Actual source code: ex2.c
1: static char help[] = "Solves a time-dependent nonlinear PDE. Uses implicit\n\
2: timestepping. Runtime options include:\n\
3: -M <xg>, where <xg> = number of grid points\n\
4: -debug : Activate debugging printouts\n\
5: -nox : Deactivate x-window graphics\n\n";
7: /* ------------------------------------------------------------------------
9: This program solves the PDE
11: u * u_xx
12: u_t = ---------
13: 2*(t+1)^2
15: on the domain 0 <= x <= 1, with boundary conditions
16: u(t,0) = t + 1, u(t,1) = 2*t + 2,
17: and initial condition
18: u(0,x) = 1 + x*x.
20: The exact solution is:
21: u(t,x) = (1 + x*x) * (1 + t)
23: Note that since the solution is linear in time and quadratic in x,
24: the finite difference scheme actually computes the "exact" solution.
26: We use by default the backward Euler method.
28: ------------------------------------------------------------------------- */
30: /*
31: Include "petscts.h" to use the PETSc timestepping routines. Note that
32: this file automatically includes "petscsys.h" and other lower-level
33: PETSc include files.
35: Include the "petscdmda.h" to allow us to use the distributed array data
36: structures to manage the parallel grid.
37: */
38: #include <petscts.h>
39: #include <petscdm.h>
40: #include <petscdmda.h>
41: #include <petscdraw.h>
43: /*
44: User-defined application context - contains data needed by the
45: application-provided callback routines.
46: */
47: typedef struct {
48: MPI_Comm comm; /* communicator */
49: DM da; /* distributed array data structure */
50: Vec localwork; /* local ghosted work vector */
51: Vec u_local; /* local ghosted approximate solution vector */
52: Vec solution; /* global exact solution vector */
53: PetscInt m; /* total number of grid points */
54: PetscReal h; /* mesh width: h = 1/(m-1) */
55: PetscBool debug; /* flag (1 indicates activation of debugging printouts) */
56: } AppCtx;
58: /*
59: User-defined routines, provided below.
60: */
61: extern PetscErrorCode InitialConditions(Vec, AppCtx *);
62: extern PetscErrorCode RHSFunction(TS, PetscReal, Vec, Vec, void *);
63: extern PetscErrorCode RHSJacobian(TS, PetscReal, Vec, Mat, Mat, void *);
64: extern PetscErrorCode Monitor(TS, PetscInt, PetscReal, Vec, void *);
65: extern PetscErrorCode ExactSolution(PetscReal, Vec, AppCtx *);
67: int main(int argc, char **argv)
68: {
69: AppCtx appctx; /* user-defined application context */
70: TS ts; /* timestepping context */
71: Mat A; /* Jacobian matrix data structure */
72: Vec u; /* approximate solution vector */
73: PetscInt time_steps_max = 100; /* default max timesteps */
74: PetscReal dt;
75: PetscReal time_total_max = 100.0; /* default max total time */
76: PetscBool mymonitor = PETSC_FALSE;
77: PetscReal bounds[] = {1.0, 3.3};
79: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
80: Initialize program and set problem parameters
81: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
83: PetscFunctionBeginUser;
84: PetscCall(PetscInitialize(&argc, &argv, (char *)0, help));
85: PetscCall(PetscViewerDrawSetBounds(PETSC_VIEWER_DRAW_(PETSC_COMM_WORLD), 1, bounds));
87: appctx.comm = PETSC_COMM_WORLD;
88: appctx.m = 60;
90: PetscCall(PetscOptionsGetInt(NULL, NULL, "-M", &appctx.m, NULL));
91: PetscCall(PetscOptionsHasName(NULL, NULL, "-debug", &appctx.debug));
92: PetscCall(PetscOptionsHasName(NULL, NULL, "-mymonitor", &mymonitor));
94: appctx.h = 1.0 / (appctx.m - 1.0);
96: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
97: Create vector data structures
98: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
100: /*
101: Create distributed array (DMDA) to manage parallel grid and vectors
102: and to set up the ghost point communication pattern. There are M
103: total grid values spread equally among all the processors.
