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(0); 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; ts->ksp_its += lits; 66 PetscCall(TSGetAdapt(ts,&adapt)); 67 PetscCall(TSAdaptCheckStage(adapt,ts,ext->ctime,Y,&accept)); 68 } 69 PetscFunctionReturn(0); 70 } 71 72 static PetscErrorCode TSStep_EIMEX(TS ts) 73 { 74 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 75 const PetscInt ns = ext->nstages; 76 Vec *T=ext->T, Y=ext->Y; 77 SNES snes; 78 PetscInt i,j; 79 PetscBool accept = PETSC_FALSE; 80 PetscReal alpha,local_error,local_error_a,local_error_r; 81 82 PetscFunctionBegin; 83 PetscCall(TSGetSNES(ts,&snes)); 84 PetscCall(SNESSetType(snes,"ksponly")); 85 ext->status = TS_STEP_INCOMPLETE; 86 87 PetscCall(VecCopy(ts->vec_sol,ext->VecSolPrev)); 88 89 /* Apply n_j steps of the base method to obtain solutions of T(j,1),1<=j<=s */ 90 for (j=0; j<ns; j++) { 91 PetscCall(TSStage_EIMEX(ts,j)); 92 PetscCall(VecCopy(Y,T[j])); 93 } 94 95 for (i=1;i<ns;i++) { 96 for (j=i;j<ns;j++) { 97 alpha = -(PetscReal)ext->N[j]/ext->N[j-i]; 98 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] */ 99 alpha = 1.0/(1.0 + alpha); 100 PetscCall(VecScale(T[Map(j,i,ns)],alpha)); 101 } 102 } 103 104 PetscCall(TSEvaluateStep(ts,ns,ts->vec_sol,NULL));/*update ts solution */ 105 106 if (ext->ord_adapt && ext->nstages < ext->max_rows) { 107 accept = PETSC_FALSE; 108 while (!accept && ext->nstages < ext->max_rows) { 109 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)); 110 accept = (local_error < 1.0)? PETSC_TRUE : PETSC_FALSE; 111 112 if (!accept) {/* add one more stage*/ 113 PetscCall(TSStage_EIMEX(ts,ext->nstages)); 114 ext->nstages++; ext->row_ind++; ext->col_ind++; 115 /*T table need to be recycled*/ 116 PetscCall(VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T)); 117 for (i=0; i<ext->nstages-1; i++) { 118 for (j=0; j<=i; j++) { 119 PetscCall(VecCopy(T[Map(i,j,ext->nstages-1)],ext->T[Map(i,j,ext->nstages)])); 120 } 121 } 122 PetscCall(VecDestroyVecs(ext->nstages*(ext->nstages-1)/2,&T)); 123 T = ext->T; /*reset the pointer*/ 124 /*recycling finished, store the new solution*/ 125 PetscCall(VecCopy(Y,T[ext->nstages-1])); 126 /*extrapolation for the newly added stage*/ 127 for (i=1;i<ext->nstages;i++) { 128 alpha = -(PetscReal)ext->N[ext->nstages-1]/ext->N[ext->nstages-1-i]; 129 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]*/ 130 alpha = 1.0/(1.0 + alpha); 131 PetscCall(VecScale(T[Map(ext->nstages-1,i,ext->nstages)],alpha)); 132 } 133 /*update ts solution */ 134 PetscCall(TSEvaluateStep(ts,ext->nstages,ts->vec_sol,NULL)); 135 }/*end if !accept*/ 136 }/*end while*/ 137 138 if (ext->nstages == ext->max_rows) { 139 PetscCall(PetscInfo(ts,"Max number of rows has been used\n")); 140 } 141 }/*end if ext->ord_adapt*/ 142 ts->ptime += ts->time_step; 143 ext->status = TS_STEP_COMPLETE; 144 145 if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED; 146 PetscFunctionReturn(0); 147 } 148 149 /* cubic Hermit spline */ 150 static PetscErrorCode TSInterpolate_EIMEX(TS ts,PetscReal itime,Vec X) 151 { 152 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 153 PetscReal t,a,b; 154 Vec Y0=ext->VecSolPrev,Y1=ext->Y,Ydot=ext->Ydot,YdotI=ext->YdotI; 155 const PetscReal h = ts->ptime - ts->ptime_prev; 156 PetscFunctionBegin; 157 t = (itime -ts->ptime + h)/h; 158 /* YdotI = -f(x)-g(x) */ 