I have to agree with you on most counts that Numerical Recipes in C
is not a full-blown encyclopedia on all subtleties of doing numerical
computations.
However it does its job greatly for a big class of stuff I am
interested in: minimization, non-linear system of equations solving
(The newton routine given there is good, accurate and fast.)
There are errors and problems as in most other numerical books. In
truth, I don't think there is anything fully correct out there.
When trying to make computations you have to do a lot of testing and
a lot of thought even if the algorithm seems perfect. That applies to
all books, recipes et al.
I have just discovered that tan(pi/2) = 1.63317787284e+16 in
numerical python. And we all know this is bad. It should be infinity
period. We should define a symbol called infinity and put the correct
definition of tan, sin .... for all known angles then interpolate if
needed for the rest, or whatever is used to actually compute those things.
Peace
>>>>>>>>>>>>>>>>>> Original Message <<<<<<<<<<<<<<<<<<
On 3/1/00, 12:49:23 PM, "Zow" Terry Brugger <zo...@pe...> wrote
regarding [Gmath-devel] Re: [Numpy-discussion] Derivatives:
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> > Whenever I see somebody implementing code based on "Numerical
Recipies", I
> > feel obligated to send them the following link:
> >
> > http://math.jpl.nasa.gov/nr/nr.html
> >
> Funny - that's the first thing I thought of too (just looking at it
> yesterday). Don't neglect to look at "the NR response" link buried at
the very
> bottom of the page.
> > YMMV, as always . . .
> >
> More precisely, I think the point is that yourself or some other
person so
> qualified should review any algorithm provided by a third party to
ensure
> applicability to your problem domain.
> > Kevin Rodgers
> "Zow" Terry Brugger
> zo...@ac...
> zo...@ll...
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