1 2 #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/ 3 #include <petscdm.h> 4 5 static const PetscInt TSEIMEXDefault = 3; 6 7 typedef struct { 8 PetscInt row_ind; /* Return the term T[row_ind][col_ind] */ 9 PetscInt col_ind; /* Return the term T[row_ind][col_ind] */ 10 PetscInt nstages; /* Numbers of stages in current scheme */ 11 PetscInt max_rows; /* Maximum number of rows */ 12 PetscInt *N; /* Harmonic sequence N[max_rows] */ 13 Vec Y; /* States computed during the step, used to complete the step */ 14 Vec Z; /* For shift*(Y-Z) */ 15 Vec *T; /* Working table, size determined by nstages */ 16 Vec YdotRHS; /* f(x) Work vector holding YdotRHS during residual evaluation */ 17 Vec YdotI; /* xdot-g(x) Work vector holding YdotI = G(t,x,xdot) when xdot =0 */ 18 Vec Ydot; /* f(x)+g(x) Work vector */ 19 Vec VecSolPrev; /* Work vector holding the solution from the previous step (used for interpolation) */ 20 PetscReal shift; 21 PetscReal ctime; 22 PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */ 23 PetscBool ord_adapt; /* order adapativity */ 24 TSStepStatus status; 25 } TS_EIMEX; 26 27 /* This function is pure */ 28 static PetscInt Map(PetscInt i, PetscInt j, PetscInt s) 29 { 30 return ((2 * s - j + 1) * j / 2 + i - j); 31 } 32 33 static PetscErrorCode TSEvaluateStep_EIMEX(TS ts, PetscInt order, Vec X, PetscBool *done) 34 { 35 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 36 const PetscInt ns = ext->nstages; 37 PetscFunctionBegin; 38 PetscCall(VecCopy(ext->T[Map(ext->row_ind, ext->col_ind, ns)], X)); 39 PetscFunctionReturn(PETSC_SUCCESS); 40 } 41 42 static PetscErrorCode TSStage_EIMEX(TS ts, PetscInt istage) 43 { 44 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 45 PetscReal h; 46 Vec Y = ext->Y, Z = ext->Z; 47 SNES snes; 48 TSAdapt adapt; 49 PetscInt i, its, lits; 50 PetscBool accept; 51 52 PetscFunctionBegin; 53 PetscCall(TSGetSNES(ts, &snes)); 54 h = ts->time_step / ext->N[istage]; /* step size for the istage-th stage */ 55 ext->shift = 1. / h; 56 PetscCall(SNESSetLagJacobian(snes, -2)); /* Recompute the Jacobian on this solve, but not again */ 57 PetscCall(VecCopy(ext->VecSolPrev, Y)); /* Take the previous solution as initial step */ 58 59 for (i = 0; i < ext->N[istage]; i++) { 60 ext->ctime = ts->ptime + h * i; 61 PetscCall(VecCopy(Y, Z)); /* Save the solution of the previous substep */ 62 PetscCall(SNESSolve(snes, NULL, Y)); 63 PetscCall(SNESGetIterationNumber(snes, &its)); 64 PetscCall(SNESGetLinearSolveIterations(snes, &lits)); 65 ts->snes_its += its; 66 ts->ksp_its += lits; 67 PetscCall(TSGetAdapt(ts, &adapt)); 68 PetscCall(TSAdaptCheckStage(adapt, ts, ext->ctime, Y, &accept)); 69 } 70 PetscFunctionReturn(PETSC_SUCCESS); 71 } 72 73 static PetscErrorCode TSStep_EIMEX(TS ts) 74 { 75 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 76 const PetscInt ns = ext->nstages; 77 Vec *T = ext->T, Y = ext->Y; 78 SNES snes; 79 PetscInt i, j; 80 PetscBool accept = PETSC_FALSE; 81 PetscReal alpha, local_error, local_error_a, local_error_r; 82 83 PetscFunctionBegin; 84 PetscCall(TSGetSNES(ts, &snes)); 85 PetscCall(SNESSetType(snes, "ksponly")); 86 ext->status = TS_STEP_INCOMPLETE; 87 88 PetscCall(VecCopy(ts->vec_sol, ext->VecSolPrev)); 89 90 /* Apply n_j steps of the base method to obtain solutions of T(j,1),1<=j<=s */ 91 for (j = 0; j < ns; j++) { 92 PetscCall(TSStage_EIMEX(ts, j)); 93 PetscCall(VecCopy(Y, T[j])); 94 } 95 96 for (i = 1; i < ns; i++) { 97 