Actual source code: eimex.c
petsc-3.7.5 2017-01-01
1: /*
2: * eimex.c
3: *
4: * Created on: Jun 21, 2012
5: * Written by Hong Zhang (zhang@vt.edu), Virginia Tech
6: * Emil Constantinescu (emconsta@mcs.anl.gov), Argonne National Laboratory
7: */
8: /*MC
9: EIMEX - Time stepping with Extrapolated IMEX methods.
11: Notes:
12: The general system is written as
14: G(t,X,Xdot) = F(t,X)
16: where G represents the stiff part and F represents the non-stiff part. The user should provide the stiff part
17: of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().
18: This method is designed to be linearly implicit on G and can use an approximate and lagged Jacobian.
20: Another common form for the system is
22: y'=f(x)+g(x)
24: The relationship between F,G and f,g is
26: G = y'-g(x), F = f(x)
28: References
29: E. Constantinescu and A. Sandu, Extrapolated implicit-explicit time stepping, SIAM Journal on Scientific
30: Computing, 31 (2010), pp. 4452-4477.
32: Level: beginner
34: .seealso: TSCreate(), TS, TSSetType(), TSEIMEXSetMaxRows(), TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt()
36: M*/
37: #include <petsc/private/tsimpl.h> /*I "petscts.h" I*/
38: #include <petscdm.h>
40: static const PetscInt TSEIMEXDefault = 3;
42: typedef struct {
43: PetscInt row_ind; /* Return the term T[row_ind][col_ind] */
44: PetscInt col_ind; /* Return the term T[row_ind][col_ind] */
45: PetscInt nstages; /* Numbers of stages in current scheme */
46: PetscInt max_rows; /* Maximum number of rows */
47: PetscInt *N; /* Harmonic sequence N[max_rows] */
48: Vec Y; /* States computed during the step, used to complete the step */
49: Vec Z; /* For shift*(Y-Z) */
50: Vec *T; /* Working table, size determined by nstages */
51: Vec YdotRHS; /* f(x) Work vector holding YdotRHS during residual evaluation */
52: Vec YdotI; /* xdot-g(x) Work vector holding YdotI = G(t,x,xdot) when xdot =0 */
53: Vec Ydot; /* f(x)+g(x) Work vector */
54: Vec VecSolPrev; /* Work vector holding the solution from the previous step (used for interpolation) */
55: PetscReal shift;
56: PetscReal ctime;
57: PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */
58: PetscBool ord_adapt; /* order adapativity */
59: TSStepStatus status;
60: } TS_EIMEX;
62: /* This function is pure */
63: static PetscInt Map(PetscInt i, PetscInt j, PetscInt s)
64: {
65: return ((2*s-j+1)*j/2+i-j);
66: }
71: static PetscErrorCode TSEvaluateStep_EIMEX(TS ts,PetscInt order,Vec X,PetscBool *done)
72: {
73: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
74: const PetscInt ns = ext->nstages;
77: VecCopy(ext->T[Map(ext->row_ind,ext->col_ind,ns)],X);
78: return(0);
79: }
84: static PetscErrorCode TSStage_EIMEX(TS ts,PetscInt istage)
85: {
86: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
87: PetscReal h;
88: Vec Y=ext->Y, Z=ext->Z;
89: SNES snes;
90: TSAdapt adapt;
91: PetscInt i,its,lits;
92: PetscBool accept;
93: PetscErrorCode ierr;
96: TSGetSNES(ts,&snes);
97: h = ts->time_step/ext->N[istage];/* step size for the istage-th stage */
98: ext->shift = 1./h;
99: SNESSetLagJacobian(snes,-2); /* Recompute the Jacobian on this solve, but not again */
100: VecCopy(ext->VecSolPrev,Y); /* Take the previous solution as intial step */
102: for(i=0; i<ext->N[istage]; i++){
103: ext->ctime = ts->ptime + h*i;
104: VecCopy(Y,Z);/* Save the solution of the previous substep */
105: SNESSolve(snes,NULL,Y);
106: SNESGetIterationNumber(snes,&its);
107: SNESGetLinearSolveIterations(snes,&lits);
108: ts->snes_its += its; ts->ksp_its += lits;
109: TSGetAdapt(ts,&adapt);
110: TSAdaptCheckStage(adapt,ts,ext->ctime,Y,&accept);
111: }
113: return(0);
114: }
119: static PetscErrorCode TSStep_EIMEX(TS ts)
120: {
