[Arpack-ng] Getting best possible solution after fixed iterations Classic List Threaded 1 message  Hi! In my use case, I don't need the exact solutions of an eigenproblem, I just need ARPACK to give me the N lowest (real part) vectors it can find after no more than X iterations --- that is, if it finds all N eigenvectors to the specified tolerance in less than X iterations then great, but if it doesn't then I still want it to give me the N lowest vectors it found even if they aren't fully converged. (The background is that I have an iterative optimization algorithm, so to make a long story short I just need a cheaply obtainable improved solution to input to the next step of the iteration, not a perfect solution, and since the optimization problem is expressed in terms of a Rayleigh quotient something like the Arnoldi iteration should do a good job of finding such a solution;  in fact, I have good experience using ARPACK in the past but I am now working with matrices that it is struggling with.) The documentation says that after X iterations have passed it gives you all of the eigenvectors that have converged, which is not what I want as I want *all* N vectors even if they haven't converged.  So my question is:  when the docs say that it only gives you the eigenvectors that converged, does it mean that it does a transformation which got rid of the rest and so they are inaccessible?  Or does it mean that if I, say, override the number of converged eigenvectors and set it to the number that I want before calling the routine that extracts the eigenvectors, then I can get the full set?  Put another way, if I replace the number of converged eigenvectors with the number I want, then will this result in garbage, or will it give me what I am looking for? Thanks a lot in advance! Greg _______________________________________________ Arpack-ng mailing list [hidden email] http://lists.scilab.org/mailman/listinfo/arpack-ng