for (j = i; j < ns; j++) { 98 alpha = -(PetscReal)ext->N[j] / ext->N[j - i]; 99 PetscCall(VecAXPBYPCZ(T[Map(j, i, ns)], alpha, 1.0, 0, T[Map(j, i - 1, ns)], T[Map(j - 1, i - 1, ns)])); /* T[j][i]=alpha*T[j][i-1]+T[j-1][i-1] */ 100 alpha = 1.0 / (1.0 + alpha); 101 PetscCall(VecScale(T[Map(j, i, ns)], alpha)); 102 } 103 } 104 105 PetscCall(TSEvaluateStep(ts, ns, ts->vec_sol, NULL)); /*update ts solution */ 106 107 if (ext->ord_adapt && ext->nstages < ext->max_rows) { 108 accept = PETSC_FALSE; 109 while (!accept && ext->nstages < ext->max_rows) { 110 PetscCall(TSErrorWeightedNorm(ts, ts->vec_sol, T[Map(ext->nstages - 1, ext->nstages - 2, ext->nstages)], ts->adapt->wnormtype, &local_error, &local_error_a, &local_error_r)); 111 accept = (local_error < 1.0) ? PETSC_TRUE : PETSC_FALSE; 112 113 if (!accept) { /* add one more stage*/ 114 PetscCall(TSStage_EIMEX(ts, ext->nstages)); 115 ext->nstages++; 116 ext->row_ind++; 117 ext->col_ind++; 118 /*T table need to be recycled*/ 119 PetscCall(VecDuplicateVecs(ts->vec_sol, (1 + ext->nstages) * ext->nstages / 2, &ext->T)); 120 for (i = 0; i < ext->nstages - 1; i++) { 121 for (j = 0; j <= i; j++) PetscCall(VecCopy(T[Map(i, j, ext->nstages - 1)], ext->T[Map(i, j, ext->nstages)])); 122 } 123 PetscCall(VecDestroyVecs(ext->nstages * (ext->nstages - 1) / 2, &T)); 124 T = ext->T; /*reset the pointer*/ 125 /*recycling finished, store the new solution*/ 126 PetscCall(VecCopy(Y, T[ext->nstages - 1])); 127 /*extrapolation for the newly added stage*/ 128 for (i = 1; i < ext->nstages; i++) { 129 alpha = -(PetscReal)ext->N[ext->nstages - 1] / ext->N[ext->nstages - 1 - i]; 130 PetscCall(VecAXPBYPCZ(T[Map(ext->nstages - 1, i, ext->nstages)], alpha, 1.0, 0, T[Map(ext->nstages - 1, i - 1, ext->nstages)], T[Map(ext->nstages - 1 - 1, i - 1, ext->nstages)])); /*T[ext->nstages-1][i]=alpha*T[ext->nstages-1][i-1]+T[ext->nstages-1-1][i-1]*/ 131 alpha = 1.0 / (1.0 + alpha); 132 PetscCall(VecScale(T[Map(ext->nstages - 1, i, ext->nstages)], alpha)); 133 } 134 /*update ts solution */ 135 PetscCall(TSEvaluateStep(ts, ext->nstages, ts->vec_sol, NULL)); 136 } /*end if !accept*/ 137 } /*end while*/ 138 139 if (ext->nstages == ext->max_rows) PetscCall(PetscInfo(ts, "Max number of rows has been used\n")); 140 } /*end if ext->ord_adapt*/ 141 ts->ptime += ts->time_step; 142 ext->status = TS_STEP_COMPLETE; 143 144 if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED; 145 PetscFunctionReturn(PETSC_SUCCESS); 146 } 147 148 /* cubic Hermit spline */ 149 static PetscErrorCode TSInterpolate_EIMEX(TS ts, PetscReal itime, Vec X) 150 { 151 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 152 PetscReal t, a, b; 153 Vec Y0 = ext->VecSolPrev, Y1 = ext->Y, Ydot = ext->Ydot, YdotI = ext->YdotI; 154 const PetscReal h = ts->ptime - ts->ptime_prev; 155 PetscFunctionBegin; 156 t = (itime - ts->ptime + h) / h; 157 /* YdotI = -f(x)-g(x) */ 158 159 PetscCall(VecZeroEntries(Ydot)); 160 PetscCall(TSComputeIFunction(ts, ts->ptime - h, Y0, Ydot, YdotI, PETSC_FALSE)); 161 162 a = 2.0 * t * t * t - 3.0 * t * t + 1.0; 163 b = -(t * t * t - 2.0 * t * t + t) * h; 164 PetscCall(VecAXPBYPCZ(X, a, b, 0.0, Y0, YdotI)); 165 166 PetscCall(TSComputeIFunction(ts, ts->ptime, Y1, Ydot, YdotI, PETSC_FALSE)); 167 a = -2.0 * t * t * t + 3.0 * t * t; 168 b = -(t * t * t - t * t) * h; 169 PetscCall(VecAXPBYPCZ(X, a, b, 1.0, Y1, YdotI)); 170 171 PetscFunctionReturn(PETSC_SUCCESS); 172 } 173 174 static PetscErrorCode