/*$Id: ex12.c,v 1.24 2001/08/07 21:30:54 bsmith Exp $*/

/* Program usage:  mpirun -np <procs> ex12 [-help] [all PETSc options] */

static char help[] = "Solves a linear system in parallel with SLES.\n\
Input parameters include:\n\
  -m <mesh_x>       : number of mesh points in x-direction\n\
  -n <mesh_n>       : number of mesh points in y-direction\n\n";

/*T
   Concepts: SLES^solving a system of linear equations
   Concepts: SLES^Laplacian, 2d
   Concepts: PC^registering preconditioners
   Processors: n
T*/

/*
   Demonstrates registering a new preconditioner (PC) type.

   To register a PC type whose code is linked into the executable,
   use PCRegister(). To register a PC type in a dynamic library use PCRegisterDynamic()

   Also provide the prototype for your PCCreate_XXX() function. In 
   this example we use the PETSc implementation of the Jacobi method,
   PCCreate_Jacobi() just as an example.

   See the file src/sles/pc/impls/jacobi/jacobi.c for details on how to 
   write a new PC component.

   See the manual page PCRegisterDynamic() for details on how to register a method.
*/

/* 
  Include "petscsles.h" so that we can use SLES solvers.  Note that this file
  automatically includes:
     petsc.h       - base PETSc routines   petscvec.h - vectors
     petscsys.h    - system routines       petscmat.h - matrices
     petscis.h     - index sets            petscksp.h - Krylov subspace methods
     petscviewer.h - viewers               petscpc.h  - preconditioners
*/
#include "petscsles.h"

EXTERN_C_BEGIN
extern int PCCreate_Jacobi(PC);
EXTERN_C_END

#undef __FUNCT__
#define __FUNCT__ "main"
int main(int argc,char **args)
{
  Vec         x,b,u;  /* approx solution, RHS, exact solution */
  Mat         A;        /* linear system matrix */
  SLES        sles;     /* linear solver context */
  PetscReal   norm;     /* norm of solution error */
  int         i,j,I,J,Istart,Iend,ierr,m = 8,n = 7,its;
  PetscScalar v,one = 1.0,neg_one = -1.0;
  PC          pc;      /* preconditioner context */

  PetscInitialize(&argc,&args,(char *)0,help);
  ierr = PetscOptionsGetInt(PETSC_NULL,"-m",&m,PETSC_NULL);CHKERRQ(ierr);
  ierr = PetscOptionsGetInt(PETSC_NULL,"-n",&n,PETSC_NULL);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
         Compute the matrix and right-hand-side vector that define
         the linear system, Ax = b.
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  /* 
     Create parallel matrix, specifying only its global dimensions.
     When using MatCreate(), the matrix format can be specified at
     runtime. Also, the parallel partitioning of the matrix is
     determined by PETSc at runtime.
  */
  ierr = MatCreate(PETSC_COMM_WORLD,PETSC_DECIDE,PETSC_DECIDE,m*n,m*n,&A);CHKERRQ(ierr);
  ierr = MatSetFromOptions(A);CHKERRQ(ierr);

  /* 
     Currently, all PETSc parallel matrix formats are partitioned by
     contiguous chunks of rows across the processors.  Determine which
     rows of the matrix are locally owned. 
  */
  ierr = MatGetOwnershipRange(A,&Istart,&Iend);CHKERRQ(ierr);

  /* 
     Set matrix elements for the 2-D, five-point stencil in parallel.
      - Each processor needs to insert only elements that it owns
        locally (but any non-local elements will be sent to the
        appropriate processor during matrix assembly). 
      - Always specify global rows and columns of matrix entries.
   */
  for (I=Istart; I<Iend; I++) { 
    v = -1.0; i = I/n; j = I - i*n;  
    if (i>0)   {J = I - n; ierr = MatSetValues(A,1,&I,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (i<m-1) {J = I + n; ierr = MatSetValues(A,1,&I,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (j>0)   {J = I - 1; ierr = MatSetValues(A,1,&I,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    if (j<n-1) {J = I + 1; ierr = MatSetValues(A,1,&I,1,&J,&v,INSERT_VALUES);CHKERRQ(ierr);}
    v = 4.0; ierr = MatSetValues(A,1,&I,1,&I,&v,INSERT_VALUES);
  }