159 160 PetscCall(VecZeroEntries(Ydot)); 161 PetscCall(TSComputeIFunction(ts,ts->ptime-h,Y0,Ydot,YdotI,PETSC_FALSE)); 162 163 a = 2.0*t*t*t - 3.0*t*t + 1.0; 164 b = -(t*t*t - 2.0*t*t + t)*h; 165 PetscCall(VecAXPBYPCZ(X,a,b,0.0,Y0,YdotI)); 166 167 PetscCall(TSComputeIFunction(ts,ts->ptime,Y1,Ydot,YdotI,PETSC_FALSE)); 168 a = -2.0*t*t*t+3.0*t*t; 169 b = -(t*t*t - t*t)*h; 170 PetscCall(VecAXPBYPCZ(X,a,b,1.0,Y1,YdotI)); 171 172 PetscFunctionReturn(0); 173 } 174 175 static PetscErrorCode TSReset_EIMEX(TS ts) 176 { 177 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 178 PetscInt ns; 179 180 PetscFunctionBegin; 181 ns = ext->nstages; 182 PetscCall(VecDestroyVecs((1+ns)*ns/2,&ext->T)); 183 PetscCall(VecDestroy(&ext->Y)); 184 PetscCall(VecDestroy(&ext->Z)); 185 PetscCall(VecDestroy(&ext->YdotRHS)); 186 PetscCall(VecDestroy(&ext->YdotI)); 187 PetscCall(VecDestroy(&ext->Ydot)); 188 PetscCall(VecDestroy(&ext->VecSolPrev)); 189 PetscCall(PetscFree(ext->N)); 190 PetscFunctionReturn(0); 191 } 192 193 static PetscErrorCode TSDestroy_EIMEX(TS ts) 194 { 195 PetscFunctionBegin; 196 PetscCall(TSReset_EIMEX(ts)); 197 PetscCall(PetscFree(ts->data)); 198 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C",NULL)); 199 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C",NULL)); 200 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",NULL)); 201 PetscFunctionReturn(0); 202 } 203 204 static PetscErrorCode TSEIMEXGetVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI, Vec *YdotRHS) 205 { 206 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 207 208 PetscFunctionBegin; 209 if (Z) { 210 if (dm && dm != ts->dm) { 211 PetscCall(DMGetNamedGlobalVector(dm,"TSEIMEX_Z",Z)); 212 } else *Z = ext->Z; 213 } 214 if (Ydot) { 215 if (dm && dm != ts->dm) { 216 PetscCall(DMGetNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot)); 217 } else *Ydot = ext->Ydot; 218 } 219 if (YdotI) { 220 if (dm && dm != ts->dm) { 221 PetscCall(DMGetNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI)); 222 } else *YdotI = ext->YdotI; 223 } 224 if (YdotRHS) { 225 if (dm && dm != ts->dm) { 226 PetscCall(DMGetNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS)); 227 } else *YdotRHS = ext->YdotRHS; 228 } 229 PetscFunctionReturn(0); 230 } 231 232 static PetscErrorCode TSEIMEXRestoreVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI,Vec *YdotRHS) 233 { 234 PetscFunctionBegin; 235 if (Z) { 236 if (dm && dm != ts->dm) { 237 PetscCall(DMRestoreNamedGlobalVector(dm,"TSEIMEX_Z",Z)); 238 } 239 } 240 if (Ydot) { 241 if (dm && dm != ts->dm) { 242 PetscCall(DMRestoreNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot)); 243 } 244 } 245 if (YdotI) { 246 if (dm && dm != ts->dm) { 247 PetscCall(DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI)); 248 } 249 } 250 if (YdotRHS) { 251 if (dm && dm != ts->dm) { 252 PetscCall(DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS)); 253 } 254 } 255 PetscFunctionReturn(0); 256 } 257 258 /* 259 This defines the nonlinear equation that is to be solved with SNES 260 Fn[t0+Theta*dt, U, (U-U0)*shift] = 0 261 In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U)) 262 Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h 263 */ 264 static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes,Vec X,Vec G,TS ts) 265 { 266 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 