TSReset_EIMEX(TS ts) 175 { 176 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 177 PetscInt ns; 178 179 PetscFunctionBegin; 180 ns = ext->nstages; 181 PetscCall(VecDestroyVecs((1 + ns) * ns / 2, &ext->T)); 182 PetscCall(VecDestroy(&ext->Y)); 183 PetscCall(VecDestroy(&ext->Z)); 184 PetscCall(VecDestroy(&ext->YdotRHS)); 185 PetscCall(VecDestroy(&ext->YdotI)); 186 PetscCall(VecDestroy(&ext->Ydot)); 187 PetscCall(VecDestroy(&ext->VecSolPrev)); 188 PetscCall(PetscFree(ext->N)); 189 PetscFunctionReturn(PETSC_SUCCESS); 190 } 191 192 static PetscErrorCode TSDestroy_EIMEX(TS ts) 193 { 194 PetscFunctionBegin; 195 PetscCall(TSReset_EIMEX(ts)); 196 PetscCall(PetscFree(ts->data)); 197 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetMaxRows_C", NULL)); 198 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetRowCol_C", NULL)); 199 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetOrdAdapt_C", NULL)); 200 PetscFunctionReturn(PETSC_SUCCESS); 201 } 202 203 static PetscErrorCode TSEIMEXGetVecs(TS ts, DM dm, Vec *Z, Vec *Ydot, Vec *YdotI, Vec *YdotRHS) 204 { 205 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 206 207 PetscFunctionBegin; 208 if (Z) { 209 if (dm && dm != ts->dm) { 210 PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Z", Z)); 211 } else *Z = ext->Z; 212 } 213 if (Ydot) { 214 if (dm && dm != ts->dm) { 215 PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot)); 216 } else *Ydot = ext->Ydot; 217 } 218 if (YdotI) { 219 if (dm && dm != ts->dm) { 220 PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI)); 221 } else *YdotI = ext->YdotI; 222 } 223 if (YdotRHS) { 224 if (dm && dm != ts->dm) { 225 PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS)); 226 } else *YdotRHS = ext->YdotRHS; 227 } 228 PetscFunctionReturn(PETSC_SUCCESS); 229 } 230 231 static PetscErrorCode TSEIMEXRestoreVecs(TS ts, DM dm, Vec *Z, Vec *Ydot, Vec *YdotI, Vec *YdotRHS) 232 { 233 PetscFunctionBegin; 234 if (Z) { 235 if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Z", Z)); 236 } 237 if (Ydot) { 238 if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot)); 239 } 240 if (YdotI) { 241 if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI)); 242 } 243 if (YdotRHS) { 244 if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS)); 245 } 246 PetscFunctionReturn(PETSC_SUCCESS); 247 } 248 249 /* 250 This defines the nonlinear equation that is to be solved with SNES 251 Fn[t0+Theta*dt, U, (U-U0)*shift] = 0 252 In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U)) 253 Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h 254 */ 255 static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes, Vec X, Vec G, TS ts) 256 { 257 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 258 Vec Ydot, Z; 259 DM dm, dmsave; 260 261 PetscFunctionBegin; 262 PetscCall(VecZeroEntries(G)); 263 264 PetscCall(SNESGetDM(snes, &dm)); 265 PetscCall(TSEIMEXGetVecs(ts, dm, &Z, &Ydot, NULL, NULL)); 266 PetscCall(VecZeroEntries(Ydot)); 267 dmsave = ts->dm; 268 ts->dm = dm; 269 PetscCall(TSComputeIFunction(ts, ext->ctime, X, Ydot, G, PETSC_FALSE)); 270 /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */ 271 PetscCall(VecCopy(G, Ydot)); 272 ts->dm = dmsave; 273 PetscCall(TSEIMEXRestoreVecs(ts, dm, &Z, &Ydot, NULL, NULL)); 274 275 PetscFunctionReturn(PETSC_SUCCESS); 276 } 277 278 /* 279 This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y)) 280 */ 281 