On 2/17/12 6:09 AM, Tim Roberts wrote:
Ken<ken.al...@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:
http://docs.scipy.org/doc/numpy/reference/routines.linalg.html
This will not do arbitrary-precision, though. We use the double- and
single-precision routines from LAPACK.
--
Robert Kern
"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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