Actual source code: eimex.c
1: #include <petsc/private/tsimpl.h>
2: #include <petscdm.h>
4: static const PetscInt TSEIMEXDefault = 3;
6: typedef struct {
7: PetscInt row_ind; /* Return the term T[row_ind][col_ind] */
8: PetscInt col_ind; /* Return the term T[row_ind][col_ind] */
9: PetscInt nstages; /* Numbers of stages in current scheme */
10: PetscInt max_rows; /* Maximum number of rows */
11: PetscInt *N; /* Harmonic sequence N[max_rows] */
12: Vec Y; /* States computed during the step, used to complete the step */
13: Vec Z; /* For shift*(Y-Z) */
14: Vec *T; /* Working table, size determined by nstages */
15: Vec YdotRHS; /* g(x) Work vector holding YdotRHS during residual evaluation */
16: Vec YdotI; /* xdot-f(x) Work vector holding YdotI = F(t,x,xdot) when xdot =0 */
17: Vec Ydot; /* f(x)+g(x) Work vector */
18: Vec VecSolPrev; /* Work vector holding the solution from the previous step (used for interpolation) */
19: PetscReal shift;
20: PetscReal ctime;
21: PetscBool recompute_jacobian; /* Recompute the Jacobian at each stage, default is to freeze the Jacobian at the start of each step */
22: PetscBool ord_adapt; /* order adapativity */
23: TSStepStatus status;
24: } TS_EIMEX;
26: /* This function is pure */
27: static PetscInt Map(PetscInt i, PetscInt j, PetscInt s)
28: {
29: return (2 * s - j + 1) * j / 2 + i - j;
30: }
32: static PetscErrorCode TSEvaluateStep_EIMEX(TS ts, PetscInt order, Vec X, PetscBool *done)
33: {
34: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
35: 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: }
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;
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 */
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: }
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;
83: PetscFunctionBegin;
84: PetscCall(TSGetSNES(ts, &snes));
85: PetscCall(SNESSetType(snes, "ksponly"));
86: ext->status = TS_STEP_INCOMPLETE;
88: PetscCall(VecCopy(ts->vec_sol, ext->VecSolPrev));
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: }
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: }
105: PetscCall(TSEvaluateStep(ts, ns, ts->vec_sol, NULL)); /*update ts solution */
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;
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*/
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;
144: if (ext->status != TS_STEP_COMPLETE && !ts->reason) ts->reason = TS_DIVERGED_STEP_REJECTED;
145: PetscFunctionReturn(PETSC_SUCCESS);
146: }
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;
156: PetscFunctionBegin;
157: t = (itime - ts->ptime + h) / h;
158: /* YdotI = -f(x)-g(x) */
160: PetscCall(VecZeroEntries(Ydot));
161: PetscCall(TSComputeIFunction(ts, ts->ptime - h, Y0, Ydot, YdotI, PETSC_FALSE));
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));
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: PetscFunctionReturn(PETSC_SUCCESS);
172: }
174: static PetscErrorCode TSReset_EIMEX(TS ts)
175: {
176: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
177: PetscInt ns;
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: }
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: }
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;
207: PetscFunctionBegin;
208: if (Z) {