104: */
105: PetscCall(DMDACreate1d(PETSC_COMM_WORLD, DM_BOUNDARY_NONE, appctx.m, 1, 1, NULL, &appctx.da));
106: PetscCall(DMSetFromOptions(appctx.da));
107: PetscCall(DMSetUp(appctx.da));
109: /*
110: Extract global and local vectors from DMDA; we use these to store the
111: approximate solution. Then duplicate these for remaining vectors that
112: have the same types.
113: */
114: PetscCall(DMCreateGlobalVector(appctx.da, &u));
115: PetscCall(DMCreateLocalVector(appctx.da, &appctx.u_local));
117: /*
118: Create local work vector for use in evaluating right-hand-side function;
119: create global work vector for storing exact solution.
120: */
121: PetscCall(VecDuplicate(appctx.u_local, &appctx.localwork));
122: PetscCall(VecDuplicate(u, &appctx.solution));
124: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
125: Create timestepping solver context; set callback routine for
126: right-hand-side function evaluation.
127: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
129: PetscCall(TSCreate(PETSC_COMM_WORLD, &ts));
130: PetscCall(TSSetProblemType(ts, TS_NONLINEAR));
131: PetscCall(TSSetRHSFunction(ts, NULL, RHSFunction, &appctx));
133: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
134: Set optional user-defined monitoring routine
135: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
137: if (mymonitor) PetscCall(TSMonitorSet(ts, Monitor, &appctx, NULL));
139: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
140: For nonlinear problems, the user can provide a Jacobian evaluation
141: routine (or use a finite differencing approximation).
143: Create matrix data structure; set Jacobian evaluation routine.
144: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
146: PetscCall(MatCreate(PETSC_COMM_WORLD, &A));
147: PetscCall(MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, appctx.m, appctx.m));
148: PetscCall(MatSetFromOptions(A));
149: PetscCall(MatSetUp(A));
150: PetscCall(TSSetRHSJacobian(ts, A, A, RHSJacobian, &appctx));
152: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
153: Set solution vector and initial timestep
154: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
156: dt = appctx.h / 2.0;
157: PetscCall(TSSetTimeStep(ts, dt));
159: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
160: Customize timestepping solver:
161: - Set the solution method to be the Backward Euler method.
162: - Set timestepping duration info
163: Then set runtime options, which can override these defaults.
164: For example,
165: -ts_max_steps <maxsteps> -ts_max_time <maxtime>
166: to override the defaults set by TSSetMaxSteps()/TSSetMaxTime().
167: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
169: PetscCall(TSSetType(ts, TSBEULER));
170: PetscCall(TSSetMaxSteps(ts, time_steps_max));
171: PetscCall(TSSetMaxTime(ts, time_total_max));
172: PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER));
173: PetscCall(TSSetFromOptions(ts));
175: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
176: Solve the problem
177: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
179: /*
180: Evaluate initial conditions
181: */
182: PetscCall(InitialConditions(u, &appctx));
184: /*
185: Run the timestepping solver
186: */
187: PetscCall(TSSolve(ts, u));
189: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
190: Free work space. All PETSc objects should be destroyed when they
191: are no longer needed.
192: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
194: PetscCall(TSDestroy(&ts));
195: PetscCall(VecDestroy(&u));
196: PetscCall(MatDestroy(&A));
197: PetscCall(DMDestroy(&appctx.da));
198: PetscCall(VecDestroy(&appctx.localwork));
199: PetscCall(VecDestroy(&appctx.solution));
200: PetscCall(VecDestroy(&appctx.u_local));
202: /*
203: Always call PetscFinalize() before exiting a program. This routine
204: - finalizes the PETSc libraries as well as MPI
205: - provides summary and diagnostic information if certain runtime
206: options are chosen (e.g., -log_view).
207: */
208: PetscCall(PetscFinalize());
209: return 0;
210: }
211: /* --------------------------------------------------------------------- */
212: /*
213: InitialConditions - Computes the solution at the initial time.
