which D features to emphasize for academic review article
dsimcha
dsimcha at yahoo.com
Sun Aug 12 10:22:20 PDT 2012
On Sunday, 12 August 2012 at 03:30:24 UTC, bearophile wrote:
> Andrei Alexandrescu:
>
>> - The language's superior modeling power and level of control
>> comes at an increase in complexity compared to languages such
>> as e.g. Python. So the statistician would need a larger
>> upfront investment in order to reap the associated benefits.
>
> Statistician often use the R language
> (http://en.wikipedia.org/wiki/R_language ).
> Python contains much more "computer science" and CS complexity
> compared to R. Not just advanced stuff like coroutines,
> metaclasses, decorators, Abstract Base Classes, operator
> overloading, and so on, but even simpler things, like
> generators, standard library collections like heaps and deques,
> and so on.
> For some statisticians I've seen, even several parts of Python
> are too much hard to use or understand. I have rewritten
> several of their Python scripts.
>
> Bye,
> bearophile
For people with more advanced CS/programming knowledge, though,
this is an advantage of D. I find Matlab and R incredibly
frustrating to use for anything but very standard
matrix/statistics computations on data that's already structured
the way I like it. This is mostly because the standard CS
concepts you mention are at best awkward and at worst impossible
to express and, being aware of them, I naturally want to take
advantage of them.
Using Matlab or R feels like being forced to program with half
the tools in my toolbox either missing or awkwardly misshapen, so
I avoid it whenever practical. (Actually, languages like C and
Java that don't have much modeling power feel the same way to me
now that I've primarily used D and to a lesser extent Python for
the past few years. Ironically, these are the languages that are
easy to integrate with R and Matlab respectively. Do most
serious programmers who work in problem domains relevant to
Matlab and R feel this way or is it just me?). This was my
motivation for writing Dstats and mentoring Cristi's fork of
SciD. D's modeling power is so outstanding that I was able to
replace R and Matlab for a lot of use cases with plain old
libraries written in D.
More information about the Digitalmars-d
mailing list