209: if (dm && dm != ts->dm) PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Z", Z));
210: else *Z = ext->Z;
211: }
212: if (Ydot) {
213: if (dm && dm != ts->dm) PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot));
214: else *Ydot = ext->Ydot;
215: }
216: if (YdotI) {
217: if (dm && dm != ts->dm) PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI));
218: else *YdotI = ext->YdotI;
219: }
220: if (YdotRHS) {
221: if (dm && dm != ts->dm) PetscCall(DMGetNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS));
222: else *YdotRHS = ext->YdotRHS;
223: }
224: PetscFunctionReturn(PETSC_SUCCESS);
225: }
227: static PetscErrorCode TSEIMEXRestoreVecs(TS ts, DM dm, Vec *Z, Vec *Ydot, Vec *YdotI, Vec *YdotRHS)
228: {
229: PetscFunctionBegin;
230: if (Z) {
231: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Z", Z));
232: }
233: if (Ydot) {
234: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_Ydot", Ydot));
235: }
236: if (YdotI) {
237: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotI", YdotI));
238: }
239: if (YdotRHS) {
240: if (dm && dm != ts->dm) PetscCall(DMRestoreNamedGlobalVector(dm, "TSEIMEX_YdotRHS", YdotRHS));
241: }
242: PetscFunctionReturn(PETSC_SUCCESS);
243: }
245: /*
246: This defines the nonlinear equation that is to be solved with SNES
247: Fn[t0+Theta*dt, U, (U-U0)*shift] = 0
248: In the case of Backward Euler, Fn = (U-U0)/h-g(t1,U))
249: Since FormIFunction calculates G = ydot - g(t,y), ydot will be set to (U-U0)/h
250: */
251: static PetscErrorCode SNESTSFormFunction_EIMEX(SNES snes, Vec X, Vec G, TS ts)
252: {
253: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
254: Vec Ydot, Z;
255: DM dm, dmsave;
257: PetscFunctionBegin;
258: PetscCall(VecZeroEntries(G));
260: PetscCall(SNESGetDM(snes, &dm));
261: PetscCall(TSEIMEXGetVecs(ts, dm, &Z, &Ydot, NULL, NULL));
262: PetscCall(VecZeroEntries(Ydot));
263: dmsave = ts->dm;
264: ts->dm = dm;
265: PetscCall(TSComputeIFunction(ts, ext->ctime, X, Ydot, G, PETSC_FALSE));
266: /* PETSC_FALSE indicates non-imex, adding explicit RHS to the implicit I function. */
267: PetscCall(VecCopy(G, Ydot));
268: ts->dm = dmsave;
269: PetscCall(TSEIMEXRestoreVecs(ts, dm, &Z, &Ydot, NULL, NULL));
270: PetscFunctionReturn(PETSC_SUCCESS);
271: }
273: /*
274: This defined the Jacobian matrix for SNES. Jn = (I/h-g'(t,y))
275: */
276: static PetscErrorCode SNESTSFormJacobian_EIMEX(SNES snes, Vec X, Mat A, Mat B, TS ts)
277: {
278: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
279: Vec Ydot;
280: DM dm, dmsave;
282: PetscFunctionBegin;
283: PetscCall(SNESGetDM(snes, &dm));
284: PetscCall(TSEIMEXGetVecs(ts, dm, NULL, &Ydot, NULL, NULL));
285: /* PetscCall(VecZeroEntries(Ydot)); */
286: /* ext->Ydot have already been computed in SNESTSFormFunction_EIMEX (SNES guarantees this) */
287: dmsave = ts->dm;
288: ts->dm = dm;
289: PetscCall(TSComputeIJacobian(ts, ts->ptime, X, Ydot, ext->shift, A, B, PETSC_TRUE));
290: ts->dm = dmsave;
291: PetscCall(TSEIMEXRestoreVecs(ts, dm, NULL, &Ydot, NULL, NULL));
292: PetscFunctionReturn(PETSC_SUCCESS);
293: }
295: static PetscErrorCode DMCoarsenHook_TSEIMEX(DM fine, DM coarse, void *ctx)
296: {
297: PetscFunctionBegin;
298: PetscFunctionReturn(PETSC_SUCCESS);
299: }