215: Input Parameters:
216: u - uninitialized solution vector (global)
217: appctx - user-defined application context
219: Output Parameter:
220: u - vector with solution at initial time (global)
221: */
222: PetscErrorCode InitialConditions(Vec u, AppCtx *appctx)
223: {
224: PetscScalar *u_localptr, h = appctx->h, x;
225: PetscInt i, mybase, myend;
227: PetscFunctionBeginUser;
228: /*
229: Determine starting point of each processor's range of
230: grid values.
231: */
232: PetscCall(VecGetOwnershipRange(u, &mybase, &myend));
234: /*
235: Get a pointer to vector data.
236: - For default PETSc vectors, VecGetArray() returns a pointer to
237: the data array. Otherwise, the routine is implementation dependent.
238: - You MUST call VecRestoreArray() when you no longer need access to
239: the array.
240: - Note that the Fortran interface to VecGetArray() differs from the
241: C version. See the users manual for details.
242: */
243: PetscCall(VecGetArray(u, &u_localptr));
245: /*
246: We initialize the solution array by simply writing the solution
247: directly into the array locations. Alternatively, we could use
248: VecSetValues() or VecSetValuesLocal().
249: */
250: for (i = mybase; i < myend; i++) {
251: x = h * (PetscReal)i; /* current location in global grid */
252: u_localptr[i - mybase] = 1.0 + x * x;
253: }
255: /*
256: Restore vector
257: */
258: PetscCall(VecRestoreArray(u, &u_localptr));
260: /*
261: Print debugging information if desired
262: */
263: if (appctx->debug) {
264: PetscCall(PetscPrintf(appctx->comm, "initial guess vector\n"));
265: PetscCall(VecView(u, PETSC_VIEWER_STDOUT_WORLD));
266: }
268: PetscFunctionReturn(PETSC_SUCCESS);
269: }
270: /* --------------------------------------------------------------------- */
271: /*
272: ExactSolution - Computes the exact solution at a given time.
274: Input Parameters:
275: t - current time
276: solution - vector in which exact solution will be computed
277: appctx - user-defined application context
279: Output Parameter:
280: solution - vector with the newly computed exact solution
281: */
282: PetscErrorCode ExactSolution(PetscReal t, Vec solution, AppCtx *appctx)
283: {
284: PetscScalar *s_localptr, h = appctx->h, x;
285: PetscInt i, mybase, myend;
287: PetscFunctionBeginUser;
288: /*
289: Determine starting and ending points of each processor's
290: range of grid values
291: */
292: PetscCall(VecGetOwnershipRange(solution, &mybase, &myend));
294: /*
295: Get a pointer to vector data.
296: */
297: PetscCall(VecGetArray(solution, &s_localptr));
299: /*
300: Simply write the solution directly into the array locations.
301: Alternatively, we could use VecSetValues() or VecSetValuesLocal().
302: */
303: for (i = mybase; i < myend; i++) {
304: x = h * (PetscReal)i;
305: s_localptr[i - mybase] = (t + 1.0) * (1.0 + x * x);
306: }
308: /*
309: Restore vector
310: */
311: PetscCall(VecRestoreArray(solution, &s_localptr));
312: PetscFunctionReturn(PETSC_SUCCESS);
313: }
314: /* --------------------------------------------------------------------- */
315: /*
316: Monitor - User-provided routine to monitor the solution computed at
317: each timestep. This example plots the solution and computes the
318: error in two different norms.
320: Input Parameters:
321: ts - the timestep context
322: step - the count of the current step (with 0 meaning the
323: initial condition)
324: time - the current time
325: u - the solution at this timestep
326: ctx - the user-provided context for this monitoring routine.
327: In this case we use the application context which contains
328: information about the problem size, workspace and the exact
329: solution.
330: */
331: PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal time, Vec u, void *ctx)
332: {
333: AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */
334: PetscReal en2, en2s, enmax;
335: PetscDraw draw;
337: PetscFunctionBeginUser;
338: /*
339: We use the default X Windows viewer
340: PETSC_VIEWER_DRAW_(appctx->comm)
341: that is associated with the current communicator. This saves
342: the effort of calling PetscViewerDrawOpen() to create the window.
