Re: [ANN] An impudent introduction to Guile

[Cao Jin <lop@null.net>]

[-- Attachment #1: Type: text/plain, Size: 2988 bytes --]

Hi Panicz,

Thank you for these information.

On 2/6/2016 14:08, Panicz Maciej Godek wrote:
> Hi
>
> 2016-02-06 1:47 GMT+01:00 Cao Jin <lop@null.net <mailto:lop@null.net>>:
>
>     It's interesting. I have used Matlab for many years, but never
>     tried R. As for as I know, there are tons of state-of-the-art
>     library in R and Matlab.
>
>     After skimming your paper, I wander that
>     1) Are these library used in your code example implemented by
>     yourself? Or other libraries are called, such as LAPACK for linear
>     algebra?
>
>
> Everything is either written from scratch, or uses one of the helper
> libraries (two such libraries are included in the repo; the other is
> SRFI-1).
> The point of the book is that it is not a tutorial on using libraries,
> but it explains some methods and translates these explanations to
> Scheme, so that they can be modified and extended easily.
>  
> If you are looking  for some serious numerical libraries for Scheme,
> there's a very powerful scmutils package available
>
> http://www.cs.rochester.edu/~gildea/guile-scmutils/
> <http://www.cs.rochester.edu/%7Egildea/guile-scmutils/>
>
> I've actually used its code for Singular Value Decomposition to
> perform Principal Component Analysis.
OK, I will try it later.
>
>     2) Is it easy to use scheme and your library, or maybe some
>     others, to do computational job? In practice, those who use R or
>     Matlab want their idea to be proved quickly, not to spend time on
>     coding style, right?
>
> I think it depends on a point of view. I initially tried using R, but
> it was causing many unexpected problems, but I already knew Scheme
> quite well, and for me even implementing the libraries from scratch
> wasn't that much of  a job.
> But the book is mostly about fun, and about understanding.
> Also, interfacing Guile with Emacs through Geiser is an incredible
> productivity boost.
>
> Interestingly, when I benchmarked the genetic algorithm that I wrote
> with genalg package from R, the Scheme version run in Guile actually
> outperformed the R version, although it was written in completely
> performance-naive style.
>
It's great to see this result.

> On the other hand, if you wanted to use the decision trees classifier,
> you'd probably want to apply memoization.
>
>     If scheme can do most computational job as python numpy does, I
>     will switch to it.
>
>
> I think that in practice Scheme can be even more convinient, as it
> provides native support for complex numbers
>
> I also think it would be helpful to interface Guile with plot
> generation. I see that Nala has a guile-plot package, but I haven't
> tried it. I personally wrote some code for generating LaTeX pgfplots
> for the project, and can add it to the repo if you llike.
>

As described above, I think it is worth trying Scheme for numerical
computing. Your work is appreciated!

Regards,
Lop


[-- Attachment #2: Type: text/html, Size: 6286 bytes --]