121: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
122: const PetscInt ns = ext->nstages;
123: Vec *T=ext->T, Y=ext->Y;
125: SNES snes;
126: PetscInt i,j;
127: PetscBool accept = PETSC_FALSE;
128: PetscErrorCode ierr;
129: PetscReal alpha,local_error;
132: TSGetSNES(ts,&snes);
133: SNESSetType(snes,"ksponly");
134: ext->status = TS_STEP_INCOMPLETE;
136: VecCopy(ts->vec_sol,ext->VecSolPrev);
138: /* Apply n_j steps of the base method to obtain solutions of T(j,1),1<=j<=s */
139: for(j=0; j<ns; j++){
140: TSStage_EIMEX(ts,j);
141: VecCopy(Y,T[j]);
142: }
144: for(i=1;i<ns;i++){
145: for(j=i;j<ns;j++){
146: alpha = -(PetscReal)ext->N[j]/ext->N[j-i];
147: 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] */
148: alpha = 1.0/(1.0 + alpha);
149: VecScale(T[Map(j,i,ns)],alpha);
150: }
151: }
153: TSEvaluateStep(ts,ns,ts->vec_sol,NULL);/*update ts solution */
155: if(ext->ord_adapt && ext->nstages < ext->max_rows){
156: accept = PETSC_FALSE;
157: while(!accept && ext->nstages < ext->max_rows){
158: TSErrorWeightedNorm(ts,ts->vec_sol,T[Map(ext->nstages-1,ext->nstages-2,ext->nstages)],ts->adapt->wnormtype,&local_error);
159: accept = (local_error < 1.0)? PETSC_TRUE : PETSC_FALSE;
161: if(!accept){/* add one more stage*/
162: TSStage_EIMEX(ts,ext->nstages);
163: ext->nstages++; ext->row_ind++; ext->col_ind++;
164: /*T table need to be recycled*/
165: VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T);
166: for(i=0; i<ext->nstages-1; i++){
167: for(j=0; j<=i; j++){
168: VecCopy(T[Map(i,j,ext->nstages-1)],ext->T[Map(i,j,ext->nstages)]);
169: }
170: }
171: VecDestroyVecs(ext->nstages*(ext->nstages-1)/2,&T);
172: T = ext->T; /*reset the pointer*/
173: /*recycling finished, store the new solution*/
174: VecCopy(Y,T[ext->nstages-1]);
175: /*extrapolation for the newly added stage*/
176: for(i=1;i<ext->nstages;i++){
177: alpha = -(PetscReal)ext->N[ext->nstages-1]/ext->N[ext->nstages-1-i];
178: 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]*/
179: alpha = 1.0/(1.0 + alpha);
180: VecScale(T[Map(ext->nstages-1,i,ext->nstages)],alpha);
181: }
182: /*update ts solution */
183: TSEvaluateStep(ts,ext->nstages,ts->vec_sol,NULL);
184: }/*end if !accept*/
185: }/*end while*/
187: if(ext->nstages == ext->max_rows){
188: PetscInfo(ts,"Max number of rows has been used\n");
189: }
190: }/*end if ext->ord_adapt*/
191: ts->ptime += ts->time_step;
192: ext->status = TS_STEP_COMPLETE;
194: if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
195: return(0);
196: }
198: /* cubic Hermit spline */
201: static PetscErrorCode TSInterpolate_EIMEX(TS ts,PetscReal itime,Vec X)
202: {
203: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
204: PetscReal t,a,b;
205: Vec Y0=ext->VecSolPrev,Y1=ext->Y,Ydot=ext->Ydot,YdotI=ext->YdotI;
206: const PetscReal h = ts->ptime - ts->ptime_prev;
209: t = (itime -ts->ptime + h)/h;
210: /* YdotI = -f(x)-g(x) */
212: VecZeroEntries(Ydot);
213: TSComputeIFunction(ts,ts->ptime-h,Y0,Ydot,YdotI,PETSC_FALSE);
215: a = 2.0*t*t*t - 3.0*t*t + 1.0;
216: b = -(t*t*t - 2.0*t*t + t)*h;
217: VecAXPBYPCZ(X,a,b,0.0,Y0,YdotI);
219: TSComputeIFunction(ts,ts->ptime,Y1,Ydot,YdotI,PETSC_FALSE);
220: a = -2.0*t*t*t+3.0*t*t;
221: b = -(t*t*t - t*t)*h;
222: VecAXPBYPCZ(X,a,b,1.0,Y1,YdotI);
224: return(0);
225: }
230: static PetscErrorCode TSReset_EIMEX(TS ts)
231: {
232: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
233: PetscInt ns;
234: PetscErrorCode ierr;
237: ns = ext->nstages;
238: VecDestroyVecs((1+ns)*ns/2,&ext->T);
239: VecDestroy(&ext->Y);
240: VecDestroy(&ext->Z);
241: VecDestroy(&ext->YdotRHS);
242: VecDestroy(&ext->YdotI);
243: VecDestroy(&ext->Ydot);
244: VecDestroy(&ext->VecSolPrev);
245: PetscFree(ext->N);
