Hi Anders,
I guess I'm just looking for a quick fix right now. I may get the urge to
implement it later when I have more time though, so thanks for the
information.
I'm working with around 1000x1000 matrices. They could be bigger. I have the
time to wait for the right answer. LAPACK and MTJ and others (Jama, JMSL,
etc) are quick, but don't give me satistfactory answers with very large
numbers for some reason. Maybe there is some tolerance or epsilon parameter
somewhere that will help the convergence (if I only knew where to look).
Anyway, I haven't found a BigDecimal eigenvalue solver implementation out
there yet. Maybe they don't exist?
Well, thanks for your kindness. It looks like you have the best start towards
this functionality in Java.
Kind regards,
Jake
On Saturday 27 January 2007 20:45, Anders Peterson wrote:
> As you've noticed ojAlgo does not contain a BigDecimal implementation
> of Eigenvalue or SingularValue. You'll have to build it yourself...
>
> If you look at PrimitiveEigenvalue you'll "see" the algorithm, and
> then study ArbitraryQR and ArbitraryLU for examples on how to use
> PhysicalStore to develop an implementation that works with any Number
> type. I've been planning to move (some of) the Householder code from
> ArbitraryQR to PhysicalStore or some utility class. That would
> probably be useful for you.
>
> What size matrices are you working with? If they are large a
> BigDecimal implementation will be very slow.
>
> /Anders
>
> On 27 jan 2007, at 19.11, jac...@gm... wrote:
> > Hi,
> >
> > I'm trying to figure out how/if I can do a BigDecimal EVD with
> > ojAlgo. I
> > would like all operations to be done with BigDecimal, so I can
> > avoid rounding
> > errors.
> >
> > Do all of the classes that implement the Eigenvalue interface round
> > down to
> > doubles?
> >
> > If so, is my only choice the BigQR, and then read off diagonal of R?
> >
> > Many thanks for any help!
> >
> > Jacob Martin
> > -------------------------------------------------
> > BasicMatrix tmpMatrix = BigMatrix.FACTORY.make(M);
> > Eigenvalue tmpDecomposition = new PrimitiveEigenvalue();
> > tmpDecomposition.compute(tmpMatrix);
> > BasicArray ba =tmpDecomposition.getEigenvalues();
> >
> >
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