1c4762a1bSJed Brown static char help[] = "Model Equations for Advection-Diffusion\n"; 2c4762a1bSJed Brown 3c4762a1bSJed Brown /* 4c4762a1bSJed Brown Page 9, Section 1.2 Model Equations for Advection-Diffusion 5c4762a1bSJed Brown 6c4762a1bSJed Brown u_t = a u_x + d u_xx 7c4762a1bSJed Brown 8c4762a1bSJed Brown The initial conditions used here different then in the book. 9c4762a1bSJed Brown 10c4762a1bSJed Brown */ 11c4762a1bSJed Brown 12c4762a1bSJed Brown /* 13c4762a1bSJed Brown Helpful runtime linear solver options: 14c4762a1bSJed Brown -pc_type mg -da_refine 2 -snes_monitor -ksp_monitor -ts_view (geometric multigrid with three levels) 15c4762a1bSJed Brown 16c4762a1bSJed Brown */ 17c4762a1bSJed Brown 18c4762a1bSJed Brown /* 19c4762a1bSJed Brown Include "petscts.h" so that we can use TS solvers. Note that this file 20c4762a1bSJed Brown automatically includes: 21c4762a1bSJed Brown petscsys.h - base PETSc routines petscvec.h - vectors 22c4762a1bSJed Brown petscmat.h - matrices 23c4762a1bSJed Brown petscis.h - index sets petscksp.h - Krylov subspace methods 24c4762a1bSJed Brown petscviewer.h - viewers petscpc.h - preconditioners 25c4762a1bSJed Brown petscksp.h - linear solvers petscsnes.h - nonlinear solvers 26c4762a1bSJed Brown */ 27c4762a1bSJed Brown 28c4762a1bSJed Brown #include <petscts.h> 29c4762a1bSJed Brown #include <petscdm.h> 30c4762a1bSJed Brown #include <petscdmda.h> 31c4762a1bSJed Brown 32c4762a1bSJed Brown /* 33c4762a1bSJed Brown User-defined application context - contains data needed by the 34c4762a1bSJed Brown application-provided call-back routines. 35c4762a1bSJed Brown */ 36c4762a1bSJed Brown typedef struct { 37c4762a1bSJed Brown PetscScalar a, d; /* advection and diffusion strength */ 38c4762a1bSJed Brown PetscBool upwind; 39c4762a1bSJed Brown } AppCtx; 40c4762a1bSJed Brown 41c4762a1bSJed Brown /* 42c4762a1bSJed Brown User-defined routines 43c4762a1bSJed Brown */ 44c4762a1bSJed Brown extern PetscErrorCode InitialConditions(TS, Vec, AppCtx *); 45c4762a1bSJed Brown extern PetscErrorCode RHSMatrixHeat(TS, PetscReal, Vec, Mat, Mat, void *); 46c4762a1bSJed Brown extern PetscErrorCode Solution(TS, PetscReal, Vec, AppCtx *); 47c4762a1bSJed Brown 48d71ae5a4SJacob Faibussowitsch int main(int argc, char **argv) 49d71ae5a4SJacob Faibussowitsch { 50c4762a1bSJed Brown AppCtx appctx; /* user-defined application context */ 51c4762a1bSJed Brown TS ts; /* timestepping context */ 52c4762a1bSJed Brown Vec U; /* approximate solution vector */ 53c4762a1bSJed Brown PetscReal dt; 54c4762a1bSJed Brown DM da; 55c4762a1bSJed Brown PetscInt M; 56c4762a1bSJed Brown 57c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 58c4762a1bSJed Brown Initialize program and set problem parameters 59c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 60c4762a1bSJed Brown 61327415f7SBarry Smith PetscFunctionBeginUser; 62c8025a54SPierre Jolivet PetscCall(PetscInitialize(&argc, &argv, NULL, help)); 63c4762a1bSJed Brown appctx.a = 1.0; 64c4762a1bSJed Brown appctx.d = 0.0; 659566063dSJacob Faibussowitsch PetscCall(PetscOptionsGetScalar(NULL, NULL, "-a", &appctx.a, NULL)); 669566063dSJacob Faibussowitsch PetscCall(PetscOptionsGetScalar(NULL, NULL, "-d", &appctx.d, NULL)); 67c4762a1bSJed Brown appctx.upwind = PETSC_TRUE; 689566063dSJacob Faibussowitsch PetscCall(PetscOptionsGetBool(NULL, NULL, "-upwind", &appctx.upwind, NULL)); 69c4762a1bSJed Brown 709566063dSJacob