On Tue, 10 Jan 2006, Morten Welinder apparently wrote:
> The problem with picking a random open (or closed,
> reallyl) software product for numerical work and using it
> is that you need to figure out if it is any good.
I was not suggesting a random choice. Just that a choice be
made that provides a good range of functionality along with
ease of use. Taking advantage of Gnumeric's existing work
on Python scripting made numpy look pretty interesting.
> A quick look at numpy suggests that the numerical quality is questionable.
> Take for example
> static double atanh(double x)
> {
> return 0.5*log((1.0+x)/(1.0-x));
> }
> This clearly has 100% loss of precision for small x.
> (Luckily this function is only used if libc fails to
> supply atanh.)
This is a classic "naive" implementation, which
unfortunately can be found in open and commercial software.
If your claim is true, it could affect Windows users.
But where are you finding this: are you sure the current
numpy supplies atanh separately from an available math
library (possibly not necessarily libc)? I see the
following::
Python 2.4.1 (#65, Mar 30 2005, 09:13:57) [MSC v.1310 32
bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from numpy import *
>>> help(atanh)
Traceback (most recent call last):
File "<stdin>", line 1, in ?
NameError: name 'atanh' is not defined
Cheers,
Alan Isaac
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