Numerical Linear Algebra in arbitrary precision
robert.kern at gmail.com
Fri Feb 17 05:26:56 EST 2012
On 2/17/12 6:09 AM, Tim Roberts wrote:
> 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.
> It is been my experience that numpy is the best place to start with
> requests like this, although I don't know whether it will actually solve
> your specific tasks:
This will not do arbitrary-precision, though. We use the double- and
single-precision routines from LAPACK.
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it as though it had
an underlying truth."
-- Umberto Eco
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