1 2 static char help[] = "Solves a simple time-dependent linear PDE (the heat equation).\n\ 3 Input parameters include:\n\ 4 -m <points>, where <points> = number of grid points\n\ 5 -time_dependent_rhs : Treat the problem as having a time-dependent right-hand side\n\ 6 -debug : Activate debugging printouts\n\ 7 -nox : Deactivate x-window graphics\n\n"; 8 9 /* ------------------------------------------------------------------------ 10 11 This program solves the one-dimensional heat equation (also called the 12 diffusion equation), 13 u_t = u_xx, 14 on the domain 0 <= x <= 1, with the boundary conditions 15 u(t,0) = 1, u(t,1) = 1, 16 and the initial condition 17 u(0,x) = cos(6*pi*x) + 3*cos(2*pi*x). 18 This is a linear, second-order, parabolic equation. 19 20 We discretize the right-hand side using finite differences with 21 uniform grid spacing h: 22 u_xx = (u_{i+1} - 2u_{i} + u_{i-1})/(h^2) 23 We then demonstrate time evolution using the various TS methods by 24 running the program via 25 ex3 -ts_type <timestepping solver> 26 27 We compare the approximate solution with the exact solution, given by 28 u_exact(x,t) = exp(-36*pi*pi*t) * cos(6*pi*x) + 29 3*exp(-4*pi*pi*t) * cos(2*pi*x) 30 31 Notes: 32 This code demonstrates the TS solver interface to two variants of 33 linear problems, u_t = f(u,t), namely 34 - time-dependent f: f(u,t) is a function of t 35 - time-independent f: f(u,t) is simply just f(u) 36 37 The parallel version of this code is ts/tutorials/ex4.c 38 39 ------------------------------------------------------------------------- */ 40 41 /* 42 Include "petscts.h" so that we can use TS solvers. Note that this file 43 automatically includes: 44 petscsys.h - base PETSc routines petscvec.h - vectors 45 petscmat.h - matrices 46 petscis.h - index sets petscksp.h - Krylov subspace methods 47 petscviewer.h - viewers petscpc.h - preconditioners 48 petscksp.h - linear solvers petscsnes.h - nonlinear solvers 49 */ 50 #include <petscts.h> 51 #include <petscdraw.h> 52 53 /* 54 User-defined application context - contains data needed by the 55 application-provided call-back routines. 56 */ 57 typedef struct { 58 Vec solution; /* global exact solution vector */ 59 PetscInt m; /* total number of grid points */ 60 PetscReal h; /* mesh width h = 1/(m-1) */ 61 PetscBool debug; /* flag (1 indicates activation of debugging printouts) */ 62 PetscViewer viewer1, viewer2; /* viewers for the solution and error */ 63 PetscReal norm_2, norm_max; /* error norms */ 64 } AppCtx; 65 66 /* 67 User-defined routines 68 */ 69 extern PetscErrorCode InitialConditions(Vec, AppCtx *); 70 extern PetscErrorCode RHSMatrixHeat(TS, PetscReal, Vec, Mat, Mat, void *); 71 extern PetscErrorCode Monitor(TS, PetscInt, PetscReal, Vec, void *); 72 extern PetscErrorCode ExactSolution(PetscReal, Vec, AppCtx *); 73 74 int main(int argc, char **argv) { 75 AppCtx appctx; /* user-defined application context */ 76 TS ts; /* timestepping context */ 77 Mat A; /* matrix data structure */ 78 Vec u; /* approximate solution vector */ 79 PetscReal time_total_max = 100.0; /* default max total time */ 80 PetscInt time_steps_max = 100; /* default max timesteps */ 81 PetscDraw draw; /* drawing context */ 82 PetscInt steps, m; 83 PetscMPIInt size; 84 PetscBool flg; 85 PetscReal dt, ftime; 86 87 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 88 Initialize program and set problem parameters 89 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 90 91 PetscFunctionBeginUser; 92 PetscCall(PetscInitialize(&argc, &argv, (char *)0, help)); 93 PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size)); 94 PetscCheck(size == 1, PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This is a uniprocessor example only!"); 95 96 m = 60; 97 PetscCall(PetscOptionsGetInt(NULL, NULL, "-m", &m, NULL)); 98 PetscCall(PetscOptionsHasName(NULL, NULL, "-debug", &appctx.debug)); 99 appctx.m = m; 100 appctx.h = 1.0 / (m - 1.0); 101 appctx.norm_2 = 0.0; 102 appctx.norm_max = 0.0; 103 104 PetscCall(PetscPrintf(PETSC_COMM_SELF, "Solving a linear TS problem on 1 processor\n")); 105 106 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 107 Create vector data structures 108 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 109 110 /* 111 Create vector