301: static PetscErrorCode DMRestrictHook_TSEIMEX(DM fine, Mat restrct, Vec rscale, Mat inject, DM coarse, void *ctx)
302: {
303: TS ts = (TS)ctx;
304: Vec Z, Z_c;
306: PetscFunctionBegin;
307: PetscCall(TSEIMEXGetVecs(ts, fine, &Z, NULL, NULL, NULL));
308: PetscCall(TSEIMEXGetVecs(ts, coarse, &Z_c, NULL, NULL, NULL));
309: PetscCall(MatRestrict(restrct, Z, Z_c));
310: PetscCall(VecPointwiseMult(Z_c, rscale, Z_c));
311: PetscCall(TSEIMEXRestoreVecs(ts, fine, &Z, NULL, NULL, NULL));
312: PetscCall(TSEIMEXRestoreVecs(ts, coarse, &Z_c, NULL, NULL, NULL));
313: PetscFunctionReturn(PETSC_SUCCESS);
314: }
316: static PetscErrorCode TSSetUp_EIMEX(TS ts)
317: {
318: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
319: DM dm;
321: PetscFunctionBegin;
322: if (!ext->N) { /* ext->max_rows not set */
323: PetscCall(TSEIMEXSetMaxRows(ts, TSEIMEXDefault));
324: }
325: if (-1 == ext->row_ind && -1 == ext->col_ind) {
326: PetscCall(TSEIMEXSetRowCol(ts, ext->max_rows, ext->max_rows));
327: } else { /* ext->row_ind and col_ind already set */
328: if (ext->ord_adapt) PetscCall(PetscInfo(ts, "Order adaptivity is enabled and TSEIMEXSetRowCol or -ts_eimex_row_col option will take no effect\n"));
329: }
331: if (ext->ord_adapt) {
332: ext->nstages = 2; /* Start with the 2-stage scheme */
333: PetscCall(TSEIMEXSetRowCol(ts, ext->nstages, ext->nstages));
334: } else {
335: ext->nstages = ext->max_rows; /* by default nstages is the same as max_rows, this can be changed by setting order adaptivity */
336: }
338: PetscCall(TSGetAdapt(ts, &ts->adapt));
340: PetscCall(VecDuplicateVecs(ts->vec_sol, (1 + ext->nstages) * ext->nstages / 2, &ext->T)); /* full T table */
341: PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotI));
342: PetscCall(VecDuplicate(ts->vec_sol, &ext->YdotRHS));
343: PetscCall(VecDuplicate(ts->vec_sol, &ext->Ydot));
344: PetscCall(VecDuplicate(ts->vec_sol, &ext->VecSolPrev));
345: PetscCall(VecDuplicate(ts->vec_sol, &ext->Y));
346: PetscCall(VecDuplicate(ts->vec_sol, &ext->Z));
347: PetscCall(TSGetDM(ts, &dm));
348: if (dm) PetscCall(DMCoarsenHookAdd(dm, DMCoarsenHook_TSEIMEX, DMRestrictHook_TSEIMEX, ts));
349: PetscFunctionReturn(PETSC_SUCCESS);
350: }
352: static PetscErrorCode TSSetFromOptions_EIMEX(TS ts, PetscOptionItems PetscOptionsObject)
353: {
354: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
355: PetscInt tindex[2];
356: PetscInt np = 2, nrows = TSEIMEXDefault;
358: PetscFunctionBegin;
359: tindex[0] = TSEIMEXDefault;
360: tindex[1] = TSEIMEXDefault;
361: PetscOptionsHeadBegin(PetscOptionsObject, "EIMEX ODE solver options");
362: {
363: PetscBool flg;
364: PetscCall(PetscOptionsInt("-ts_eimex_max_rows", "Define the maximum number of rows used", "TSEIMEXSetMaxRows", nrows, &nrows, &flg)); /* default value 3 */
365: if (flg) PetscCall(TSEIMEXSetMaxRows(ts, nrows));
366: PetscCall(PetscOptionsIntArray("-ts_eimex_row_col", "Return the specific term in the T table", "TSEIMEXSetRowCol", tindex, &np, &flg));
367: if (flg) PetscCall(TSEIMEXSetRowCol(ts, tindex[0], tindex[1]));
368: PetscCall(PetscOptionsBool("-ts_eimex_order_adapt", "Solve the problem with adaptive order", "TSEIMEXSetOrdAdapt", ext->ord_adapt, &ext->ord_adapt, NULL));
369: }
370: PetscOptionsHeadEnd();
371: PetscFunctionReturn(PETSC_SUCCESS);
372: }