  /* 
     Assemble matrix, using the 2-step process:
       MatAssemblyBegin(), MatAssemblyEnd()
     Computations can be done while messages are in transition
     by placing code between these two statements.
  */
  ierr = MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);

  /* 
     Create parallel vectors.
      - When using VecCreate(), VecSetSizes() and VecSetFromOptions(),
      we specify only the vector's global
        dimension; the parallel partitioning is determined at runtime. 
      - When solving a linear system, the vectors and matrices MUST
        be partitioned accordingly.  PETSc automatically generates
        appropriately partitioned matrices and vectors when MatCreate()
        and VecCreate() are used with the same communicator. 
      - Note: We form 1 vector from scratch and then duplicate as needed.
  */
  ierr = VecCreate(PETSC_COMM_WORLD,&u);CHKERRQ(ierr);
  ierr = VecSetSizes(u,PETSC_DECIDE,m*n);CHKERRQ(ierr);
  ierr = VecSetFromOptions(u);CHKERRQ(ierr);
  ierr = VecDuplicate(u,&b);CHKERRQ(ierr); 
  ierr = VecDuplicate(b,&x);CHKERRQ(ierr);

  /* 
     Set exact solution; then compute right-hand-side vector.
     Use an exact solution of a vector with all elements of 1.0;  
  */
  ierr = VecSet(&one,u);CHKERRQ(ierr);
  ierr = MatMult(A,u,b);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                Create the linear solver and set various options
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /* 
     Create linear solver context
  */
  ierr = SLESCreate(PETSC_COMM_WORLD,&sles);CHKERRQ(ierr);

  /* 
     Set operators. Here the matrix that defines the linear system
     also serves as the preconditioning matrix.
  */
  ierr = SLESSetOperators(sles,A,A,DIFFERENT_NONZERO_PATTERN);CHKERRQ(ierr);

  /*
       First register a new PC type with the command PCRegister()
  */
  ierr = PCRegister("ourjacobi",0,"PCCreate_Jacobi",PCCreate_Jacobi);CHKERRQ(ierr);
  
  /* 
     Set the PC type to be the new method
  */  
  ierr = SLESGetPC(sles,&pc);CHKERRQ(ierr);
  ierr = PCSetType(pc,"ourjacobi");

  /* 
    Set runtime options, e.g.,
        -ksp_type <type> -pc_type <type> -ksp_monitor -ksp_rtol <rtol>
    These options will override those specified above as long as
    SLESSetFromOptions() is called _after_ any other customization
    routines.
  */
  ierr = SLESSetFromOptions(sles);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                      Solve the linear system
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = SLESSolve(sles,b,x,&its);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 
                      Check solution and clean up
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /* 
     Check the error
  */
  ierr = VecAXPY(&neg_one,u,x);CHKERRQ(ierr);
  ierr = VecNorm(x,NORM_2,&norm);CHKERRQ(ierr);

  /* Scale the norm */
  /*  norm *= sqrt(1.0/((m+1)*(n+1))); */

  /*
     Print convergence information.  PetscPrintf() produces a single 
     print statement from all processes that share a communicator.
  */
  ierr = PetscPrintf(PETSC_COMM_WORLD,"Norm of error %A iterations %d\n",norm,its);CHKERRQ(ierr);

  /* 
     Free work space.  All PETSc objects should be destroyed when they
     are no longer needed.
  */
  ierr = SLESDestroy(sles);CHKERRQ(ierr);
  ierr = VecDestroy(u);CHKERRQ(ierr);  ierr = VecDestroy(x);CHKERRQ(ierr);
  ierr = VecDestroy(b);CHKERRQ(ierr);  ierr = MatDestroy(A);CHKERRQ(ierr);

  /*
     Always call PetscFinalize() before exiting a program.  This routine
       - finalizes the PETSc libraries as well as MPI
       - provides summary and diagnostic information if certain runtime
         options are chosen (e.g., -log_summary). 
  */
  ierr = PetscFinalize();CHKERRQ(ierr);
  return 0;
}