static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes, Vec X, Mat A, Mat B, TS ts) 282 { 283 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 284 Vec Ydot; 285 DM dm, dmsave; 286 PetscFunctionBegin; 287 PetscCall(SNESGetDM(snes, &dm)); 288 PetscCall(TSEIMEXGetVecs(ts, dm, NULL, &Ydot, NULL, NULL)); 289 /* PetscCall(VecZeroEntries(Ydot)); */ 290 /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */ 291 dmsave = ts->dm; 292 ts->dm = dm; 293 PetscCall(TSComputeIJacobian(ts, ts->ptime, X, Ydot, ext->shift, A, B, PETSC_TRUE)); 294 ts->dm = dmsave; 295 PetscCall(TSEIMEXRestoreVecs(ts, dm, NULL, &Ydot, NULL, NULL)); 296 PetscFunctionReturn(PETSC_SUCCESS); 297 } 298 299 static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine, DM coarse, void *ctx) 300 { 301 PetscFunctionBegin; 302 PetscFunctionReturn(PETSC_SUCCESS); 303 } 304 305 static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine, Mat restrct, Vec rscale, Mat inject, DM coarse, void *ctx) 306 { 307 TS ts = (TS)ctx; 308 Vec Z, Z_c; 309 310 PetscFunctionBegin; 311 PetscCall(TSEIMEXGetVecs(ts, fine, &Z, NULL, NULL, NULL)); 312 PetscCall(TSEIMEXGetVecs(ts, coarse, &Z_c, NULL, NULL, NULL)); 313 PetscCall(MatRestrict(restrct, Z, Z_c)); 314 PetscCall(VecPointwiseMult(Z_c, rscale, Z_c)); 315 PetscCall(TSEIMEXRestoreVecs(ts, fine, &Z, NULL, NULL, NULL)); 316 PetscCall(TSEIMEXRestoreVecs(ts, coarse, &Z_c, NULL, NULL, NULL)); 317 PetscFunctionReturn(PETSC_SUCCESS); 318 } 319 320 static PetscErrorCode TSSetUp_EIMEX(TS ts) 321 { 322 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 323 DM dm; 324 325 PetscFunctionBegin; 326 if (!ext->N) { /* ext->max_rows not set */ 327 PetscCall(TSEIMEXSetMaxRows(ts, TSEIMEXDefault)); 328 } 329 if (-1 == ext->row_ind && -1 == ext->col_ind) { 330 PetscCall(TSEIMEXSetRowCol(ts, ext->max_rows, ext->max_rows)); 331 } else { /* ext->row_ind and col_ind already set */ 332 if (ext->ord_adapt) PetscCall(PetscInfo(ts, "Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n")); 333 } 334 335 if (ext->ord_adapt) { 336 ext->nstages = 2; /* Start with the 2-stage scheme */ 337 PetscCall(TSEIMEXSetRowCol(ts, ext->nstages, ext->nstages)); 338 } else { 339 ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */ 340 } 341 342 PetscCall(TSGetAdapt(ts, &ts->adapt)); 343 344 PetscCall(VecDuplicateVecs(ts->vec_sol, (1 + ext->nstages) * ext->nstages / 2, &ext->T)); /* full T table */ 345 PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotI)); 346 PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotRHS)); 347 PetscCall(VecDuplicate(ts->vec_sol, &ext->Ydot)); 348 PetscCall(VecDuplicate(ts->vec_sol, &ext->VecSolPrev)); 349 PetscCall(VecDuplicate(ts->vec_sol, &ext->Y)); 350 PetscCall(VecDuplicate(ts->vec_sol, &ext->Z)); 351 PetscCall(TSGetDM(ts, &dm)); 352 if (dm) PetscCall(DMCoarsenHookAdd(dm, DMCoarsenHook_TSEIMEX, DMRestrictHook_TSEIMEX, ts)); 353 PetscFunctionReturn(PETSC_SUCCESS); 354 } 355 356 static PetscErrorCode TSSetFromOptions_EIMEX(TS ts, PetscOptionItems *PetscOptionsObject) 357 { 358 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 359 PetscInt tindex[2]; 360 PetscInt np = 2, nrows = TSEIMEXDefault; 361 362 PetscFunctionBegin; 363 tindex[0] = TSEIMEXDefault; 364 tindex[1] = TSEIMEXDefault; 365 PetscOptionsHeadBegin(PetscOptionsObject, "EIMEX ODE solver options"); 366 { 367 PetscBool flg; 368 PetscCall(PetscOptionsInt("-ts_eimex_max_rows", "Define the maximum number of rows