static char help[] ="Tests PetscObjectSetOptions() for TS object\n\n";

/*
   Concepts: TS^time-dependent nonlinear problems
   Processors: n
*/

/* ------------------------------------------------------------------------

   This program solves the PDE

               u * u_xx
         u_t = ---------
               2*(t+1)^2

    on the domain 0 <= x <= 1, with boundary conditions
         u(t,0) = t + 1,  u(t,1) = 2*t + 2,
    and initial condition
         u(0,x) = 1 + x*x.

    The exact solution is:
         u(t,x) = (1 + x*x) * (1 + t)

    Note that since the solution is linear in time and quadratic in x,
    the finite difference scheme actually computes the "exact" solution.

    We use by default the backward Euler method.

  ------------------------------------------------------------------------- */

/*
   Include "petscts.h" to use the PETSc timestepping routines. Note that
   this file automatically includes "petscsys.h" and other lower-level
   PETSc include files.

   Include the "petscdmda.h" to allow us to use the distributed array data
   structures to manage the parallel grid.
*/
#include <petscts.h>
#include <petscdm.h>
#include <petscdmda.h>
#include <petscdraw.h>

/*
   User-defined application context - contains data needed by the
   application-provided callback routines.
*/
typedef struct {
  MPI_Comm  comm;           /* communicator */
  DM        da;             /* distributed array data structure */
  Vec       localwork;      /* local ghosted work vector */
  Vec       u_local;        /* local ghosted approximate solution vector */
  Vec       solution;       /* global exact solution vector */
  PetscInt  m;              /* total number of grid points */
  PetscReal h;              /* mesh width: h = 1/(m-1) */
} AppCtx;

/*
   User-defined routines, provided below.
*/
extern PetscErrorCode InitialConditions(Vec,AppCtx*);
extern PetscErrorCode RHSFunction(TS,PetscReal,Vec,Vec,void*);
extern PetscErrorCode RHSJacobian(TS,PetscReal,Vec,Mat,Mat,void*);
extern PetscErrorCode ExactSolution(PetscReal,Vec,AppCtx*);

int main(int argc,char **argv)
{
  AppCtx         appctx;                 /* user-defined application context */
  TS             ts;                     /* timestepping context */
  Mat            A;                      /* Jacobian matrix data structure */
  Vec            u;                      /* approximate solution vector */
  PetscInt       time_steps_max = 100;  /* default max timesteps */
  PetscErrorCode ierr;
  PetscReal      dt;
  PetscReal      time_total_max = 100.0; /* default max total time */
  PetscOptions   options,optionscopy;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Initialize program and set problem parameters
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = PetscInitialize(&argc,&argv,(char*)0,help);if (ierr) return ierr;

  ierr = PetscOptionsCreate(&options);CHKERRQ(ierr);
  ierr = PetscOptionsSetValue(options,"-ts_monitor","ascii");CHKERRQ(ierr);
  ierr = PetscOptionsSetValue(options,"-snes_monitor","ascii");CHKERRQ(ierr);
  ierr = PetscOptionsSetValue(options,"-ksp_monitor","ascii");CHKERRQ(ierr);

  appctx.comm = PETSC_COMM_WORLD;
  appctx.m    = 60;

  ierr = PetscOptionsGetInt(options,NULL,"-M",&appctx.m,NULL);CHKERRQ(ierr);

  appctx.h    = 1.0/(appctx.m-1.0);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Create vector data structures
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /*
     Create distributed array (DMDA) to manage parallel grid and vectors
     and to set up the ghost point communication pattern.  There are M
     total grid values spread equally among all the processors.
  */
  ierr = DMDACreate1d(PETSC_COMM_WORLD,DM_BOUNDARY_NONE,appctx.m,1,1,NULL,&appctx.da);CHKERRQ(ierr);
  ierr = PetscObjectSetOptions((PetscObject)appctx.da,options);CHKERRQ(ierr);
  ierr = DMSetFromOptions(appctx.da);CHKERRQ(ierr);
  ierr = DMSetUp(appctx.da);CHKERRQ(ierr);

  /*
     Extract global and local vectors from DMDA; we use these to store the
     approximate solution.  Then duplicate these for remaining vectors that
     have the same types.
  */
  ierr = DMCreateGlobalVector(appctx.da,&u);CHKERRQ(ierr);
  ierr = DMCreateLocalVector(appctx.da,&appctx.u_local);CHKERRQ(ierr);

  /*
     Create local work vector for use in evaluating right-hand-side function;
     create global work vector for storing exact solution.
  */
  ierr = VecDuplicate(appctx.u_local,&appctx.localwork);CHKERRQ(ierr);
  ierr = VecDuplicate(u,&appctx.solution);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Create timestepping solver context; set callback routine for
     right-hand-side function evaluation.
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = TSCreate(PETSC_COMM_WORLD,&ts);CHKERRQ(ierr);
  ierr = PetscObjectSetOptions((PetscObject)ts,options);CHKERRQ(ierr);
  ierr = TSSetProblemType(ts,TS_NONLINEAR);CHKERRQ(ierr);
  ierr = TSSetRHSFunction(ts,NULL,RHSFunction,&appctx);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     For nonlinear problems, the user can provide a Jacobian evaluation
     routine (or use a finite differencing approximation).

