[SciPy-dev] Ticket #709 (was: Re: Next scipy release 0.7)
Tue Sep 30 13:36:12 CDT 2008
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 returns bogus
output, losing one eigenvalue from a complex eigenpair. (The eigenvalue
problem should nonetheless be well-defined, AFAIK, this looks like a bug
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 pairs.
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 a_I)/beta, the
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 interpreted
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 correctly calculated
one (2), or leave the missing eigenvalue as corrupted and return only the
correct one (3).
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