See this description from Jed http://scicomp.stackexchange.com/questions/3298/appropriate-space-for-weak-solutions-to-an-elliptical-pde-with-mixed-inhomogeneo/3300#3300.
In a simpler way you could just scale your diagonal entries which are 1 at the moment with a value that is out of your interest range, such that the values do not appear in the solution. On Fri, Oct 14, 2016 at 2:01 AM, Barry Smith <bsm...@mcs.anl.gov> wrote: > > I would use MatGetSubMatrix() to pull out the part of the matrix you care > about and hand that matrix off to SLEPc. > > Others prefer to remove the Dirichlet boundary value locations while doing > the finite element assembly, this way those locations never appear in the > matrix. > > The end result is the same, you have the slightly smaller matrix of > interest to compute the eigenvalues from. > > > Barry > >> On Oct 13, 2016, at 5:48 PM, Christopher Pierce <cmpie...@wpi.edu> wrote: >> >> Hello All, >> >> As there isn't a SLEPc specific list, it was recommended that I bring my >> question here. I am using SLEPc to solve a generalized eigenvalue >> problem generated as part of the Finite Element Method, but am having >> difficulty getting the diagonalizer to converge. I am worried that the >> method used to set boundary conditions in the matrix is creating the >> problem and am looking for other people's input. >> >> In order to set the boundary conditions, I find the list of IDs that >> should be zero in the resulting eigenvectors and then use >> MatZeroRowsColumns to zero the rows and columns and in the matrix A >> insert a large value such as 1E10 on each diagonal element that was >> zeroed and likewise for the B matrix except with the value 1.0. That >> way the eigenvalues resulting from those solutions are on the order of >> 1E10 and are outside of the region of interest for my problem. >> >> When I tried to diagonal the matrices I could only get converged >> solutions from the rqcg method which I have found to not scale well with >> my problem. When using any other method, the approximate error of the >> eigenpairs hovers around 1E00 and 1E01 until it reaches the max number >> of iterations. Could having so many identical eigenvalues (~1,000) in >> the spectrum be causing this to happen even if they are far outside of >> the range of interest? >> >> Thank, >> >> Chris Pierce >> WPI Center for Computation Nano-Science >> >> >