343: Note that if we wished to plot several items in separate windows we
344: would create each viewer with PetscViewerDrawOpen() and store them in
345: the application context, appctx.
347: PetscReal buffering makes graphics look better.
348: */
349: PetscCall(PetscViewerDrawGetDraw(PETSC_VIEWER_DRAW_(appctx->comm), 0, &draw));
350: PetscCall(PetscDrawSetDoubleBuffer(draw));
351: PetscCall(VecView(u, PETSC_VIEWER_DRAW_(appctx->comm)));
353: /*
354: Compute the exact solution at this timestep
355: */
356: PetscCall(ExactSolution(time, appctx->solution, appctx));
358: /*
359: Print debugging information if desired
360: */
361: if (appctx->debug) {
362: PetscCall(PetscPrintf(appctx->comm, "Computed solution vector\n"));
363: PetscCall(VecView(u, PETSC_VIEWER_STDOUT_WORLD));
364: PetscCall(PetscPrintf(appctx->comm, "Exact solution vector\n"));
365: PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_WORLD));
366: }
368: /*
369: Compute the 2-norm and max-norm of the error
370: */
371: PetscCall(VecAXPY(appctx->solution, -1.0, u));
372: PetscCall(VecNorm(appctx->solution, NORM_2, &en2));
373: en2s = PetscSqrtReal(appctx->h) * en2; /* scale the 2-norm by the grid spacing */
374: PetscCall(VecNorm(appctx->solution, NORM_MAX, &enmax));
376: /*
377: PetscPrintf() causes only the first processor in this
378: communicator to print the timestep information.
379: */
380: PetscCall(PetscPrintf(appctx->comm, "Timestep %" PetscInt_FMT ": time = %g 2-norm error = %g max norm error = %g\n", step, (double)time, (double)en2s, (double)enmax));
382: /*
383: Print debugging information if desired
384: */
385: if (appctx->debug) {
386: PetscCall(PetscPrintf(appctx->comm, "Error vector\n"));
387: PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_WORLD));
388: }
389: PetscFunctionReturn(PETSC_SUCCESS);
390: }
391: /* --------------------------------------------------------------------- */
392: /*
393: RHSFunction - User-provided routine that evalues the right-hand-side
394: function of the ODE. This routine is set in the main program by
395: calling TSSetRHSFunction(). We compute:
396: global_out = F(global_in)
398: Input Parameters:
399: ts - timesteping context
400: t - current time
401: global_in - vector containing the current iterate
402: ctx - (optional) user-provided context for function evaluation.
403: In this case we use the appctx defined above.
405: Output Parameter:
406: global_out - vector containing the newly evaluated function
407: */
408: PetscErrorCode RHSFunction(TS ts, PetscReal t, Vec global_in, Vec global_out, void *ctx)
409: {
410: AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */
411: DM da = appctx->da; /* distributed array */
412: Vec local_in = appctx->u_local; /* local ghosted input vector */
413: Vec localwork = appctx->localwork; /* local ghosted work vector */
414: PetscInt i, localsize;
415: PetscMPIInt rank, size;
416: PetscScalar *copyptr, sc;
417: const PetscScalar *localptr;
419: PetscFunctionBeginUser;
420: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
421: Get ready for local function computations
422: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
423: /*
424: Scatter ghost points to local vector, using the 2-step process
425: DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
426: By placing code between these two statements, computations can be
427: done while messages are in transition.
