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| From | Robert Kern <robert.kern@gmail.com> |
| Subject | Re: Numerical Linear Algebra in arbitrary precision |
| Date | Fri, 17 Feb 2012 10:26:56 +0000 |
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On 2/17/12 6:09 AM, Tim Roberts wrote: > Ken<ken.allen@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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Numerical Linear Algebra in arbitrary precision Ken <ken.allen@sbcglobal.net> - 2012-02-15 13:02 -0800
Re: Numerical Linear Algebra in arbitrary precision Tim Roberts <timr@probo.com> - 2012-02-16 22:09 -0800
Re: Numerical Linear Algebra in arbitrary precision Robert Kern <robert.kern@gmail.com> - 2012-02-17 10:26 +0000
Re: Numerical Linear Algebra in arbitrary precision Albert van der Horst <albert@spenarnc.xs4all.nl> - 2012-02-27 10:24 +0000
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