267 Vec Ydot,Z; 268 DM dm,dmsave; 269 270 PetscFunctionBegin; 271 PetscCall(VecZeroEntries(G)); 272 273 PetscCall(SNESGetDM(snes,&dm)); 274 PetscCall(TSEIMEXGetVecs(ts,dm,&Z,&Ydot,NULL,NULL)); 275 PetscCall(VecZeroEntries(Ydot)); 276 dmsave = ts->dm; 277 ts->dm = dm; 278 PetscCall(TSComputeIFunction(ts,ext->ctime,X,Ydot,G,PETSC_FALSE)); 279 /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */ 280 PetscCall(VecCopy(G,Ydot)); 281 ts->dm = dmsave; 282 PetscCall(TSEIMEXRestoreVecs(ts,dm,&Z,&Ydot,NULL,NULL)); 283 284 PetscFunctionReturn(0); 285 } 286 287 /* 288 This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y)) 289 */ 290 static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes,Vec X,Mat A,Mat B,TS ts) 291 { 292 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 293 Vec Ydot; 294 DM dm,dmsave; 295 PetscFunctionBegin; 296 PetscCall(SNESGetDM(snes,&dm)); 297 PetscCall(TSEIMEXGetVecs(ts,dm,NULL,&Ydot,NULL,NULL)); 298 /* PetscCall(VecZeroEntries(Ydot)); */ 299 /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */ 300 dmsave = ts->dm; 301 ts->dm = dm; 302 PetscCall(TSComputeIJacobian(ts,ts->ptime,X,Ydot,ext->shift,A,B,PETSC_TRUE)); 303 ts->dm = dmsave; 304 PetscCall(TSEIMEXRestoreVecs(ts,dm,NULL,&Ydot,NULL,NULL)); 305 PetscFunctionReturn(0); 306 } 307 308 static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine,DM coarse,void *ctx) 309 { 310 PetscFunctionBegin; 311 PetscFunctionReturn(0); 312 } 313 314 static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx) 315 { 316 TS ts = (TS)ctx; 317 Vec Z,Z_c; 318 319 PetscFunctionBegin; 320 PetscCall(TSEIMEXGetVecs(ts,fine,&Z,NULL,NULL,NULL)); 321 PetscCall(TSEIMEXGetVecs(ts,coarse,&Z_c,NULL,NULL,NULL)); 322 PetscCall(MatRestrict(restrct,Z,Z_c)); 323 PetscCall(VecPointwiseMult(Z_c,rscale,Z_c)); 324 PetscCall(TSEIMEXRestoreVecs(ts,fine,&Z,NULL,NULL,NULL)); 325 PetscCall(TSEIMEXRestoreVecs(ts,coarse,&Z_c,NULL,NULL,NULL)); 326 PetscFunctionReturn(0); 327 } 328 329 static PetscErrorCode TSSetUp_EIMEX(TS ts) 330 { 331 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 332 DM dm; 333 334 PetscFunctionBegin; 335 if (!ext->N) { /* ext->max_rows not set */ 336 PetscCall(TSEIMEXSetMaxRows(ts,TSEIMEXDefault)); 337 } 338 if (-1 == ext->row_ind && -1 == ext->col_ind) { 339 PetscCall(TSEIMEXSetRowCol(ts,ext->max_rows,ext->max_rows)); 340 } else{/* ext->row_ind and col_ind already set */ 341 if (ext->ord_adapt) { 342 PetscCall(PetscInfo(ts,"Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n")); 343 } 344 } 345 346 if (ext->ord_adapt) { 347 ext->nstages = 2; /* Start with the 2-stage scheme */ 348 PetscCall(TSEIMEXSetRowCol(ts,ext->nstages,ext->nstages)); 349 } else{ 350 ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */ 351 } 352 353 PetscCall(TSGetAdapt(ts,&ts->adapt)); 354 355 PetscCall(VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T));/* full T table */ 356 PetscCall(VecDuplicate(ts->vec_sol,&ext->YdotI)); 357 PetscCall(VecDuplicate(ts->vec_sol,&ext->YdotRHS)); 358 PetscCall(VecDuplicate(ts->vec_sol,&ext->Ydot)); 359 PetscCall(VecDuplicate(ts->vec_sol,&ext->VecSolPrev)); 360 PetscCall(VecDuplicate(ts->vec_sol,&ext->Y)); 361 PetscCall(VecDuplicate(ts->vec_sol,&ext->Z)); 362 PetscCall(TSGetDM(ts,&dm)); 363 if (dm) PetscCall(DMCoarsenHookAdd(dm,DMCoarsenHook_TSEIMEX,DMRestrictHook_TSEIMEX,ts)); 