246: return(0);
247: }
251: static PetscErrorCode TSDestroy_EIMEX(TS ts)
252: {
253: PetscErrorCode ierr;
256: TSReset_EIMEX(ts);
257: PetscFree(ts->data);
258: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C",NULL);
259: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C",NULL);
260: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",NULL);
262: return(0);
263: }
268: static PetscErrorCode TSEIMEXGetVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI, Vec *YdotRHS)
269: {
270: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
274: if (Z) {
275: if (dm && dm != ts->dm) {
276: DMGetNamedGlobalVector(dm,"TSEIMEX_Z",Z);
277: } else *Z = ext->Z;
278: }
279: if (Ydot) {
280: if (dm && dm != ts->dm) {
281: DMGetNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
282: } else *Ydot = ext->Ydot;
283: }
284: if (YdotI) {
285: if (dm && dm != ts->dm) {
286: DMGetNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
287: } else *YdotI = ext->YdotI;
288: }
289: if (YdotRHS) {
290: if (dm && dm != ts->dm) {
291: DMGetNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
292: } else *YdotRHS = ext->YdotRHS;
293: }
294: return(0);
295: }
300: static PetscErrorCode TSEIMEXRestoreVecs(TS ts,DM dm,Vec *Z,Vec *Ydot,Vec *YdotI,Vec *YdotRHS)
301: {
305: if (Z) {
306: if (dm && dm != ts->dm) {
307: DMRestoreNamedGlobalVector(dm,"TSEIMEX_Z",Z);
308: }
309: }
310: if (Ydot) {
311: if (dm && dm != ts->dm) {
312: DMRestoreNamedGlobalVector(dm,"TSEIMEX_Ydot",Ydot);
313: }
314: }
315: if (YdotI) {
316: if (dm && dm != ts->dm) {
317: DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotI",YdotI);
318: }
319: }
320: if (YdotRHS) {
321: if (dm && dm != ts->dm) {
322: DMRestoreNamedGlobalVector(dm,"TSEIMEX_YdotRHS",YdotRHS);
323: }
324: }
325: return(0);
326: }
329: /*
330: This defines the nonlinear equation that is to be solved with SNES
331: Fn[t0+Theta*dt, U, (U-U0)*shift] = 0
332: In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U))
333: Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h
334: */
337: static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes,Vec X,Vec G,TS ts)
338: {
339: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
340: PetscErrorCode ierr;
341: Vec Ydot,Z;
342: DM dm,dmsave;
345: VecZeroEntries(G);
347: SNESGetDM(snes,&dm);
348: TSEIMEXGetVecs(ts,dm,&Z,&Ydot,NULL,NULL);
349: VecZeroEntries(Ydot);
350: dmsave = ts->dm;
351: ts->dm = dm;
352: TSComputeIFunction(ts,ext->ctime,X,Ydot,G,PETSC_FALSE);
353: /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */
354: VecCopy(G,Ydot);
355: ts->dm = dmsave;
356: TSEIMEXRestoreVecs(ts,dm,&Z,&Ydot,NULL,NULL);
358: return(0);
359: }
361: /*
362: This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y))
363: */
366: static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes,Vec X,Mat A,Mat B,TS ts)
367: {
368: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
369: Vec Ydot;
370: PetscErrorCode ierr;
371: DM dm,dmsave;
373: SNESGetDM(snes,&dm);
374: TSEIMEXGetVecs(ts,dm,NULL,&Ydot,NULL,NULL);
375: /* VecZeroEntries(Ydot); */
376: /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */
377: dmsave = ts->dm;
378: ts->dm = dm;
379: TSComputeIJacobian(ts,ts->ptime,X,Ydot,ext->shift,A,B,PETSC_TRUE);
380: ts->dm = dmsave;
381: TSEIMEXRestoreVecs(ts,dm,NULL,&Ydot,NULL,NULL);
382: return(0);
383: }
387: static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine,DM coarse,void *ctx)
388: {
391: return(0);
392: }
396: static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine,Mat restrct,Vec rscale,Mat inject,DM coarse,void *ctx)
397: {
398: TS ts = (TS)ctx;
400: Vec Z,Z_c;
403: TSEIMEXGetVecs(ts,fine,&Z,NULL,NULL,NULL);