     Create matrix data structure; set Jacobian evaluation routine.
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = MatCreate(PETSC_COMM_WORLD,&A);CHKERRQ(ierr);
  ierr = PetscObjectSetOptions((PetscObject)A,options);CHKERRQ(ierr);
  ierr = MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,appctx.m,appctx.m);CHKERRQ(ierr);
  ierr = MatSetFromOptions(A);CHKERRQ(ierr);
  ierr = MatSetUp(A);CHKERRQ(ierr);
  ierr = TSSetRHSJacobian(ts,A,A,RHSJacobian,&appctx);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Set solution vector and initial timestep
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  dt   = appctx.h/2.0;
  ierr = TSSetTimeStep(ts,dt);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Customize timestepping solver:
       - Set the solution method to be the Backward Euler method.
       - Set timestepping duration info
     Then set runtime options, which can override these defaults.
     For example,
          -ts_max_steps <maxsteps> -ts_max_time <maxtime>
     to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = TSSetType(ts,TSBEULER);CHKERRQ(ierr);
  ierr = TSSetMaxSteps(ts,time_steps_max);CHKERRQ(ierr);
  ierr = TSSetMaxTime(ts,time_total_max);CHKERRQ(ierr);
  ierr = TSSetExactFinalTime(ts,TS_EXACTFINALTIME_STEPOVER);CHKERRQ(ierr);
  ierr = TSSetFromOptions(ts);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Solve the problem
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /*
     Evaluate initial conditions
  */
  ierr = InitialConditions(u,&appctx);CHKERRQ(ierr);

  /*
     Run the timestepping solver
  */
  ierr = TSSolve(ts,u);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Free work space.  All PETSc objects should be destroyed when they
     are no longer needed.
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  ierr = PetscObjectGetOptions((PetscObject)ts,&optionscopy);CHKERRQ(ierr);
  if (options != optionscopy) SETERRQ(PETSC_COMM_WORLD,PETSC_ERR_PLIB,"PetscObjectGetOptions() failed");

  ierr = TSDestroy(&ts);CHKERRQ(ierr);
  ierr = VecDestroy(&u);CHKERRQ(ierr);
  ierr = MatDestroy(&A);CHKERRQ(ierr);
  ierr = DMDestroy(&appctx.da);CHKERRQ(ierr);
  ierr = VecDestroy(&appctx.localwork);CHKERRQ(ierr);
  ierr = VecDestroy(&appctx.solution);CHKERRQ(ierr);
  ierr = VecDestroy(&appctx.u_local);CHKERRQ(ierr);
  ierr = PetscOptionsDestroy(&options);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_view).
  */
  ierr = PetscFinalize();
  return ierr;
}
/* --------------------------------------------------------------------- */
/*
   InitialConditions - Computes the solution at the initial time.

   Input Parameters:
   u - uninitialized solution vector (global)
   appctx - user-defined application context

   Output Parameter:
   u - vector with solution at initial time (global)
*/
PetscErrorCode InitialConditions(Vec u,AppCtx *appctx)
{
  PetscScalar    *u_localptr,h = appctx->h,x;
  PetscInt       i,mybase,myend;
  PetscErrorCode ierr;

  /*
     Determine starting point of each processor's range of
     grid values.
  */
  ierr = VecGetOwnershipRange(u,&mybase,&myend);CHKERRQ(ierr);

  /*
    Get a pointer to vector data.
    - For default PETSc vectors, VecGetArray() returns a pointer to
      the data array.  Otherwise, the routine is implementation dependent.
    - You MUST call VecRestoreArray() when you no longer need access to
      the array.
    - Note that the Fortran interface to VecGetArray() differs from the
      C version.  See the users manual for details.
  */
  ierr = VecGetArray(u,&u_localptr);CHKERRQ(ierr);

  /*
     We initialize the solution array by simply writing the solution
     directly into the array locations.  Alternatively, we could use
     VecSetValues() or VecSetValuesLocal().
  */
  for (i=mybase; i<myend; i++) {
    x = h*(PetscReal)i; /* current location in global grid */
    u_localptr[i-mybase] = 1.0 + x*x;
  }

  /*
     Restore vector
  */
  ierr = VecRestoreArray(u,&u_localptr);CHKERRQ(ierr);

  return 0;
}
/* --------------------------------------------------------------------- */
/*
   ExactSolution - Computes the exact solution at a given time.

