[eigen] Generalised Eigenvector Problem using the QZ algorithm.

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I'm trying to implement the ellipse fitting algorithm from


in C++ with eigen2. The algorithm relies on being able to solve the
generalised eigenvector problem:

Ax = lambda Bx

(See: http://www.cs.utk.edu/~dongarra/etemplates/node282.html )

In my case A and B are both rank-deficient so I can't invert them.
Apparently the normal way to solve this is using the QZ algorithm,
which is apparently similar to the QR algorithm.

The LAPACK routine is (I think) DGGEV or DGGEVX (who names these things?)

Any chance anyone could port the LAPACK code (or the CLAPACK code) to
eigen? I could probably do it but I'm guessing there's someone out
there who is familiar with LAPACK's crazy naming scheme and eigen who
could do it a lot faster.

In return I have access to many journals. Papers on request. Or beer
if you live in London. :-)


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