404: TSEIMEXGetVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
405: MatRestrict(restrct,Z,Z_c);
406: VecPointwiseMult(Z_c,rscale,Z_c);
407: TSEIMEXRestoreVecs(ts,fine,&Z,NULL,NULL,NULL);
408: TSEIMEXRestoreVecs(ts,coarse,&Z_c,NULL,NULL,NULL);
409: return(0);
410: }
415: static PetscErrorCode TSSetUp_EIMEX(TS ts)
416: {
417: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
419: DM dm;
422: if (!ext->N){ /* ext->max_rows not set */
423: TSEIMEXSetMaxRows(ts,TSEIMEXDefault);
424: }
425: if(-1 == ext->row_ind && -1 == ext->col_ind){
426: TSEIMEXSetRowCol(ts,ext->max_rows,ext->max_rows);
427: } else{/* ext->row_ind and col_ind already set */
428: if (ext->ord_adapt){
429: PetscInfo(ts,"Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n");
430: }
431: }
433: if(ext->ord_adapt){
434: ext->nstages = 2; /* Start with the 2-stage scheme */
435: TSEIMEXSetRowCol(ts,ext->nstages,ext->nstages);
436: } else{
437: ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */
438: }
440: VecDuplicateVecs(ts->vec_sol,(1+ext->nstages)*ext->nstages/2,&ext->T);/* full T table */
441: VecDuplicate(ts->vec_sol,&ext->YdotI);
442: VecDuplicate(ts->vec_sol,&ext->YdotRHS);
443: VecDuplicate(ts->vec_sol,&ext->Ydot);
444: VecDuplicate(ts->vec_sol,&ext->VecSolPrev);
445: VecDuplicate(ts->vec_sol,&ext->Y);
446: VecDuplicate(ts->vec_sol,&ext->Z);
447: TSGetDM(ts,&dm);
448: if (dm) {
449: DMCoarsenHookAdd(dm,DMCoarsenHook_TSEIMEX,DMRestrictHook_TSEIMEX,ts);
450: }
451: return(0);
452: }
456: static PetscErrorCode TSSetFromOptions_EIMEX(PetscOptionItems *PetscOptionsObject,TS ts)
457: {
458: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
460: PetscInt tindex[2];
461: PetscInt np = 2, nrows=TSEIMEXDefault;
464: tindex[0] = TSEIMEXDefault;
465: tindex[1] = TSEIMEXDefault;
466: PetscOptionsHead(PetscOptionsObject,"EIMEX ODE solver options");
467: {
468: PetscBool flg;
469: PetscOptionsInt("-ts_eimex_max_rows","Define the maximum number of rows used","TSEIMEXSetMaxRows",nrows,&nrows,&flg); /* default value 3 */
470: if(flg){
471: TSEIMEXSetMaxRows(ts,nrows);
472: }
473: PetscOptionsIntArray("-ts_eimex_row_col","Return the specific term in the T table","TSEIMEXSetRowCol",tindex,&np,&flg);
474: if(flg){
475: TSEIMEXSetRowCol(ts,tindex[0],tindex[1]);
476: }
477: PetscOptionsBool("-ts_eimex_order_adapt","Solve the problem with adaptive order","TSEIMEXSetOrdAdapt",ext->ord_adapt,&ext->ord_adapt,NULL);
478: }
479: PetscOptionsTail();
480: return(0);
481: }
485: static PetscErrorCode TSView_EIMEX(TS ts,PetscViewer viewer)
486: {
487: /* TS_EIMEX *ext = (TS_EIMEX*)ts->data; */
488: PetscBool iascii;
489: PetscErrorCode ierr;
492: PetscObjectTypeCompare((PetscObject)viewer,PETSCVIEWERASCII,&iascii);
493: if (iascii) {
494: PetscViewerASCIIPrintf(viewer," EIMEX\n");
495: }
496: SNESView(ts->snes,viewer);
497: return(0);
498: }
503: /*@C
504: TSEIMEXSetMaxRows - Set the maximum number of rows for EIMEX schemes
506: Logically collective
508: Input Parameter:
509: + ts - timestepping context
510: - nrows - maximum number of rows
512: Level: intermediate
514: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
515: @*/
516: PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows)
517: {
521: PetscTryMethod(ts,"TSEIMEXSetMaxRows_C",(TS,PetscInt),(ts,nrows));
522: return(0);
523: }
528: /*@C
529: TSEIMEXSetRowCol - Set the type index in the T table for the return value
531: Logically collective
533: Input Parameter:
534: + ts - timestepping context
535: - tindex - index in the T table
537: Level: intermediate
539: .seealso: TSEIMEXSetMaxRows(), TSEIMEXSetOrdAdapt(), TSEIMEX
540: @*/
541: PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col)
542: {