   Input Parameters:
   t - current time
   solution - vector in which exact solution will be computed
   appctx - user-defined application context

   Output Parameter:
   solution - vector with the newly computed exact solution
*/
PetscErrorCode ExactSolution(PetscReal t,Vec solution,AppCtx *appctx)
{
  PetscScalar    *s_localptr,h = appctx->h,x;
  PetscInt       i,mybase,myend;
  PetscErrorCode ierr;

  /*
     Determine starting and ending points of each processor's
     range of grid values
  */
  ierr = VecGetOwnershipRange(solution,&mybase,&myend);CHKERRQ(ierr);

  /*
     Get a pointer to vector data.
  */
  ierr = VecGetArray(solution,&s_localptr);CHKERRQ(ierr);

  /*
     Simply write the solution directly into the array locations.
     Alternatively, we could use VecSetValues() or VecSetValuesLocal().
  */
  for (i=mybase; i<myend; i++) {
    x = h*(PetscReal)i;
    s_localptr[i-mybase] = (t + 1.0)*(1.0 + x*x);
  }

  /*
     Restore vector
  */
  ierr = VecRestoreArray(solution,&s_localptr);CHKERRQ(ierr);
  return 0;
}
/* --------------------------------------------------------------------- */
/*
   RHSFunction - User-provided routine that evalues the right-hand-side
   function of the ODE.  This routine is set in the main program by
   calling TSSetRHSFunction().  We compute:
          global_out = F(global_in)

   Input Parameters:
   ts         - timesteping context
   t          - current time
   global_in  - vector containing the current iterate
   ctx        - (optional) user-provided context for function evaluation.
                In this case we use the appctx defined above.

   Output Parameter:
   global_out - vector containing the newly evaluated function
*/
PetscErrorCode RHSFunction(TS ts,PetscReal t,Vec global_in,Vec global_out,void *ctx)
{
  AppCtx            *appctx   = (AppCtx*) ctx;     /* user-defined application context */
  DM                da        = appctx->da;        /* distributed array */
  Vec               local_in  = appctx->u_local;   /* local ghosted input vector */
  Vec               localwork = appctx->localwork; /* local ghosted work vector */
  PetscErrorCode    ierr;
  PetscInt          i,localsize;
  PetscMPIInt       rank,size;
  PetscScalar       *copyptr,sc;
  const PetscScalar *localptr;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Get ready for local function computations
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  /*
     Scatter ghost points to local vector, using the 2-step process
        DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
     By placing code between these two statements, computations can be
     done while messages are in transition.
  */
  ierr = DMGlobalToLocalBegin(da,global_in,INSERT_VALUES,local_in);CHKERRQ(ierr);
  ierr = DMGlobalToLocalEnd(da,global_in,INSERT_VALUES,local_in);CHKERRQ(ierr);

  /*
      Access directly the values in our local INPUT work array
  */
  ierr = VecGetArrayRead(local_in,&localptr);CHKERRQ(ierr);

  /*
      Access directly the values in our local OUTPUT work array
  */
  ierr = VecGetArray(localwork,&copyptr);CHKERRQ(ierr);

  sc = 1.0/(appctx->h*appctx->h*2.0*(1.0+t)*(1.0+t));

  /*
      Evaluate our function on the nodes owned by this processor
  */
  ierr = VecGetLocalSize(local_in,&localsize);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Compute entries for the locally owned part
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /*
     Handle boundary conditions: This is done by using the boundary condition
        u(t,boundary) = g(t,boundary)
     for some function g. Now take the derivative with respect to t to obtain
        u_{t}(t,boundary) = g_{t}(t,boundary)

     In our case, u(t,0) = t + 1, so that u_{t}(t,0) = 1
             and  u(t,1) = 2t+ 2, so that u_{t}(t,1) = 2
  */
  ierr = MPI_Comm_rank(appctx->comm,&rank);CHKERRMPI(ierr);
  ierr = MPI_Comm_size(appctx->comm,&size);CHKERRMPI(ierr);
  if (rank == 0)          copyptr[0]           = 1.0;
  if (rank == size-1) copyptr[localsize-1] = 2.0;

  /*
     Handle the interior nodes where the PDE is replace by finite
     difference operators.
  */
  for (i=1; i<localsize-1; i++) copyptr[i] =  localptr[i] * sc * (localptr[i+1] + localptr[i-1] - 2.0*localptr[i]);

  /*
     Restore vectors
  */
  ierr = VecRestoreArrayRead(local_in,&localptr);CHKERRQ(ierr);
  ierr = VecRestoreArray(localwork,&copyptr);CHKERRQ(ierr);

  /*
     Insert values from the local OUTPUT vector into the global
     output vector
  */
  ierr = DMLocalToGlobalBegin(da,localwork,INSERT_VALUES,global_out);CHKERRQ(ierr);
  ierr = DMLocalToGlobalEnd(da,localwork,INSERT_VALUES,global_out);CHKERRQ(ierr);

  return 0;
}
/* --------------------------------------------------------------------- */
/*
   RHSJacobian - User-provided routine to compute the Jacobian of
   the nonlinear right-hand-side function of the ODE.