Faibussowitsch PetscCall(DMDACreate1d(PETSC_COMM_WORLD, DM_BOUNDARY_PERIODIC, 60, 1, 1, NULL, &da)); 719566063dSJacob Faibussowitsch PetscCall(DMSetFromOptions(da)); 729566063dSJacob Faibussowitsch PetscCall(DMSetUp(da)); 73c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 74c4762a1bSJed Brown Create vector data structures 75c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 76c4762a1bSJed Brown 77c4762a1bSJed Brown /* 78c4762a1bSJed Brown Create vector data structures for approximate and exact solutions 79c4762a1bSJed Brown */ 809566063dSJacob Faibussowitsch PetscCall(DMCreateGlobalVector(da, &U)); 81c4762a1bSJed Brown 82c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 83c4762a1bSJed Brown Create timestepping solver context 84c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 85c4762a1bSJed Brown 869566063dSJacob Faibussowitsch PetscCall(TSCreate(PETSC_COMM_WORLD, &ts)); 879566063dSJacob Faibussowitsch PetscCall(TSSetDM(ts, da)); 88c4762a1bSJed Brown 89c4762a1bSJed Brown /* 90c4762a1bSJed Brown For linear problems with a time-dependent f(U,t) in the equation 91dd8e379bSPierre Jolivet u_t = f(u,t), the user provides the discretized right-hand side 92c4762a1bSJed Brown as a time-dependent matrix. 93c4762a1bSJed Brown */ 949566063dSJacob Faibussowitsch PetscCall(TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx)); 959566063dSJacob Faibussowitsch PetscCall(TSSetRHSJacobian(ts, NULL, NULL, RHSMatrixHeat, &appctx)); 969566063dSJacob Faibussowitsch PetscCall(TSSetSolutionFunction(ts, (PetscErrorCode (*)(TS, PetscReal, Vec, void *))Solution, &appctx)); 97c4762a1bSJed Brown 98c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 99c4762a1bSJed Brown Customize timestepping solver: 100c4762a1bSJed Brown - Set timestepping duration info 101c4762a1bSJed Brown Then set runtime options, which can override these defaults. 102c4762a1bSJed Brown For example, 103c4762a1bSJed Brown -ts_max_steps <maxsteps> -ts_max_time <maxtime> 104c4762a1bSJed Brown to override the defaults set by TSSetMaxSteps()/TSSetMaxTime(). 105c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 106c4762a1bSJed Brown 1079566063dSJacob Faibussowitsch PetscCall(DMDAGetInfo(da, PETSC_IGNORE, &M, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)); 108c4762a1bSJed Brown dt = .48 / (M * M); 1099566063dSJacob Faibussowitsch PetscCall(TSSetTimeStep(ts, dt)); 1109566063dSJacob Faibussowitsch PetscCall(TSSetMaxSteps(ts, 1000)); 1119566063dSJacob Faibussowitsch PetscCall(TSSetMaxTime(ts, 100.0)); 1129566063dSJacob Faibussowitsch PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER)); 1139566063dSJacob Faibussowitsch PetscCall(TSSetType(ts, TSARKIMEX)); 1149566063dSJacob Faibussowitsch PetscCall(TSSetFromOptions(ts)); 115c4762a1bSJed Brown 116c4762a1bSJed Brown /* 117c4762a1bSJed Brown Evaluate initial conditions 118c4762a1bSJed Brown */ 1199566063dSJacob Faibussowitsch PetscCall(InitialConditions(ts, U, &appctx)); 120c4762a1bSJed Brown 121c4762a1bSJed Brown /* 122c4762a1bSJed Brown Run the timestepping solver 123c4762a1bSJed Brown */ 1249566063dSJacob Faibussowitsch PetscCall(TSSolve(ts, U)); 125c4762a1bSJed Brown 126c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 127c4762a1bSJed Brown Free work space. All PETSc objects should be destroyed when they 128c4762a1bSJed Brown are no longer needed. 