546: PetscTryMethod(ts,"TSEIMEXSetRowCol_C",(TS,PetscInt, PetscInt),(ts,row,col));
547: return(0);
548: }
553: /*@C
554: TSEIMEXSetOrdAdapt - Set the order adaptativity
556: Logically collective
558: Input Parameter:
559: + ts - timestepping context
560: - tindex - index in the T table
562: Level: intermediate
564: .seealso: TSEIMEXSetRowCol(), TSEIMEXSetOrdAdapt(), TSEIMEX
565: @*/
566: PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg)
567: {
571: PetscTryMethod(ts,"TSEIMEXSetOrdAdapt_C",(TS,PetscBool),(ts,flg));
572: return(0);
573: }
578: static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts,PetscInt nrows)
579: {
580: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
582: PetscInt i;
585: if (nrows < 0 || nrows > 100) SETERRQ1(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"Max number of rows (current value %D) should be an integer number between 1 and 100\n",nrows);
586: PetscFree(ext->N);
587: ext->max_rows = nrows;
588: PetscMalloc1(nrows,&ext->N);
589: for(i=0;i<nrows;i++) ext->N[i]=i+1;
590: return(0);
591: }
595: static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts,PetscInt row,PetscInt col)
596: {
597: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
600: if (row < 1 || col < 1) SETERRQ2(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The row or column index (current value %d,%d) should not be less than 1 \n",row,col);
601: if (row > ext->max_rows || col > ext->max_rows) SETERRQ3(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The row or column index (current value %d,%d) exceeds the maximum number of rows %d\n",row,col,ext->max_rows);
602: if (col > row) SETERRQ2(((PetscObject)ts)->comm,PETSC_ERR_ARG_OUTOFRANGE,"The column index (%d) exceeds the row index (%d)\n",col,row);
604: ext->row_ind = row - 1;
605: ext->col_ind = col - 1; /* Array index in C starts from 0 */
606: return(0);
607: }
611: static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts,PetscBool flg)
612: {
613: TS_EIMEX *ext = (TS_EIMEX*)ts->data;
615: ext->ord_adapt = flg;
616: return(0);
617: }
619: /* ------------------------------------------------------------ */
620: /*MC
621: TSEIMEX - ODE solver using extrapolated IMEX schemes
622: These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using TSSetIFunction() and the non-stiff part with TSSetRHSFunction().
624: Notes:
625: The default is a 3-stage scheme, it can be changed with TSEIMEXSetMaxRows() or -ts_eimex_max_rows
627: This method currently only works with ODE, for which the stiff part G(t,X,Xdot) has the form Xdot + Ghat(t,X).
629: Level: beginner
631: .seealso: TSCreate(), TS
632: M*/
635: PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts)
636: {
637: TS_EIMEX *ext;
642: ts->ops->reset = TSReset_EIMEX;
643: ts->ops->destroy = TSDestroy_EIMEX;
644: ts->ops->view = TSView_EIMEX;
645: ts->ops->setup = TSSetUp_EIMEX;
646: ts->ops->step = TSStep_EIMEX;
647: ts->ops->interpolate = TSInterpolate_EIMEX;
648: ts->ops->evaluatestep = TSEvaluateStep_EIMEX;
649: ts->ops->setfromoptions = TSSetFromOptions_EIMEX;
650: ts->ops->snesfunction = SNESTSFormFunction_EIMEX;
651: ts->ops->snesjacobian = SNESTSFormJacobian_EIMEX;
653: PetscNewLog(ts,&ext);
654: ts->data = (void*)ext;
656: ext->ord_adapt = PETSC_FALSE; /* By default, no order adapativity */
657: ext->row_ind = -1;
658: ext->col_ind = -1;
659: ext->max_rows = TSEIMEXDefault;
660: ext->nstages = TSEIMEXDefault;
662: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetMaxRows_C", TSEIMEXSetMaxRows_EIMEX);
663: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetRowCol_C", TSEIMEXSetRowCol_EIMEX);
664: PetscObjectComposeFunction((PetscObject)ts,"TSEIMEXSetOrdAdapt_C",TSEIMEXSetOrdAdapt_EIMEX);
665: return(0);
666: }