On Wednesday, March 9, 2011, kcrisman <[email protected]> wrote:
> Before the review, a tidbit from "97 Things Every Programmer Should
> Know" - #93, I think (page 186-7):
>
> Write Code As If you Had to Support It for the Rest of Your Life
>
> Now to our main story.
>
> I love the new books section of any academic library. Today, I
> checked out the interesting-sounding "Data Analysis with Open Source
> Tools" by Philipp Janert. I hoped to find Numpy or R covered, but the
> catalog entry was pretty terse, so I had to actually walk over to find
> out.
>
> Well, this is quite a book - I'll spare the superlatives or gripes
> (though I'll note that the bibliography of each section, where it
> intersects with my own knowledge of what is excellent, is right on,
> though at a high level at all times). If you have access to it
> (Google Books?), check out the 'Workshop' sections toward the end of
> most chapters. There are mini-case study intros to the following Sage
> components:
>
> NumPy
> matplotlib
> scipy.signal
> gnuplot (I think it's in Sage?)
Gnuplot is not in sage. The license is GPL incompatible.
> GSL
> Sage
> R
> SQLite
>
> as well as a few other tools, several Python libraries.
>
> I note that Sage is in fact one of the programs listed (see pages
> 184-188), primarily for its calculus and symbolic linear algebra
> abilities. It is far too long for me to type in here, but I think it
> would be interesting in the light of the "+100 FAIL points" thread for
> those with access to read his thoughts on Sage.
>
> Highlights are an amusing example:
>
> var('a,b,c')
> M = matrix([[a,b,a],[b,c,b],[a,b,0]])
> M.eigenvalues()
> <snip huge result>
>
> and a somewhat harsh critique of the 500 MB unpacking to 2 GB and a
> "heavy-handed and ultimately unsustainable" solution as being the big
> umbrella, though he "sincerely appreciates the straightforward
> pragmatism of this solution". I think he is looking at it too much
> from the point of view of the book's title; of course, the right tool
> for the right solution; Sage has a different goal.
>
> The author is in fact pretty positive about these tools in general,
> including Sage - otherwise why write a 500 page book, weighty even by
> O'Reilly standards? - but even in Appendix A, where he discusses
> various tools like Matlab, R, the Enthought suite, can't seem to
> really be happy about any of the options.
>
> So worth knowing about, especially from the point of view of what it
> is that quants need from software, and that some people will be
> introduced to Sage for the first time from this reference.
>
> - kcrisman
>
> --
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--
William Stein
Professor of Mathematics
University of Washington
http://wstein.org
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