Numerical Linear Algebra in arbitrary precision

[Albert van der Horst]

In article <e6ca88fb-3fc7-47b6-b2f5-3c7ee8b65eec at tc8g2000pbc.googlegroups.com>,
Ken  <ken.allen at sbcglobal.net> wrote:
>Brand new Python user and a bit overwhelmed with the variety of
>packages available.  Any recommendation for performing numerical
>linear algebra (specifically least squares and generalized least
>squares using QR or SVD) in arbitrary precision?  I've been looking at
>mpmath but can't seem to find much info on built in functions except
>for LU decomposition/solve.

Arbitrary precision? As in automatically increasing precision to
stay exact? You will find this impractical as the number of decimals
will explode, or you will find it not at all.

If you mean that you want to be able to select something with larger
precision than single or double floats, numpy is the starting point.

>
>Appreciate any comments.
>
>Ken

Groetjes Albert

--
-- 
Albert van der Horst, UTRECHT,THE NETHERLANDS
Economic growth -- being exponential -- ultimately falters.
albert at spe&ar&c.xs4all.nl &=n http://home.hccnet.nl/a.w.m.van.der.horst