428: */
429: PetscCall(DMGlobalToLocalBegin(da, global_in, INSERT_VALUES, local_in));
430: PetscCall(DMGlobalToLocalEnd(da, global_in, INSERT_VALUES, local_in));
432: /*
433: Access directly the values in our local INPUT work array
434: */
435: PetscCall(VecGetArrayRead(local_in, &localptr));
437: /*
438: Access directly the values in our local OUTPUT work array
439: */
440: PetscCall(VecGetArray(localwork, ©ptr));
442: sc = 1.0 / (appctx->h * appctx->h * 2.0 * (1.0 + t) * (1.0 + t));
444: /*
445: Evaluate our function on the nodes owned by this processor
446: */
447: PetscCall(VecGetLocalSize(local_in, &localsize));
449: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
450: Compute entries for the locally owned part
451: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
453: /*
454: Handle boundary conditions: This is done by using the boundary condition
455: u(t,boundary) = g(t,boundary)
456: for some function g. Now take the derivative with respect to t to obtain
457: u_{t}(t,boundary) = g_{t}(t,boundary)
459: In our case, u(t,0) = t + 1, so that u_{t}(t,0) = 1
460: and u(t,1) = 2t+ 2, so that u_{t}(t,1) = 2
461: */
462: PetscCallMPI(MPI_Comm_rank(appctx->comm, &rank));
463: PetscCallMPI(MPI_Comm_size(appctx->comm, &size));
464: if (rank == 0) copyptr[0] = 1.0;
465: if (rank == size - 1) copyptr[localsize - 1] = 2.0;
467: /*
468: Handle the interior nodes where the PDE is replace by finite
469: difference operators.
470: */
471: for (i = 1; i < localsize - 1; i++) copyptr[i] = localptr[i] * sc * (localptr[i + 1] + localptr[i - 1] - 2.0 * localptr[i]);
473: /*
474: Restore vectors
475: */
476: PetscCall(VecRestoreArrayRead(local_in, &localptr));
477: PetscCall(VecRestoreArray(localwork, ©ptr));
479: /*
480: Insert values from the local OUTPUT vector into the global
481: output vector
482: */
483: PetscCall(DMLocalToGlobalBegin(da, localwork, INSERT_VALUES, global_out));
484: PetscCall(DMLocalToGlobalEnd(da, localwork, INSERT_VALUES, global_out));
486: /* Print debugging information if desired */
487: if (appctx->debug) {
488: PetscCall(PetscPrintf(appctx->comm, "RHS function vector\n"));
489: PetscCall(VecView(global_out, PETSC_VIEWER_STDOUT_WORLD));
490: }
492: PetscFunctionReturn(PETSC_SUCCESS);
493: }
494: /* --------------------------------------------------------------------- */
495: /*
496: RHSJacobian - User-provided routine to compute the Jacobian of
497: the nonlinear right-hand-side function of the ODE.
499: Input Parameters:
500: ts - the TS context
501: t - current time
502: global_in - global input vector
503: dummy - optional user-defined context, as set by TSetRHSJacobian()
505: Output Parameters:
506: AA - Jacobian matrix
507: BB - optionally different preconditioning matrix
508: str - flag indicating matrix structure
510: Notes:
511: RHSJacobian computes entries for the locally owned part of the Jacobian.
512: - Currently, all PETSc parallel matrix formats are partitioned by
513: contiguous chunks of rows across the processors.
514: - Each processor needs to insert only elements that it owns
515: locally (but any non-local elements will be sent to the
516: appropriate processor during matrix assembly).
517: - Always specify global row and columns of matrix entries when
518: using MatSetValues().
519: - Here, we set all entries for a particular row at once.
520: - Note that MatSetValues() uses 0-based row and column numbers
521: in Fortran as well as in C.
522: */
523: PetscErrorCode RHSJacobian(TS ts, PetscReal t, Vec global_in, Mat AA, Mat BB, void *ctx)
524: {
525: AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */
526: Vec local_in = appctx->u_local; /* local ghosted input vector */
527: DM da = appctx->da; /* distributed array */
528: PetscScalar v[3], sc;
529: const PetscScalar *localptr;
530: PetscInt i, mstart, mend, mstarts, mends, idx[3], is;
532: PetscFunctionBeginUser;
533: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
534: Get ready for local Jacobian computations
535: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
536: /*
537: Scatter ghost points to local vector, using the 2-step process
538: DMGlobalToLocalBegin(), DMGlobalToLocalEnd().