   Input Parameters:
   ts - the TS context
   t - current time
   global_in - global input vector
   dummy - optional user-defined context, as set by TSetRHSJacobian()

   Output Parameters:
   AA - Jacobian matrix
   BB - optionally different preconditioning matrix
   str - flag indicating matrix structure

  Notes:
  RHSJacobian computes entries for the locally owned part of the Jacobian.
   - Currently, all PETSc parallel matrix formats are partitioned by
     contiguous chunks of rows across the processors.
   - 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 row and columns of matrix entries when
     using MatSetValues().
   - Here, we set all entries for a particular row at once.
   - Note that MatSetValues() uses 0-based row and column numbers
     in Fortran as well as in C.
*/
PetscErrorCode RHSJacobian(TS ts,PetscReal t,Vec global_in,Mat AA,Mat BB,void *ctx)
{
  AppCtx            *appctx  = (AppCtx*)ctx;    /* user-defined application context */
  Vec               local_in = appctx->u_local;   /* local ghosted input vector */
  DM                da       = appctx->da;        /* distributed array */
  PetscScalar       v[3],sc;
  const PetscScalar *localptr;
  PetscErrorCode    ierr;
  PetscInt          i,mstart,mend,mstarts,mends,idx[3],is;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Get ready for local Jacobian computations
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  /*
     Scatter ghost points to local vector, using the 2-step process
        DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
     By placing code between these two statements, computations can be
     done while messages are in transition.
  */
  ierr = DMGlobalToLocalBegin(da,global_in,INSERT_VALUES,local_in);CHKERRQ(ierr);
  ierr = DMGlobalToLocalEnd(da,global_in,INSERT_VALUES,local_in);CHKERRQ(ierr);

  /*
     Get pointer to vector data
  */
  ierr = VecGetArrayRead(local_in,&localptr);CHKERRQ(ierr);

  /*
     Get starting and ending locally owned rows of the matrix
  */
  ierr   = MatGetOwnershipRange(BB,&mstarts,&mends);CHKERRQ(ierr);
  mstart = mstarts; mend = mends;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Compute entries for the locally owned part of the Jacobian.
      - Currently, all PETSc parallel matrix formats are partitioned by
        contiguous chunks of rows across the processors.
      - 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).
      - Here, we set all entries for a particular row at once.
      - We can set matrix entries either using either
        MatSetValuesLocal() or MatSetValues().
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */

  /*
     Set matrix rows corresponding to boundary data
  */
  if (mstart == 0) {
    v[0] = 0.0;
    ierr = MatSetValues(BB,1,&mstart,1,&mstart,v,INSERT_VALUES);CHKERRQ(ierr);
    mstart++;
  }
  if (mend == appctx->m) {
    mend--;
    v[0] = 0.0;
    ierr = MatSetValues(BB,1,&mend,1,&mend,v,INSERT_VALUES);CHKERRQ(ierr);
  }

  /*
     Set matrix rows corresponding to interior data.  We construct the
     matrix one row at a time.
  */
  sc = 1.0/(appctx->h*appctx->h*2.0*(1.0+t)*(1.0+t));
  for (i=mstart; i<mend; i++) {
    idx[0] = i-1; idx[1] = i; idx[2] = i+1;
    is     = i - mstart + 1;
    v[0]   = sc*localptr[is];
    v[1]   = sc*(localptr[is+1] + localptr[is-1] - 4.0*localptr[is]);
    v[2]   = sc*localptr[is];
    ierr   = MatSetValues(BB,1,&i,3,idx,v,INSERT_VALUES);CHKERRQ(ierr);
  }

  /*
     Restore vector
  */
  ierr = VecRestoreArrayRead(local_in,&localptr);CHKERRQ(ierr);

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Complete the matrix assembly process and set some options
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  /*
     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(BB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  ierr = MatAssemblyEnd(BB,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  if (BB != AA) {
    ierr = MatAssemblyBegin(AA,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
    ierr = MatAssemblyEnd(AA,MAT_FINAL_ASSEMBLY);CHKERRQ(ierr);
  }

  /*
     Set and option to indicate that we will never add a new nonzero location
     to the matrix. If we do, it will generate an error.
  */
  ierr = MatSetOption(BB,MAT_NEW_NONZERO_LOCATION_ERR,PETSC_TRUE);CHKERRQ(ierr);

  return 0;
}

/*TEST

    test:
      requires: !single

TEST*/