129c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 130c4762a1bSJed Brown 1319566063dSJacob Faibussowitsch PetscCall(TSDestroy(&ts)); 1329566063dSJacob Faibussowitsch PetscCall(VecDestroy(&U)); 1339566063dSJacob Faibussowitsch PetscCall(DMDestroy(&da)); 134c4762a1bSJed Brown 135c4762a1bSJed Brown /* 136c4762a1bSJed Brown Always call PetscFinalize() before exiting a program. This routine 137c4762a1bSJed Brown - finalizes the PETSc libraries as well as MPI 138c4762a1bSJed Brown - provides summary and diagnostic information if certain runtime 139c4762a1bSJed Brown options are chosen (e.g., -log_view). 140c4762a1bSJed Brown */ 1419566063dSJacob Faibussowitsch PetscCall(PetscFinalize()); 142b122ec5aSJacob Faibussowitsch return 0; 143c4762a1bSJed Brown } 144c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 145c4762a1bSJed Brown /* 146c4762a1bSJed Brown InitialConditions - Computes the solution at the initial time. 147c4762a1bSJed Brown 148c4762a1bSJed Brown Input Parameter: 149c4762a1bSJed Brown u - uninitialized solution vector (global) 150c4762a1bSJed Brown appctx - user-defined application context 151c4762a1bSJed Brown 152c4762a1bSJed Brown Output Parameter: 153c4762a1bSJed Brown u - vector with solution at initial time (global) 154c4762a1bSJed Brown */ 155d71ae5a4SJacob Faibussowitsch PetscErrorCode InitialConditions(TS ts, Vec U, AppCtx *appctx) 156d71ae5a4SJacob Faibussowitsch { 157c4762a1bSJed Brown PetscScalar *u, h; 158c4762a1bSJed Brown PetscInt i, mstart, mend, xm, M; 159c4762a1bSJed Brown DM da; 160c4762a1bSJed Brown 1613ba16761SJacob Faibussowitsch PetscFunctionBeginUser; 1629566063dSJacob Faibussowitsch PetscCall(TSGetDM(ts, &da)); 1639566063dSJacob Faibussowitsch PetscCall(DMDAGetCorners(da, &mstart, 0, 0, &xm, 0, 0)); 1649566063dSJacob Faibussowitsch PetscCall(DMDAGetInfo(da, PETSC_IGNORE, &M, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)); 165c4762a1bSJed Brown h = 1.0 / M; 166c4762a1bSJed Brown mend = mstart + xm; 167c4762a1bSJed Brown /* 168c4762a1bSJed Brown Get a pointer to vector data. 169c4762a1bSJed Brown - For default PETSc vectors, VecGetArray() returns a pointer to 170c4762a1bSJed Brown the data array. Otherwise, the routine is implementation dependent. 171c4762a1bSJed Brown - You MUST call VecRestoreArray() when you no longer need access to 172c4762a1bSJed Brown the array. 173c4762a1bSJed Brown - Note that the Fortran interface to VecGetArray() differs from the 174c4762a1bSJed Brown C version. See the users manual for details. 175c4762a1bSJed Brown */ 1769566063dSJacob Faibussowitsch PetscCall(DMDAVecGetArray(da, U, &u)); 177c4762a1bSJed Brown 178c4762a1bSJed Brown /* 179c4762a1bSJed Brown We initialize the solution array by simply writing the solution 180c4762a1bSJed Brown directly into the array locations. Alternatively, we could use 181c4762a1bSJed Brown VecSetValues() or VecSetValuesLocal(). 182c4762a1bSJed Brown */ 183c4762a1bSJed Brown for (i = mstart; i < mend; i++) u[i] = PetscSinScalar(PETSC_PI * i * 6. * h) + 3. * PetscSinScalar(PETSC_PI * i * 2. * h); 184c4762a1bSJed Brown 185c4762a1bSJed Brown /* 186c4762a1bSJed Brown Restore vector 187c4762a1bSJed Brown */ 1889566063dSJacob Faibussowitsch PetscCall(DMDAVecRestoreArray(da, U, &u)); 1893ba16761SJacob Faibussowitsch PetscFunctionReturn(PETSC_SUCCESS); 190c4762a1bSJed Brown } 191c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 192c4762a1bSJed Brown /* 193c4762a1bSJed Brown Solution - Computes