static char help[] = "Test file for the PCFactorSetShiftType()\n";
/*
 * Test file for the PCFactorSetShiftType() routine or -pc_factor_shift_type POSITIVE_DEFINITE option.
 * The test matrix is the example from Kershaw's paper [J.Comp.Phys 1978]
 * of a positive definite matrix for which ILU(0) will give a negative pivot.
 * This means that the CG method will break down; the Manteuffel shift
 * [Math. Comp. 1980] repairs this.
 *
 * Run the executable twice:
 * 1/ without options: the iterative method diverges because of an
 *    indefinite preconditioner
 * 2/ with -pc_factor_shift_type POSITIVE_DEFINITE option (or comment in the PCFactorSetShiftType() line below):
 *    the method will now successfully converge.
 *
 * Contributed by Victor Eijkhout 2003.
 */

#include <petscksp.h>

int main(int argc, char **argv)
{
  KSP                solver;
  PC                 prec;
  Mat                A, M;
  Vec                X, B, D;
  MPI_Comm           comm;
  PetscScalar        v;
  KSPConvergedReason reason;
  PetscInt           i, j, its;

  PetscFunctionBeginUser;
  PetscCall(PetscInitialize(&argc, &argv, 0, help));
  comm = MPI_COMM_SELF;

  /*
   * Construct the Kershaw matrix
   * and a suitable rhs / initial guess
   */
  PetscCall(MatCreateSeqAIJ(comm, 4, 4, 4, 0, &A));
  PetscCall(VecCreateSeq(comm, 4, &B));
  PetscCall(VecDuplicate(B, &X));
  for (i = 0; i < 4; i++) {
    v = 3;
    PetscCall(MatSetValues(A, 1, &i, 1, &i, &v, INSERT_VALUES));
    v = 1;
    PetscCall(VecSetValues(B, 1, &i, &v, INSERT_VALUES));
    PetscCall(VecSetValues(X, 1, &i, &v, INSERT_VALUES));
  }

  i = 0;
  v = 0;
  PetscCall(VecSetValues(X, 1, &i, &v, INSERT_VALUES));

  for (i = 0; i < 3; i++) {
    v = -2;
    j = i + 1;
    PetscCall(MatSetValues(A, 1, &i, 1, &j, &v, INSERT_VALUES));
    PetscCall(MatSetValues(A, 1, &j, 1, &i, &v, INSERT_VALUES));
  }
  i = 0;
  j = 3;
  v = 2;

  PetscCall(MatSetValues(A, 1, &i, 1, &j, &v, INSERT_VALUES));
  PetscCall(MatSetValues(A, 1, &j, 1, &i, &v, INSERT_VALUES));
  PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
  PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
  PetscCall(VecAssemblyBegin(B));
  PetscCall(VecAssemblyEnd(B));

  /*
   * A Conjugate Gradient method
   * with ILU(0) preconditioning
   */
  PetscCall(KSPCreate(comm, &solver));
  PetscCall(KSPSetOperators(solver, A, A));

  PetscCall(KSPSetType(solver, KSPCG));
  PetscCall(KSPSetInitialGuessNonzero(solver, PETSC_TRUE));

  /*
   * ILU preconditioner;
   * this will break down unless you add the Shift line,
   * or use the -pc_factor_shift_positive_definite option */
  PetscCall(KSPGetPC(solver, &prec));
  PetscCall(PCSetType(prec, PCILU));
  /* PetscCall(PCFactorSetShiftType(prec,MAT_SHIFT_POSITIVE_DEFINITE)); */

  PetscCall(KSPSetFromOptions(solver));
  PetscCall(KSPSetUp(solver));

  /*
   * Now that the factorisation is done, show the pivots;
   * note that the last one is negative. This in itself is not an error,
   * but it will make the iterative method diverge.
   */
  PetscCall(PCFactorGetMatrix(prec, &M));
  PetscCall(VecDuplicate(B, &D));
  PetscCall(MatGetDiagonal(M, D));

  /*
   * Solve the system;
   * without the shift this will diverge with
   * an indefinite preconditioner
   */
  PetscCall(KSPSolve(solver, B, X));
  PetscCall(KSPGetConvergedReason(solver, &reason));
  if (reason == KSP_DIVERGED_INDEFINITE_PC) {
    PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\nDivergence because of indefinite preconditioner;\n"));
    PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Run the executable again but with '-pc_factor_shift_type POSITIVE_DEFINITE' option.\n"));
  } else if (reason < 0) {
    PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\nOther kind of divergence: this should not happen.\n"));
  } else {
    PetscCall(KSPGetIterationNumber(solver, &its));
  }

  PetscCall(VecDestroy(&X));
  PetscCall(VecDestroy(&B));
  PetscCall(VecDestroy(&D));
  PetscCall(MatDestroy(&A));
  PetscCall(KSPDestroy(&solver));
  PetscCall(PetscFinalize());
  return 0;
}

/*TEST

   test:
      args: -pc_factor_shift_type positive_definite

TEST*/