data structures for approximate and exact solutions 112 */ 113 PetscCall(VecCreateSeq(PETSC_COMM_SELF, m, &u)); 114 PetscCall(VecDuplicate(u, &appctx.solution)); 115 116 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 117 Set up displays to show graphs of the solution and error 118 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 119 120 PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 380, 400, 160, &appctx.viewer1)); 121 PetscCall(PetscViewerDrawGetDraw(appctx.viewer1, 0, &draw)); 122 PetscCall(PetscDrawSetDoubleBuffer(draw)); 123 PetscCall(PetscViewerDrawOpen(PETSC_COMM_SELF, 0, "", 80, 0, 400, 160, &appctx.viewer2)); 124 PetscCall(PetscViewerDrawGetDraw(appctx.viewer2, 0, &draw)); 125 PetscCall(PetscDrawSetDoubleBuffer(draw)); 126 127 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 128 Create timestepping solver context 129 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 130 131 PetscCall(TSCreate(PETSC_COMM_SELF, &ts)); 132 PetscCall(TSSetProblemType(ts, TS_LINEAR)); 133 134 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 135 Set optional user-defined monitoring routine 136 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 137 138 PetscCall(TSMonitorSet(ts, Monitor, &appctx, NULL)); 139 140 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 141 142 Create matrix data structure; set matrix evaluation routine. 143 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 144 145 PetscCall(MatCreate(PETSC_COMM_SELF, &A)); 146 PetscCall(MatSetSizes(A, PETSC_DECIDE, PETSC_DECIDE, m, m)); 147 PetscCall(MatSetFromOptions(A)); 148 PetscCall(MatSetUp(A)); 149 150 PetscCall(PetscOptionsHasName(NULL, NULL, "-time_dependent_rhs", &flg)); 151 if (flg) { 152 /* 153 For linear problems with a time-dependent f(u,t) in the equation 154 u_t = f(u,t), the user provides the discretized right-hand-side 155 as a time-dependent matrix. 156 */ 157 PetscCall(TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx)); 158 PetscCall(TSSetRHSJacobian(ts, A, A, RHSMatrixHeat, &appctx)); 159 } else { 160 /* 161 For linear problems with a time-independent f(u) in the equation 162 u_t = f(u), the user provides the discretized right-hand-side 163 as a matrix only once, and then sets a null matrix evaluation 164 routine. 165 */ 166 PetscCall(RHSMatrixHeat(ts, 0.0, u, A, A, &appctx)); 167 PetscCall(TSSetRHSFunction(ts, NULL, TSComputeRHSFunctionLinear, &appctx)); 168 PetscCall(TSSetRHSJacobian(ts, A, A, TSComputeRHSJacobianConstant, &appctx)); 169 } 170 171 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 172 Set solution vector and initial timestep 173 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 174 175 dt = appctx.h * appctx.h / 2.0; 176 PetscCall(TSSetTimeStep(ts, dt)); 177 PetscCall(TSSetSolution(ts, u)); 178 179 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 180 Customize timestepping solver: 181 - Set the solution method to be the Backward Euler method. 182 - Set timestepping duration info 183 Then set runtime options, which can override these defaults. 184 For example, 185 -ts_max_steps <maxsteps> -ts_max_time <maxtime> 186 to override the defaults set by TSSetMaxSteps()/TSSetMaxTime(). 187 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 188 189 PetscCall(TSSetMaxSteps(ts, time_steps_max)); 190 PetscCall(TSSetMaxTime(ts, time_total_max)); 191 PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_STEPOVER)); 192 PetscCall(TSSetFromOptions(ts)); 193 194 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 195 Solve the problem 196 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 197 198 /* 199 Evaluate initial conditions 200 */ 201 PetscCall(InitialConditions(u, &appctx)); 202 203 /* 204 Run the timestepping solver 205 */ 206 PetscCall(TSSolve(ts, u)); 207 PetscCall(TSGetSolveTime(ts, &ftime)); 208 PetscCall(TSGetStepNumber(ts, &steps)); 209 210 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 211 View timestepping solver info 212 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 213 214 PetscCall(PetscPrintf(PETSC_COMM_SELF, "avg. error (2 norm) = %g, avg. error (max norm) = %g\n", (double)(appctx.norm_2 / steps), (double)(appctx.norm_max / steps))); 215 PetscCall(TSView(ts, PETSC_VIEWER_STDOUT_SELF)); 216 217 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 218 Free work space. All PETSc objects should be destroyed when they 219 are no longer needed. 