the exact solution at a given time. 194c4762a1bSJed Brown 195c4762a1bSJed Brown Input Parameters: 196c4762a1bSJed Brown t - current time 197c4762a1bSJed Brown solution - vector in which exact solution will be computed 198c4762a1bSJed Brown appctx - user-defined application context 199c4762a1bSJed Brown 200c4762a1bSJed Brown Output Parameter: 201c4762a1bSJed Brown solution - vector with the newly computed exact solution 202c4762a1bSJed Brown */ 203d71ae5a4SJacob Faibussowitsch PetscErrorCode Solution(TS ts, PetscReal t, Vec U, AppCtx *appctx) 204d71ae5a4SJacob Faibussowitsch { 205c4762a1bSJed Brown PetscScalar *u, ex1, ex2, sc1, sc2, h; 206c4762a1bSJed Brown PetscInt i, mstart, mend, xm, M; 207c4762a1bSJed Brown DM da; 208c4762a1bSJed Brown 2093ba16761SJacob Faibussowitsch PetscFunctionBeginUser; 2109566063dSJacob Faibussowitsch PetscCall(TSGetDM(ts, &da)); 2119566063dSJacob Faibussowitsch PetscCall(DMDAGetCorners(da, &mstart, 0, 0, &xm, 0, 0)); 2129566063dSJacob Faibussowitsch PetscCall(DMDAGetInfo(da, PETSC_IGNORE, &M, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)); 213c4762a1bSJed Brown h = 1.0 / M; 214c4762a1bSJed Brown mend = mstart + xm; 215c4762a1bSJed Brown /* 216c4762a1bSJed Brown Get a pointer to vector data. 217c4762a1bSJed Brown */ 2189566063dSJacob Faibussowitsch PetscCall(DMDAVecGetArray(da, U, &u)); 219c4762a1bSJed Brown 220c4762a1bSJed Brown /* 221c4762a1bSJed Brown Simply write the solution directly into the array locations. 222c4762a1bSJed Brown Alternatively, we culd use VecSetValues() or VecSetValuesLocal(). 223c4762a1bSJed Brown */ 224c4762a1bSJed Brown ex1 = PetscExpScalar(-36. * PETSC_PI * PETSC_PI * appctx->d * t); 225c4762a1bSJed Brown ex2 = PetscExpScalar(-4. * PETSC_PI * PETSC_PI * appctx->d * t); 2269371c9d4SSatish Balay sc1 = PETSC_PI * 6. * h; 2279371c9d4SSatish Balay sc2 = PETSC_PI * 2. * h; 228c4762a1bSJed Brown for (i = mstart; i < mend; i++) u[i] = PetscSinScalar(sc1 * (PetscReal)i + appctx->a * PETSC_PI * 6. * t) * ex1 + 3. * PetscSinScalar(sc2 * (PetscReal)i + appctx->a * PETSC_PI * 2. * t) * ex2; 229c4762a1bSJed Brown 230c4762a1bSJed Brown /* 231c4762a1bSJed Brown Restore vector 232c4762a1bSJed Brown */ 2339566063dSJacob Faibussowitsch PetscCall(DMDAVecRestoreArray(da, U, &u)); 2343ba16761SJacob Faibussowitsch PetscFunctionReturn(PETSC_SUCCESS); 235c4762a1bSJed Brown } 236c4762a1bSJed Brown 237c4762a1bSJed Brown /* --------------------------------------------------------------------- */ 238c4762a1bSJed Brown /* 239c4762a1bSJed Brown RHSMatrixHeat - User-provided routine to compute the right-hand-side 240c4762a1bSJed Brown matrix for the heat equation. 241c4762a1bSJed Brown 242c4762a1bSJed Brown Input Parameters: 243c4762a1bSJed Brown ts - the TS context 244c4762a1bSJed Brown t - current time 245c4762a1bSJed Brown global_in - global input vector 246c4762a1bSJed Brown dummy - optional user-defined context, as set by TSetRHSJacobian() 247c4762a1bSJed Brown 248c4762a1bSJed Brown Output Parameters: 249c4762a1bSJed Brown AA - Jacobian matrix 2507addb90fSBarry Smith BB - optionally different matrix used to construct the preconditioner 251c4762a1bSJed Brown 252c4762a1bSJed Brown Notes: 253c4762a1bSJed Brown Recall that MatSetValues() uses 0-based row and column numbers 254c4762a1bSJed Brown in Fortran as well as in C. 255c4762a1bSJed Brown */ 256*2a8381b2SBarry Smith PetscErrorCode RHSMatrixHeat(TS