364 PetscFunctionReturn(0); 365 } 366 367 static PetscErrorCode TSSetFromOptions_EIMEX(PetscOptionItems *PetscOptionsObject,TS ts) 368 { 369 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 370 PetscInt tindex[2]; 371 PetscInt np = 2, nrows=TSEIMEXDefault; 372 373 PetscFunctionBegin; 374 tindex[0] = TSEIMEXDefault; 375 tindex[1] = TSEIMEXDefault; 376 PetscOptionsHeadBegin(PetscOptionsObject,"EIMEX ODE solver options"); 377 { 378 PetscBool flg; 379 PetscCall(PetscOptionsInt("-ts_eimex_max_rows","Define the maximum number of rows used","TSEIMEXSetMaxRows",nrows,&nrows,&flg)); /* default value 3 */ 380 if (flg) PetscCall(TSEIMEXSetMaxRows(ts,nrows)); 381 PetscCall(PetscOptionsIntArray("-ts_eimex_row_col","Return the specific term in the T table","TSEIMEXSetRowCol",tindex,&np,&flg)); 382 if (flg) { 383 PetscCall(TSEIMEXSetRowCol(ts,tindex[0],tindex[1])); 384 } 385 PetscCall(PetscOptionsBool("-ts_eimex_order_adapt","Solve the problem with adaptive order","TSEIMEXSetOrdAdapt",ext->ord_adapt,&ext->ord_adapt,NULL)); 386 } 387 PetscOptionsHeadEnd(); 388 PetscFunctionReturn(0); 389 } 390 391 static PetscErrorCode TSView_EIMEX(TS ts,PetscViewer viewer) 392 { 393 PetscFunctionBegin; 394 PetscFunctionReturn(0); 395 } 396 397 /*@C 398 TSEIMEXSetMaxRows - Set the maximum number of rows for EIMEX schemes 399 400 Logically collective 401 402 Input Parameters: 403 + ts - timestepping context 404 - nrows - maximum number of rows 405 406 Level: intermediate 407 408 .seealso: `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 409 @*/ 410 PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows) 411 { 412 PetscFunctionBegin; 413 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 414 PetscTryMethod(ts,"TSEIMEXSetMaxRows_C",(TS,PetscInt),(ts,nrows)); 415 PetscFunctionReturn(0); 416 } 417 418 /*@C 419 TSEIMEXSetRowCol - Set the type index in the T table for the return value 420 421 Logically collective 422 423 Input Parameters: 424 + ts - timestepping context 425 - tindex - index in the T table 426 427 Level: intermediate 428 429 .seealso: `TSEIMEXSetMaxRows()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 430 @*/ 431 PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col) 432 { 433 PetscFunctionBegin; 434 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 435 PetscTryMethod(ts,"TSEIMEXSetRowCol_C",(TS,PetscInt, PetscInt),(ts,row,col)); 436 PetscFunctionReturn(0); 437 } 438 439 /*@C 440 TSEIMEXSetOrdAdapt - Set the order adaptativity 441 442 Logically collective 443 444 Input Parameters: 445 + ts - timestepping context 446 - tindex - index in the T table 447 448 Level: intermediate 449 450 .seealso: `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX` 451 @*/ 452 PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg) 453 { 454 PetscFunctionBegin; 455 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 456 PetscTryMethod(ts,"TSEIMEXSetOrdAdapt_C",(TS,PetscBool),(ts,flg)); 457 PetscFunctionReturn(0); 458 } 459 460 static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts,PetscInt nrows) 461 { 462 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 463 PetscInt i; 464 465 PetscFunctionBegin; 466 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); 467 PetscCall(PetscFree(ext->N)); 468 ext->max_rows = nrows; 469 PetscCall(PetscMalloc1(nrows,&ext->N)); 470 for (i=0;i<nrows;i++) ext->N[i]=i+1; 471 PetscFunctionReturn(0); 472 } 473 474 static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts,PetscInt row,PetscInt col) 475 { 476 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 477 478 PetscFunctionBegin; 479 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); 480 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,ext->max_rows); 481 PetscCheck(col <= row,((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The column index (%" PetscInt_FMT ") exceeds the row index (%" PetscInt_FMT ")",col,row); 482 483 ext->row_ind = row - 1; 484 ext->col_ind = col - 1; /* Array index in C starts from 0 */ 485 PetscFunctionReturn(0); 486 } 487 488 static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts,PetscBool flg) 489 { 490 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 491 PetscFunctionBegin; 492 ext->ord_adapt = flg; 493 PetscFunctionReturn(0); 494 } 495 496 /*MC 497 TSEIMEX - Time stepping with Extrapolated IMEX methods. 498 499 These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it 500 is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using TSSetIFunction() and the 501 non-stiff part with TSSetRHSFunction(). 502 503 Notes: 504 The default is a 3-stage scheme, it can be changed with TSEIMEXSetMaxRows() or -ts_eimex_max_rows 505 506 This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X). 507 508 The general system is written as 509 510 G(t,X,Xdot) = F(t,X) 511 512 where G represents the stiff part and F represents the non-stiff part. The user should provide the stiff part 513 of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction(). 514 This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian. 515 516 Another common form for the system is 517 518 y'=f(x)+g(x) 519 520 The relationship between F,G and f,g is 521 522 G = y'-g(x), F = f(x) 523 524 References 525 E. Constantinescu and A. Sandu, Extrapolated implicit-explicit time stepping, SIAM Journal on Scientific 526 Computing, 31 (2010), pp. 4452-4477. 527 528 Level: beginner 529 530 .seealso: `TSCreate()`, `TS`, `TSSetType()`, `TSEIMEXSetMaxRows()`, `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()` 531 532 M*/ 533 PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts) 534 { 535 TS_EIMEX *ext; 536 537 PetscFunctionBegin; 538 539 ts->ops->reset = TSReset_EIMEX; 540 ts->ops->destroy = TSDestroy_EIMEX; 541 ts->ops->view = TSView_EIMEX; 542 ts->ops->setup = TSSetUp_EIMEX; 543 ts->ops->step = TSStep_EIMEX; 544 ts->ops->interpolate = TSInterpolate_EIMEX; 545 ts->ops->evaluatestep = TSEvaluateStep_EIMEX; 546 ts->ops->setfromoptions = TSSetFromOptions_EIMEX; 547 ts->ops->snesfunction = SNESTSFormFunction_EIMEX; 548 ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX; 549 ts->default_adapt_type = TSADAPTNONE; 550 551 ts->usessnes = PETSC_TRUE; 552 553 PetscCall(PetscNewLog(ts,&ext)); 554 ts->data = (void*)ext; 555 556 ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */ 557 ext->row_ind = -1; 558 ext->col_ind = -1; 559 ext->max_rows = TSEIMEXDefault; 560 ext->nstages = TSEIMEXDefault; 561 562 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX)); 563 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX)); 564 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",TSEIMEXSetOrdAdapt_EIMEX)); 565 PetscFunctionReturn(0); 566 } 567