0 SNES Function norm 95.2794
    1 SNES Function norm 11.2562
      0 SNES Function norm 6.68972
      1 SNES Function norm 1.27466
      2 SNES Function norm 0.079264
      3 SNES Function norm 0.000353131
      4 SNES Function norm 7.07495e-09
    1 SNES Function norm 1.52162
  1 SNES Function norm 1.52162
    1 SNES Function norm 0.785084
      0 SNES Function norm 0.643439
      1 SNES Function norm 0.0233763
      2 SNES Function norm 3.2067e-05
      3 SNES Function norm 6.041e-11
    1 SNES Function norm 0.170971
  2 SNES Function norm 0.170971
    1 SNES Function norm 0.0601088
      0 SNES Function norm 0.0465713
      1 SNES Function norm 0.000125247
      2 SNES Function norm 9.069e-10
      3 SNES Function norm < 1.e-11
    1 SNES Function norm 0.00964638
  3 SNES Function norm 0.00964638
    1 SNES Function norm 0.00427687
      0 SNES Function norm 0.00402538
      1 SNES Function norm 9.35825e-07
      2 SNES Function norm < 1.e-11
    1 SNES Function norm 0.00100069
  4 SNES Function norm 0.00100069
    1 SNES Function norm 0.000502492
      0 SNES Function norm 0.000461856
      1 SNES Function norm 1.23187e-08
      2 SNES Function norm < 1.e-11
    1 SNES Function norm 0.000113958
  5 SNES Function norm 0.000113958
    1 SNES Function norm 5.42902e-05
      0 SNES Function norm 4.86028e-05
      1 SNES Function norm 1.364e-10
      2 SNES Function norm < 1.e-11
    1 SNES Function norm 1.16564e-05
  6 SNES Function norm 1.16564e-05
    1 SNES Function norm 5.44297e-06
      0 SNES Function norm 4.84838e-06
      1 SNES Function norm < 1.e-11
      2 SNES Function norm < 1.e-11
    1 SNES Function norm 1.15586e-06
  7 SNES Function norm 1.15586e-06
    1 SNES Function norm 5.35218e-07
      0 SNES Function norm 4.76451e-07
      1 SNES Function norm < 1.e-11
      2 SNES Function norm < 1.e-11
    1 SNES Function norm 1.13316e-07
  8 SNES Function norm 1.13316e-07
L_2 Error: 0.0198799
Nonlinear solve converged due to CONVERGED_FNORM_RELATIVE iterations 8
SNES Object: 1 MPI process
  type: fas
    type is MULTIPLICATIVE, levels=2, cycles=1
    Not using Galerkin computed coarse grid function evaluation
    Coarse grid solver -- level 0 -------------------------------
    SNES Object: (fas_coarse_) 1 MPI process
      type: newtonls
      maximum iterations=50, maximum function evaluations=10000
      tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
      total number of linear solver iterations=2
      total number of function evaluations=2
      norm schedule ALWAYS
      SNESLineSearch Object: (fas_coarse_) 1 MPI process
        type: basic
        maxlambda=1.000000e+00, minlambda=1.000000e-12
        tolerances: relative=1.000000e-08, absolute=1.000000e-15, lambda=1.000000e-08
        maximum iterations=40
      KSP Object: (fas_coarse_) 1 MPI process
        type: gmres
          restart=30, using classical (unmodified) Gram-Schmidt orthogonalization with no iterative refinement
          happy breakdown tolerance=1e-30
        maximum iterations=10000, initial guess is zero
        tolerances: relative=1e-10, absolute=1e-50, divergence=10000.
        left preconditioning
        using PRECONDITIONED norm type for convergence test
      PC Object: (fas_coarse_) 1 MPI process
        type: svd
          All singular values smaller than 1e-12 treated as zero
          Provided essential rank of the matrix 0 (all other eigenvalues are zeroed)
        linear system matrix, which is also used to construct the preconditioner:
        Mat Object: 1 MPI process
          type: seqaij
          rows=1, cols=1
          total: nonzeros=1, allocated nonzeros=1
          total number of mallocs used during MatSetValues calls=0
            not using I-node routines
    Down solver (pre-smoother) on level 1 -------------------------------
    SNES Object: (fas_levels_1_) 1 MPI process
      type: ngs
        Use finite difference secant approximation with coloring with h = 1.49012e-08 
      maximum iterations=1, maximum function evaluations=10000
      tolerances: relative=0., absolute=0., solution=0.
      total number of function evaluations=2
      norm schedule FINALONLY
    Up solver (post-smoother) same as down solver (pre-smoother)
  maximum iterations=10000, maximum function evaluations=30000
  tolerances: relative=1e-08, absolute=1e-50, solution=1e-08
  total number of function evaluations=1
  norm schedule ALWAYS