220 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 221 222 PetscCall(TSDestroy(&ts)); 223 PetscCall(MatDestroy(&A)); 224 PetscCall(VecDestroy(&u)); 225 PetscCall(PetscViewerDestroy(&appctx.viewer1)); 226 PetscCall(PetscViewerDestroy(&appctx.viewer2)); 227 PetscCall(VecDestroy(&appctx.solution)); 228 229 /* 230 Always call PetscFinalize() before exiting a program. This routine 231 - finalizes the PETSc libraries as well as MPI 232 - provides summary and diagnostic information if certain runtime 233 options are chosen (e.g., -log_view). 234 */ 235 PetscCall(PetscFinalize()); 236 return 0; 237 } 238 /* --------------------------------------------------------------------- */ 239 /* 240 InitialConditions - Computes the solution at the initial time. 241 242 Input Parameter: 243 u - uninitialized solution vector (global) 244 appctx - user-defined application context 245 246 Output Parameter: 247 u - vector with solution at initial time (global) 248 */ 249 PetscErrorCode InitialConditions(Vec u, AppCtx *appctx) { 250 PetscScalar *u_localptr, h = appctx->h; 251 PetscInt i; 252 253 /* 254 Get a pointer to vector data. 255 - For default PETSc vectors, VecGetArray() returns a pointer to 256 the data array. Otherwise, the routine is implementation dependent. 257 - You MUST call VecRestoreArray() when you no longer need access to 258 the array. 259 - Note that the Fortran interface to VecGetArray() differs from the 260 C version. See the users manual for details. 261 */ 262 PetscCall(VecGetArray(u, &u_localptr)); 263 264 /* 265 We initialize the solution array by simply writing the solution 266 directly into the array locations. Alternatively, we could use 267 VecSetValues() or VecSetValuesLocal(). 268 */ 269 for (i = 0; i < appctx->m; i++) u_localptr[i] = PetscCosScalar(PETSC_PI * i * 6. * h) + 3. * PetscCosScalar(PETSC_PI * i * 2. * h); 270 271 /* 272 Restore vector 273 */ 274 PetscCall(VecRestoreArray(u, &u_localptr)); 275 276 /* 277 Print debugging information if desired 278 */ 279 if (appctx->debug) { 280 printf("initial guess vector\n"); 281 PetscCall(VecView(u, PETSC_VIEWER_STDOUT_SELF)); 282 } 283 284 return 0; 285 } 286 /* --------------------------------------------------------------------- */ 287 /* 288 ExactSolution - Computes the exact solution at a given time. 289 290 Input Parameters: 291 t - current time 292 solution - vector in which exact solution will be computed 293 appctx - user-defined application context 294 295 Output Parameter: 296 solution - vector with the newly computed exact solution 297 */ 298 PetscErrorCode ExactSolution(PetscReal t, Vec solution, AppCtx *appctx) { 299 PetscScalar *s_localptr, h = appctx->h, ex1, ex2, sc1, sc2, tc = t; 300 PetscInt i; 301 302 /* 303 Get a pointer to vector data. 304 */ 305 PetscCall(VecGetArray(solution, &s_localptr)); 306 307 /* 308 Simply write the solution directly into the array locations. 309 Alternatively, we culd use VecSetValues() or VecSetValuesLocal(). 310 */ 311 ex1 = PetscExpScalar(-36. * PETSC_PI * PETSC_PI * tc); 312 ex2 = PetscExpScalar(-4. * PETSC_PI * PETSC_PI * tc); 313 sc1 = PETSC_PI * 6. * h; 314 sc2 = PETSC_PI * 2. * h; 315 for (i = 0; i < appctx->m; i++) s_localptr[i] = PetscCosScalar(sc1 * (PetscReal)i) * ex1 + 3. * PetscCosScalar(sc2 * (PetscReal)i) * ex2; 316 317 /* 318 Restore vector 319 */ 320 PetscCall(VecRestoreArray(solution, &s_localptr)); 321 return 0; 322 } 323 /* --------------------------------------------------------------------- */ 324 /* 325 Monitor - User-provided routine to monitor the solution computed at 326 each timestep. This example plots the solution and computes the 327 error in two different norms. 328 329 Input Parameters: 330 ts - the timestep context 331 step - the count of the current step (with 0 meaning the 332 initial condition) 333 time - the current time 334 u - the solution at this timestep 335 ctx - the user-provided context for this monitoring routine. 336 In this case we use the application context which contains 337 information about the problem size, workspace and the exact 338 solution. 