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) { 364 PetscCall(DMCoarsenHookAdd(dm,DMCoarsenHook_TSEIMEX,DMRestrictHook_TSEIMEX,ts)); 365 } 366 PetscFunctionReturn(0); 367 } 368 369 static PetscErrorCode TSSetFromOptions_EIMEX(PetscOptionItems *PetscOptionsObject,TS ts) 370 { 371 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 372 PetscInt tindex[2]; 373 PetscInt np = 2, nrows=TSEIMEXDefault; 374 375 PetscFunctionBegin; 376 tindex[0] = TSEIMEXDefault; 377 tindex[1] = TSEIMEXDefault; 378 PetscOptionsHeadBegin(PetscOptionsObject,"EIMEX ODE solver options"); 379 { 380 PetscBool flg; 381 PetscCall(PetscOptionsInt("-ts_eimex_max_rows","Define the maximum number of rows used","TSEIMEXSetMaxRows",nrows,&nrows,&flg)); /* default value 3 */ 382 if (flg) { 383 PetscCall(TSEIMEXSetMaxRows(ts,nrows)); 384 } 385 PetscCall(PetscOptionsIntArray("-ts_eimex_row_col","Return the specific term in the T table","TSEIMEXSetRowCol",tindex,&np,&flg)); 386 if (flg) { 387 PetscCall(TSEIMEXSetRowCol(ts,tindex[0],tindex[1])); 388 } 389 PetscCall(PetscOptionsBool("-ts_eimex_order_adapt","Solve the problem with adaptive order","TSEIMEXSetOrdAdapt",ext->ord_adapt,&ext->ord_adapt,NULL)); 390 } 391 PetscOptionsHeadEnd(); 392 PetscFunctionReturn(0); 393 } 394 395 static PetscErrorCode TSView_EIMEX(TS ts,PetscViewer viewer) 396 { 397 PetscFunctionBegin; 398 PetscFunctionReturn(0); 399 } 400 401 /*@C 402 TSEIMEXSetMaxRows - Set the maximum number of rows for EIMEX schemes 403 404 Logically collective 405 406 Input Parameters: 407 + ts - timestepping context 408 - nrows - maximum number of rows 409 410 Level: intermediate 411 412 .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX 413 @*/ 414 PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows) 415 { 416 PetscFunctionBegin; 417 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 418 PetscTryMethod(ts,"TSEIMEXSetMaxRows_C",(TS,PetscInt),(ts,nrows)); 419 PetscFunctionReturn(0); 420 } 421 422 /*@C 423 TSEIMEXSetRowCol - Set the type index in the T table for the return value 424 425 Logically collective 426 427 Input Parameters: 428 + ts - timestepping context 429 - tindex - index in the T table 430 431 Level: intermediate 432 433 .seealso: TSEIMEXSetMaxRows(), TSEIMEXSetOrdAdapt(), TSEIMEX 434 @*/ 435 PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col) 436 { 437 PetscFunctionBegin; 438 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 439 PetscTryMethod(ts,"TSEIMEXSetRowCol_C",(TS,PetscInt, PetscInt),(ts,row,col)); 440 PetscFunctionReturn(0); 441 } 442 443 /*@C 444 TSEIMEXSetOrdAdapt - Set the order adaptativity 445 446 Logically collective 447 448 Input Parameters: 449 + ts - timestepping context 450 - tindex - index in the T table 451 452 Level: intermediate 453 454 .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX 455 @*/ 456 PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg) 457 { 458 PetscFunctionBegin; 459 PetscValidHeaderSpecific(ts,TS_CLASSID,1); 460 PetscTryMethod(ts,"TSEIMEXSetOrdAdapt_C",(TS,PetscBool),(ts,flg)); 461 PetscFunctionReturn(0); 462 } 463 464 static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts,PetscInt nrows) 465 { 466 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 467 PetscInt i; 468 469 PetscFunctionBegin; 470 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); 471 PetscCall(PetscFree(ext->N)); 472 ext->max_rows = nrows; 473 PetscCall(PetscMalloc1(nrows,&ext->N)); 474 for (i=0;i<nrows;i++) ext->N[i]=i+1; 475 PetscFunctionReturn(0); 476 } 477 478 static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts,PetscInt row,PetscInt col) 479 { 480 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 481 482 PetscFunctionBegin; 483 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); 484 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); 485 PetscCheck(col <= row,((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The column index (%" PetscInt_FMT ") exceeds the row index (%" PetscInt_FMT ")",col,row); 486 487 ext->row_ind = row - 1; 488 ext->col_ind = col - 1; /* Array index in C starts from 0 */ 489 PetscFunctionReturn(0); 490 } 491 492 static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts,PetscBool flg) 493 { 494 TS_EIMEX *ext = (TS_EIMEX*)ts->data; 495 PetscFunctionBegin; 496 ext->ord_adapt = flg; 497 PetscFunctionReturn(0); 498 } 499 500 /*MC 501 TSEIMEX - Time stepping with Extrapolated IMEX methods. 502 503 These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it 504 is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using TSSetIFunction() and the 505 non-stiff part with TSSetRHSFunction(). 506 507 Notes: 508 The default is a 3-stage scheme, it can be changed with TSEIMEXSetMaxRows() or -ts_eimex_max_rows 509 510 This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X). 511 512 The general system is written as 513 514 G(t,X,Xdot) = F(t,X) 515 516 where G represents the stiff part and F represents the non-stiff part. The user should provide the stiff part 517 of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction(). 518 This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian. 519 520 Another common form for the system is 521 522 y'=f(x)+g(x) 523 524 The relationship between F,G and f,g is 525 526 G = y'-g(x), F = f(x) 527 528 References 529 E. Constantinescu and A. Sandu, Extrapolated implicit-explicit time stepping, SIAM Journal on Scientific 530 Computing, 31 (2010), pp. 4452-4477. 531 532 Level: beginner 533 534 .seealso: TSCreate(), TS, TSSetType(), TSEIMEXSetMaxRows(), TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt() 535 536 M*/ 537 PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts) 538 { 539 TS_EIMEX *ext; 540 541 PetscFunctionBegin; 542 543 ts->ops->reset = TSReset_EIMEX; 544 ts->ops->destroy = TSDestroy_EIMEX; 545 ts->ops->view = TSView_EIMEX; 546 ts->ops->setup = TSSetUp_EIMEX; 547 ts->ops->step = TSStep_EIMEX; 548 ts->ops->interpolate = TSInterpolate_EIMEX; 549 ts->ops->evaluatestep = TSEvaluateStep_EIMEX; 550 ts->ops->setfromoptions = TSSetFromOptions_EIMEX; 551 ts->ops->snesfunction = SNESTSFormFunction_EIMEX; 552 ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX; 553 ts->default_adapt_type = TSADAPTNONE; 554 555 ts->usessnes = PETSC_TRUE; 556 557 PetscCall(PetscNewLog(ts,&ext)); 558 ts->data = (void*)ext; 559 560 ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */ 561 ext->row_ind = -1; 562 ext->col_ind = -1; 563 ext->max_rows = TSEIMEXDefault; 564 ext->nstages = TSEIMEXDefault; 565 566 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX)); 567 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX)); 568 PetscCall(PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",TSEIMEXSetOrdAdapt_EIMEX)); 569 PetscFunctionReturn(0); 570 } 571