[SciPy-dev] Ticket #709 (was: Re: Next scipy release 0.7)
Tue Sep 30 14:21:38 CDT 2008
On Tue, 30 Sep 2008 18:36:12 +0000 (UTC)
Pauli Virtanen <firstname.lastname@example.org> wrote:
> Tue, 30 Sep 2008 19:56:58 +0200, Nils Wagner wrote:
>> should be resolved, too.
> Short summary about this one: it's about a special
>matrix pair for which
> LAPACK's generalized eigenvalue problem solver DGGEV
> output, losing one eigenvalue from a complex eigenpair.
> problem should nonetheless be well-defined, AFAIK, this
>looks like a bug
> in LAPACK.)
In that case the LAPACK developers should be informed as
soon as possible. Did you check a FORTRAN implementation
of the test case ?
Can someone run the test (2dof.py) in Matlab, Octave,
> The question here is what we should/can do:
> 1. Raise LinAlgError if we detect this condition.
> 2. Try to repair the returned data by filling in the
>other eigenvalue of
> the pair, as we know all complex eigenvalues come in
Well, this holds for real matrices but what could be done
in case of complex matrices ?
> 3. Try to return as much as we can make sense of, but
>put NaN in place of
> the missing eigenvalue.
> Instead of expected complex eigenvalue pair (a_R +- i
> LAPACK routine instead returns the values
> a_R = whatever
> a_I = [0., -2.18645248e-16j]
> beta = [0., 7.95804395e-17]
> The correct result would have been something like
> a_R = whatever
> a_I = [+2.18645248e-16j, -2.18645248e-16j]
> beta = [7.95804395e-17, 7.95804395e-17]
> but one eigenvalue of the pair was lost, apparently due
>to rounding etc.
> Eigenvector data corresponding to zeros in a_I are
> differently than for positive entries, so the zero in
>the wrong place
> messed up the Scipy routine. We could detect this and
>raise an error (1),
> substitute in the missing eigenvalue based on the
> one (2), or leave the missing eigenvalue as corrupted
>and return only the
> correct one (3).
> Pauli Virtanen
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