ts, PetscReal t, Vec U, Mat AA, Mat BB, PetscCtx ctx) 257d71ae5a4SJacob Faibussowitsch { 258c4762a1bSJed Brown Mat A = AA; /* Jacobian matrix */ 259c4762a1bSJed Brown AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */ 260c4762a1bSJed Brown PetscInt mstart, mend; 261c4762a1bSJed Brown PetscInt i, idx[3], M, xm; 262c4762a1bSJed Brown PetscScalar v[3], h; 263c4762a1bSJed Brown DM da; 264c4762a1bSJed Brown 2653ba16761SJacob Faibussowitsch PetscFunctionBeginUser; 2669566063dSJacob Faibussowitsch PetscCall(TSGetDM(ts, &da)); 2679566063dSJacob Faibussowitsch PetscCall(DMDAGetInfo(da, 0, &M, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0)); 2689566063dSJacob Faibussowitsch PetscCall(DMDAGetCorners(da, &mstart, 0, 0, &xm, 0, 0)); 269c4762a1bSJed Brown h = 1.0 / M; 270c4762a1bSJed Brown mend = mstart + xm; 271c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 272c4762a1bSJed Brown Compute entries for the locally owned part of the matrix 273c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 274c4762a1bSJed Brown /* 275c4762a1bSJed Brown Set matrix rows corresponding to boundary data 276c4762a1bSJed Brown */ 277c4762a1bSJed Brown 278c4762a1bSJed Brown /* diffusion */ 279c4762a1bSJed Brown v[0] = appctx->d / (h * h); 280c4762a1bSJed Brown v[1] = -2.0 * appctx->d / (h * h); 281c4762a1bSJed Brown v[2] = appctx->d / (h * h); 282c4762a1bSJed Brown if (!mstart) { 2839371c9d4SSatish Balay idx[0] = M - 1; 2849371c9d4SSatish Balay idx[1] = 0; 2859371c9d4SSatish Balay idx[2] = 1; 2869566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mstart, 3, idx, v, INSERT_VALUES)); 287c4762a1bSJed Brown mstart++; 288c4762a1bSJed Brown } 289c4762a1bSJed Brown 290c4762a1bSJed Brown if (mend == M) { 291c4762a1bSJed Brown mend--; 2929371c9d4SSatish Balay idx[0] = M - 2; 2939371c9d4SSatish Balay idx[1] = M - 1; 2949371c9d4SSatish Balay idx[2] = 0; 2959566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mend, 3, idx, v, INSERT_VALUES)); 296c4762a1bSJed Brown } 297c4762a1bSJed Brown 298c4762a1bSJed Brown /* 299c4762a1bSJed Brown Set matrix rows corresponding to interior data. We construct the 300c4762a1bSJed Brown matrix one row at a time. 301c4762a1bSJed Brown */ 302c4762a1bSJed Brown for (i = mstart; i < mend; i++) { 3039371c9d4SSatish Balay idx[0] = i - 1; 3049371c9d4SSatish Balay idx[1] = i; 3059371c9d4SSatish Balay idx[2] = i + 1; 3069566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &i, 3, idx, v, INSERT_VALUES)); 307c4762a1bSJed Brown } 3089566063dSJacob Faibussowitsch PetscCall(MatAssemblyBegin(A, MAT_FLUSH_ASSEMBLY)); 3099566063dSJacob Faibussowitsch PetscCall(MatAssemblyEnd(A, MAT_FLUSH_ASSEMBLY)); 310c4762a1bSJed Brown 3119566063dSJacob Faibussowitsch PetscCall(DMDAGetCorners(da, &mstart, 0, 0, &xm, 0, 0)); 312c4762a1bSJed Brown mend = mstart + xm; 313c4762a1bSJed Brown if (!appctx->upwind) { 314c4762a1bSJed Brown /* advection -- centered differencing */ 315c4762a1bSJed Brown v[0] = -.5 * appctx->a / (h); 316c4762a1bSJed Brown v[1] = .5 * appctx->a / (h); 317c4762a1bSJed Brown if (!mstart) { 3189371c9d4SSatish Balay idx[0] = M - 1; 3199371c9d4SSatish Balay idx[1] = 1; 3209566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mstart, 2, idx, v, ADD_VALUES)); 321c4762a1bSJed Brown mstart++; 322c4762a1bSJed Brown } 323c4762a1bSJed Brown 324c4762a1bSJed Brown if (mend == M) { 325c4762a1bSJed Brown mend--; 3269371c9d4SSatish Balay idx[0] = M - 2; 3279371c9d4SSatish Balay idx[1] = 0; 3289566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mend, 2, idx, v, ADD_VALUES)); 329c4762a1bSJed Brown } 330c4762a1bSJed Brown 331c4762a1bSJed Brown for (i = mstart; i < mend; i++) { 3329371c9d4SSatish Balay idx[0] = i - 1; 3339371c9d4SSatish Balay idx[1] = i + 1; 3349566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &i, 2, idx, v, ADD_VALUES)); 335c4762a1bSJed Brown } 336c4762a1bSJed Brown } else { 337c4762a1bSJed Brown /* advection -- upwinding */ 338c4762a1bSJed Brown v[0] = -appctx->a / (h); 339c4762a1bSJed Brown v[1] = appctx->a / (h); 340c4762a1bSJed Brown if (!mstart) { 3419371c9d4SSatish Balay idx[0] = 0; 3429371c9d4SSatish Balay idx[1] = 1; 3439566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mstart, 2, idx, v, ADD_VALUES)); 344c4762a1bSJed Brown mstart++; 345c4762a1bSJed Brown } 346c4762a1bSJed Brown 347c4762a1bSJed Brown if (mend == M) { 348c4762a1bSJed Brown mend--; 3499371c9d4SSatish Balay idx[0] = M - 1; 3509371c9d4SSatish Balay idx[1] = 0; 3519566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &mend, 2, idx, v, ADD_VALUES)); 352c4762a1bSJed Brown } 353c4762a1bSJed Brown 354c4762a1bSJed Brown for (i = mstart; i < mend; i++) { 3559371c9d4SSatish Balay idx[0] = i; 3569371c9d4SSatish Balay idx[1] = i + 1; 3579566063dSJacob Faibussowitsch PetscCall(MatSetValues(A, 1, &i, 2, idx, v, ADD_VALUES)); 358c4762a1bSJed Brown } 359c4762a1bSJed Brown } 360c4762a1bSJed Brown 361c4762a1bSJed Brown /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 362c4762a1bSJed Brown Complete the matrix assembly process and set some options 363c4762a1bSJed Brown - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 364c4762a1bSJed Brown /* 365c4762a1bSJed Brown Assemble matrix, using the 2-step process: 366c4762a1bSJed Brown MatAssemblyBegin(), MatAssemblyEnd() 367c4762a1bSJed Brown Computations can be done while messages are in transition 368c4762a1bSJed Brown by placing code between these two statements. 369c4762a1bSJed Brown */ 3709566063dSJacob Faibussowitsch PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 3719566063dSJacob Faibussowitsch PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 372c4762a1bSJed Brown 373c4762a1bSJed Brown /* 374c4762a1bSJed Brown Set and option to indicate that we will never add a new nonzero location 375c4762a1bSJed Brown to the matrix. If we do, it will generate an error. 376c4762a1bSJed Brown */ 3779566063dSJacob Faibussowitsch PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); 3783ba16761SJacob Faibussowitsch PetscFunctionReturn(PETSC_SUCCESS); 379c4762a1bSJed Brown } 380c4762a1bSJed Brown 381c4762a1bSJed Brown /*TEST 382c4762a1bSJed Brown 383c4762a1bSJed Brown test: 384c4762a1bSJed Brown args: -pc_type mg -da_refine 2 -ts_view -ts_monitor -ts_max_time .3 -mg_levels_ksp_max_it 3 385c4762a1bSJed Brown requires: double 386c2eed0edSBarry Smith filter: grep -v "total number of" 387c4762a1bSJed Brown 388c4762a1bSJed Brown test: 389c4762a1bSJed Brown suffix: 2 390c4762a1bSJed Brown args: -pc_type mg -da_refine 2 -ts_view -ts_monitor_draw_solution -ts_monitor -ts_max_time .3 -mg_levels_ksp_max_it 3 391c4762a1bSJed Brown requires: x 392c4762a1bSJed Brown output_file: output/ex3_1.out 393c4762a1bSJed Brown requires: double 394c2eed0edSBarry Smith filter: grep -v "total number of" 395c4762a1bSJed Brown 396c4762a1bSJed Brown TEST*/ 397