used", "TSEIMEXSetMaxRows", nrows, &nrows, &flg)); /* default value 3 */ 369 if (flg) PetscCall(TSEIMEXSetMaxRows(ts, nrows)); 370 PetscCall(PetscOptionsIntArray("-ts_eimex_row_col", "Return the specific term in the T table", "TSEIMEXSetRowCol", tindex, &np, &flg)); 371 if (flg) PetscCall(TSEIMEXSetRowCol(ts, tindex[0], tindex[1])); 372 PetscCall(PetscOptionsBool("-ts_eimex_order_adapt", "Solve the problem with adaptive order", "TSEIMEXSetOrdAdapt", ext->ord_adapt, &ext->ord_adapt, NULL)); 373 } 374 PetscOptionsHeadEnd(); 375 PetscFunctionReturn(PETSC_SUCCESS); 376 } 377 378 static PetscErrorCode TSView_EIMEX(TS ts, PetscViewer viewer) 379 { 380 PetscFunctionBegin; 381 PetscFunctionReturn(PETSC_SUCCESS); 382 } 383 384 /*@C 385 TSEIMEXSetMaxRows - Set the maximum number of rows for `TSEIMEX` schemes 386 387 Logically collective 388 389 Input Parameters: 390 + ts - timestepping context 391 - nrows - maximum number of rows 392 393 Level: intermediate 394 395 .seealso: [](chapter_ts), `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 396 @*/ 397 PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows) 398 { 399 PetscFunctionBegin; 400 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 401 PetscTryMethod(ts, "TSEIMEXSetMaxRows_C", (TS, PetscInt), (ts, nrows)); 402 PetscFunctionReturn(PETSC_SUCCESS); 403 } 404 405 /*@C 406 TSEIMEXSetRowCol - Set the type index in the T table for the return value for the `TSEIMEX` scheme 407 408 Logically collective 409 410 Input Parameters: 411 + ts - timestepping context 412 - tindex - index in the T table 413 414 Level: intermediate 415 416 .seealso: [](chapter_ts), `TSEIMEXSetMaxRows()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 417 @*/ 418 PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col) 419 { 420 PetscFunctionBegin; 421 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 422 PetscTryMethod(ts, "TSEIMEXSetRowCol_C", (TS, PetscInt, PetscInt), (ts, row, col)); 423 PetscFunctionReturn(PETSC_SUCCESS); 424 } 425 426 /*@C 427 TSEIMEXSetOrdAdapt - Set the order adaptativity for the `TSEIMEX` schemes 428 429 Logically collective 430 431 Input Parameters: 432 + ts - timestepping context 433 - tindex - index in the T table 434 435 Level: intermediate 436 437 .seealso: [](chapter_ts), `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 438 @*/ 439 PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg) 440 { 441 PetscFunctionBegin; 442 PetscValidHeaderSpecific(ts, TS_CLASSID, 1); 443 PetscTryMethod(ts, "TSEIMEXSetOrdAdapt_C", (TS, PetscBool), (ts, flg)); 444 PetscFunctionReturn(PETSC_SUCCESS); 445 } 446 447 static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts, PetscInt nrows) 448 { 449 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 450 PetscInt i; 451 452 PetscFunctionBegin; 453 PetscCheck(nrows >= 0 && nrows <= 100, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "Max number of rows (current value %" PetscInt_FMT ") should be an integer number between 1 and 100", nrows); 454 PetscCall(PetscFree(ext->N)); 455 ext->max_rows = nrows; 456 PetscCall(PetscMalloc1(nrows, &ext->N)); 457 for (i = 0; i < nrows; i++) ext->N[i] = i + 1; 458 PetscFunctionReturn(PETSC_SUCCESS); 459 } 460 461 static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts, PetscInt row, PetscInt col) 462 { 463 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 464 465 PetscFunctionBegin; 466 PetscCheck(row >= 1 && col >= 1, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The