339 */ 340 PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal time, Vec u, void *ctx) { 341 AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */ 342 PetscReal norm_2, norm_max; 343 344 /* 345 View a graph of the current iterate 346 */ 347 PetscCall(VecView(u, appctx->viewer2)); 348 349 /* 350 Compute the exact solution 351 */ 352 PetscCall(ExactSolution(time, appctx->solution, appctx)); 353 354 /* 355 Print debugging information if desired 356 */ 357 if (appctx->debug) { 358 printf("Computed solution vector\n"); 359 PetscCall(VecView(u, PETSC_VIEWER_STDOUT_SELF)); 360 printf("Exact solution vector\n"); 361 PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF)); 362 } 363 364 /* 365 Compute the 2-norm and max-norm of the error 366 */ 367 PetscCall(VecAXPY(appctx->solution, -1.0, u)); 368 PetscCall(VecNorm(appctx->solution, NORM_2, &norm_2)); 369 norm_2 = PetscSqrtReal(appctx->h) * norm_2; 370 PetscCall(VecNorm(appctx->solution, NORM_MAX, &norm_max)); 371 if (norm_2 < 1e-14) norm_2 = 0; 372 if (norm_max < 1e-14) norm_max = 0; 373 374 PetscCall(PetscPrintf(PETSC_COMM_WORLD, "Timestep %" PetscInt_FMT ": time = %g, 2-norm error = %g, max norm error = %g\n", step, (double)time, (double)norm_2, (double)norm_max)); 375 appctx->norm_2 += norm_2; 376 appctx->norm_max += norm_max; 377 378 /* 379 View a graph of the error 380 */ 381 PetscCall(VecView(appctx->solution, appctx->viewer1)); 382 383 /* 384 Print debugging information if desired 385 */ 386 if (appctx->debug) { 387 printf("Error vector\n"); 388 PetscCall(VecView(appctx->solution, PETSC_VIEWER_STDOUT_SELF)); 389 } 390 391 return 0; 392 } 393 /* --------------------------------------------------------------------- */ 394 /* 395 RHSMatrixHeat - User-provided routine to compute the right-hand-side 396 matrix for the heat equation. 397 398 Input Parameters: 399 ts - the TS context 400 t - current time 401 global_in - global input vector 402 dummy - optional user-defined context, as set by TSetRHSJacobian() 403 404 Output Parameters: 405 AA - Jacobian matrix 406 BB - optionally different preconditioning matrix 407 str - flag indicating matrix structure 408 409 Notes: 410 Recall that MatSetValues() uses 0-based row and column numbers 411 in Fortran as well as in C. 412 */ 413 PetscErrorCode RHSMatrixHeat(TS ts, PetscReal t, Vec X, Mat AA, Mat BB, void *ctx) { 414 Mat A = AA; /* Jacobian matrix */ 415 AppCtx *appctx = (AppCtx *)ctx; /* user-defined application context */ 416 PetscInt mstart = 0; 417 PetscInt mend = appctx->m; 418 PetscInt i, idx[3]; 419 PetscScalar v[3], stwo = -2. / (appctx->h * appctx->h), sone = -.5 * stwo; 420 421 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 422 Compute entries for the locally owned part of the matrix 423 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 424 /* 425 Set matrix rows corresponding to boundary data 426 */ 427 428 mstart = 0; 429 v[0] = 1.0; 430 PetscCall(MatSetValues(A, 1, &mstart, 1, &mstart, v, INSERT_VALUES)); 431 mstart++; 432 433 mend--; 434 v[0] = 1.0; 435 PetscCall(MatSetValues(A, 1, &mend, 1, &mend, v, INSERT_VALUES)); 436 437 /* 438 Set matrix rows corresponding to interior data. We construct the 439 matrix one row at a time. 440 */ 441 v[0] = sone; 442 v[1] = stwo; 443 v[2] = sone; 444 for (i = mstart; i < mend; i++) { 445 idx[0] = i - 1; 446 idx[1] = i; 447 idx[2] = i + 1; 448 PetscCall(MatSetValues(A, 1, &i, 3, idx, v, INSERT_VALUES)); 449 } 450 451 /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 452 Complete the matrix assembly process and set some options 453 - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */ 454 /* 455 Assemble matrix, using the 2-step process: 456 MatAssemblyBegin(), MatAssemblyEnd() 457 Computations can be done while messages are in transition 458 by placing code between these two statements. 459 */ 460 PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); 461 PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); 462 463 /* 464 Set and option to indicate that we will never add a new nonzero location 465 to the matrix. If we do, it will generate an error. 466 */ 467 PetscCall(MatSetOption(A, MAT_NEW_NONZERO_LOCATION_ERR, PETSC_TRUE)); 468 469 return 0; 470 } 471 472 /*TEST 473 474 test: 475 requires: x 476 477 test: 478 suffix: nox 479 args: -nox 480 481 TEST*/ 482