539: By placing code between these two statements, computations can be
540: done while messages are in transition.
541: */
542: PetscCall(DMGlobalToLocalBegin(da, global_in, INSERT_VALUES, local_in));
543: PetscCall(DMGlobalToLocalEnd(da, global_in, INSERT_VALUES, local_in));
545: /*
546: Get pointer to vector data
547: */
548: PetscCall(VecGetArrayRead(local_in, &localptr));
550: /*
551: Get starting and ending locally owned rows of the matrix
552: */
553: PetscCall(MatGetOwnershipRange(BB, &mstarts, &mends));
554: mstart = mstarts;
555: mend = mends;
557: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
558: Compute entries for the locally owned part of the Jacobian.
559: - Currently, all PETSc parallel matrix formats are partitioned by
560: contiguous chunks of rows across the processors.
561: - Each processor needs to insert only elements that it owns
562: locally (but any non-local elements will be sent to the
563: appropriate processor during matrix assembly).
564: - Here, we set all entries for a particular row at once.
565: - We can set matrix entries either using either
566: MatSetValuesLocal() or MatSetValues().
567: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
569: /*
570: Set matrix rows corresponding to boundary data
571: */
572: if (mstart == 0) {
573: v[0] = 0.0;
574: PetscCall(MatSetValues(BB, 1, &mstart, 1, &mstart, v, INSERT_VALUES));
575: mstart++;
576: }
577: if (mend == appctx->m) {
578: mend--;
579: v[0] = 0.0;
580: PetscCall(MatSetValues(BB, 1, &mend, 1, &mend, v, INSERT_VALUES));
581: }
583: /*
584: Set matrix rows corresponding to interior data. We construct the
585: matrix one row at a time.
586: */
587: sc = 1.0 / (appctx->h * appctx->h * 2.0 * (1.0 + t) * (1.0 + t));
588: for (i = mstart; i < mend; i++) {
589: idx[0] = i - 1;
590: idx[1] = i;
591: idx[2] = i + 1;
592: is = i - mstart + 1;
593: v[0] = sc * localptr[is];
594: v[1] = sc * (localptr[is + 1] + localptr[is - 1] - 4.0 * localptr[is]);
595: v[2] = sc * localptr[is];
596: PetscCall(MatSetValues(BB, 1, &i, 3, idx, v, INSERT_VALUES));
597: }
599: /*
600: Restore vector
601: */
602: PetscCall(VecRestoreArrayRead(local_in, &localptr));
604: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
605: Complete the matrix assembly process and set some options
606: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
607: /*
608: Assemble matrix, using the 2-step process:
609: MatAssemblyBegin(), MatAssemblyEnd()
610: Computations can be done while messages are in transition
611: by placing code between these two statements.
612: */
613: PetscCall(MatAssemblyBegin(BB, MAT_FINAL_ASSEMBLY));
614: PetscCall(MatAssemblyEnd(BB, MAT_FINAL_ASSEMBLY));
615: if (BB != AA) {
616: PetscCall(MatAssemblyBegin(AA, MAT_FINAL_ASSEMBLY));
617: PetscCall(MatAssemblyEnd(AA, MAT_FINAL_ASSEMBLY));
618: }
620: /*
621: Set and option to indicate that we will never add a new nonzero location
622: to the matrix. If we do, it will generate an error.
623: */
624: PetscCall(MatSetOption(BB, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE));
626: PetscFunctionReturn(PETSC_SUCCESS);
627: }
629: /*TEST
631: test:
632: args: -nox -ts_dt 10 -mymonitor
633: nsize: 2
634: requires: !single
636: test:
637: suffix: tut_1
638: nsize: 1
639: args: -ts_max_steps 10 -ts_monitor
641: test:
642: suffix: tut_2
643: nsize: 4
644: args: -ts_max_steps 10 -ts_monitor -snes_monitor -ksp_monitor
646: test:
647: suffix: tut_3
648: nsize: 4
649: args: -ts_max_steps 10 -ts_monitor -M 128
651: TEST*/