row or column index (current value %" PetscInt_FMT ",%" PetscInt_FMT ") should not be less than 1 ", row, col); 467 PetscCheck(row <= ext->max_rows && col <= ext->max_rows, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The row or column index (current value %" PetscInt_FMT ",%" PetscInt_FMT ") exceeds the maximum number of rows %" PetscInt_FMT, row, col, 468 ext->max_rows); 469 PetscCheck(col <= row, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The column index (%" PetscInt_FMT ") exceeds the row index (%" PetscInt_FMT ")", col, row); 470 471 ext->row_ind = row - 1; 472 ext->col_ind = col - 1; /* Array index in C starts from 0 */ 473 PetscFunctionReturn(PETSC_SUCCESS); 474 } 475 476 static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts, PetscBool flg) 477 { 478 TS_EIMEX *ext = (TS_EIMEX *)ts->data; 479 PetscFunctionBegin; 480 ext->ord_adapt = flg; 481 PetscFunctionReturn(PETSC_SUCCESS); 482 } 483 484 /*MC 485 TSEIMEX - Time stepping with Extrapolated IMEX methods. 486 487 These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it 488 is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using `TSSetIFunction()` and the 489 non-stiff part with `TSSetRHSFunction()`. 490 491 Level: beginner 492 493 Notes: 494 The default is a 3-stage scheme, it can be changed with `TSEIMEXSetMaxRows()` or -ts_eimex_max_rows 495 496 This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X). 497 498 The general system is written as 499 500 G(t,X,Xdot) = F(t,X) 501 502 where G represents the stiff part and F represents the non-stiff part. The user should provide the stiff part 503 of the equation using TSSetIFunction() and the non-stiff part with `TSSetRHSFunction()`. 504 This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian. 505 506 Another common form for the system is 507 508 y'=f(x)+g(x) 509 510 The relationship between F,G and f,g is 511 512 G = y'-g(x), F = f(x) 513 514 Reference: 515 . [1] - E. Constantinescu and A. Sandu, Extrapolated implicit-explicit time stepping, SIAM Journal on Scientific Computing, 31 (2010), pp. 4452-4477. 516 517 .seealso: [](chapter_ts), `TSCreate()`, `TS`, `TSSetType()`, `TSEIMEXSetMaxRows()`, `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSType` 518 M*/ 519 PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts) 520 { 521 TS_EIMEX *ext; 522 523 PetscFunctionBegin; 524 525 ts->ops->reset = TSReset_EIMEX; 526 ts->ops->destroy = TSDestroy_EIMEX; 527 ts->ops->view = TSView_EIMEX; 528 ts->ops->setup = TSSetUp_EIMEX; 529 ts->ops->step = TSStep_EIMEX; 530 ts->ops->interpolate = TSInterpolate_EIMEX; 531 ts->ops->evaluatestep = TSEvaluateStep_EIMEX; 532 ts->ops->setfromoptions = TSSetFromOptions_EIMEX; 533 ts->ops->snesfunction = SNESTSFormFunction_EIMEX; 534 ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX; 535 ts->default_adapt_type = TSADAPTNONE; 536 537 ts->usessnes = PETSC_TRUE; 538 539 PetscCall(PetscNew(&ext)); 540 ts->data = (void *)ext; 541 542 ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */ 543 ext->row_ind = -1; 544 ext->col_ind = -1; 545 ext->max_rows = TSEIMEXDefault; 546 ext->nstages = TSEIMEXDefault; 547 548 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX)); 549 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX)); 550 PetscCall(PetscObjectComposeFunction((PetscObject)ts, "TSEIMEXSetOrdAdapt_C", TSEIMEXSetOrdAdapt_EIMEX)); 551 PetscFunctionReturn(PETSC_SUCCESS); 552 } 553