
Diagonal Eigenproblem, n=20

RQCG reset parameter = 10

EPS Object: 1 MPI processes
  type: rqcg
    reset every 10 iterations
  problem type: hermitian eigenvalue problem
  extraction type: harmonic Ritz
  selected portion of the spectrum: closest to target: 4.8 (in magnitude)
  postprocessing eigenvectors with purification
  number of eigenvalues (nev): 4
  number of column vectors (ncv): 0
  maximum dimension of projected problem (mpd): 0
  maximum number of iterations: 0
  convergence test: relative to the eigenvalue and matrix norms
  computed matrix norms: norm(A)=0.
BV Object: 1 MPI processes
  type: svec
  0 columns of global length -1
  vector orthogonalization method: classical Gram-Schmidt
  orthogonalization refinement: if needed (eta: 0.7071)
  block orthogonalization method: GS
  doing matmult as a single matrix-matrix product
DS Object: 1 MPI processes
  type: nhep
ST Object: 1 MPI processes
  type: precond
  shift: 0.
  number of matrices: 1
  KSP Object: (st_) 1 MPI processes
    type: gmres
      restart=30, using Classical (unmodified) Gram-Schmidt Orthogonalization with no iterative refinement
    maximum iterations=5, initial guess is zero
    left preconditioning
    using DEFAULT norm type for convergence test
  PC Object: (st_) 1 MPI processes
    type: jacobi
    PC has not been set up so information may be incomplete
EPS Object: 1 MPI processes
  type: gd
    search subspace is orthogonalized
    block size=1
    type of the initial subspace: non-Krylov
    size of the subspace after restarting: 6
    number of vectors after restarting from the previous iteration: 1
  problem type: hermitian eigenvalue problem
  extraction type: harmonic Ritz
  selected portion of the spectrum: closest to target: 4.8 (in magnitude)
  number of eigenvalues (nev): 4
  number of column vectors (ncv): 20
  maximum dimension of projected problem (mpd): 20
  maximum number of iterations: 2000
  convergence test: relative to the eigenvalue and matrix norms
  computed matrix norms: norm(A)=20.
BV Object: 1 MPI processes
  type: svec
  20 columns of global length 20
  vector orthogonalization method: classical Gram-Schmidt
  orthogonalization refinement: if needed (eta: 0.7071)
  block orthogonalization method: GS
  doing matmult as a single matrix-matrix product
DS Object: 1 MPI processes
  type: gnhep
ST Object: 1 MPI processes
  type: precond
  shift: 4.8
  number of matrices: 1
  KSP Object: (st_) 1 MPI processes
    type: preonly
    maximum iterations=5, initial guess is zero
    left preconditioning
    using DEFAULT norm type for convergence test
  PC Object: (st_) 1 MPI processes
    type: jacobi
    linear system matrix = precond matrix:
    Mat Object: 1 MPI processes
      type: seqaij
      rows=20, cols=20
      total: nonzeros=20, allocated nonzeros=20
      total number of mallocs used during MatSetValues calls =0
        not using I-node routines
     5.00000, 4.00000, 6.00000, 3.00000

