[eigen] [Sparse][LU] scale factors

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I'm using SuperLU and UmfPack backends for Sparse matrix LU decompositions. Those backends expose the P and Q permutations, but not the scaling factors (I believe that SuperLU backend gets them but does not give access[0], while UmfPack backend does not read the scaling factors [1], for UmfPack, one would also need acces to the do_recip flag).

Are there some strong reasons not to provide those access ?

Best regards,


PS: Is there a "nice" way to convert the permutations vectors to sparse matrices such that P* and *Q do the permutation ? I'm well aware that this would not be the proper way to perform those permutations, but I need thoses sparse matrices anyway , and my current code reading the values in the vectors and setting the 1. by hand in the sparse matrix feels ugly.

PS2: I saw that Scipy patched SuperLU [2], and while I'm against embedding libraries, those patches seem serious ☹

[0] https://bitbucket.org/eigen/eigen/src/tip/unsupported/Eigen/src/SparseExtra/SuperLUSupport.h#cl-370 [1] https://bitbucket.org/eigen/eigen/src/10990f843213/unsupported/Eigen/src/SparseExtra/UmfPackSupport.h#cl-306 [2] http://projects.scipy.org/scipy/log/trunk/scipy/sparse/linalg/dsolve/SuperLU/SRC?rev=6355

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