374: static PetscErrorCode TSView_EIMEX(TS ts, PetscViewer viewer)
375: {
376: PetscFunctionBegin;
377: PetscFunctionReturn(PETSC_SUCCESS);
378: }
380: /*@
381: TSEIMEXSetMaxRows - Set the maximum number of rows for `TSEIMEX` schemes
383: Logically Collective
385: Input Parameters:
386: + ts - timestepping context
387: - nrows - maximum number of rows
389: Level: intermediate
391: .seealso: [](ch_ts), `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX`
392: @*/
393: PetscErrorCode TSEIMEXSetMaxRows(TS ts, PetscInt nrows)
394: {
395: PetscFunctionBegin;
397: PetscTryMethod(ts, "TSEIMEXSetMaxRows_C", (TS, PetscInt), (ts, nrows));
398: PetscFunctionReturn(PETSC_SUCCESS);
399: }
401: /*@
402: TSEIMEXSetRowCol - Set the number of rows and the number of columns for the tableau that represents the T solution in the `TSEIMEX` scheme
404: Logically Collective
406: Input Parameters:
407: + ts - timestepping context
408: . row - the row
409: - col - the column
411: Level: intermediate
413: .seealso: [](ch_ts), `TSEIMEXSetMaxRows()`, `TSEIMEXSetOrdAdapt()`, `TSEIMEX`
414: @*/
415: PetscErrorCode TSEIMEXSetRowCol(TS ts, PetscInt row, PetscInt col)
416: {
417: PetscFunctionBegin;
419: PetscTryMethod(ts, "TSEIMEXSetRowCol_C", (TS, PetscInt, PetscInt), (ts, row, col));
420: PetscFunctionReturn(PETSC_SUCCESS);
421: }
423: /*@
424: TSEIMEXSetOrdAdapt - Set the order adaptativity for the `TSEIMEX` schemes
426: Logically Collective
428: Input Parameters:
429: + ts - timestepping context
430: - flg - index in the T table
432: Level: intermediate
434: .seealso: [](ch_ts), `TSEIMEXSetRowCol()`, `TSEIMEX`
435: @*/
436: PetscErrorCode TSEIMEXSetOrdAdapt(TS ts, PetscBool flg)
437: {
438: PetscFunctionBegin;
440: PetscTryMethod(ts, "TSEIMEXSetOrdAdapt_C", (TS, PetscBool), (ts, flg));
441: PetscFunctionReturn(PETSC_SUCCESS);
442: }
444: static PetscErrorCode TSEIMEXSetMaxRows_EIMEX(TS ts, PetscInt nrows)
445: {
446: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
447: PetscInt i;
449: PetscFunctionBegin;
450: 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);
451: PetscCall(PetscFree(ext->N));
452: ext->max_rows = nrows;
453: PetscCall(PetscMalloc1(nrows, &ext->N));
454: for (i = 0; i < nrows; i++) ext->N[i] = i + 1;
455: PetscFunctionReturn(PETSC_SUCCESS);
456: }
458: static PetscErrorCode TSEIMEXSetRowCol_EIMEX(TS ts, PetscInt row, PetscInt col)
459: {
460: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
462: PetscFunctionBegin;
463: 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);
464: 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,
465: ext->max_rows);
466: PetscCheck(col <= row, ((PetscObject)ts)->comm, PETSC_ERR_ARG_OUTOFRANGE, "The column index (%" PetscInt_FMT ") exceeds the row index (%" PetscInt_FMT ")", col, row);
468: ext->row_ind = row - 1;
469: ext->col_ind = col - 1; /* Array index in C starts from 0 */
470: PetscFunctionReturn(PETSC_SUCCESS);
471: }
473: static PetscErrorCode TSEIMEXSetOrdAdapt_EIMEX(TS ts, PetscBool flg)
474: {
475: TS_EIMEX *ext = (TS_EIMEX *)ts->data;
477: PetscFunctionBegin;
478: ext->ord_adapt = flg;
479: PetscFunctionReturn(PETSC_SUCCESS);
480: }
482: /*MC
483: TSEIMEX - Time stepping with Extrapolated W-IMEX methods {cite}`constantinescu_a2010a`.
485: These methods are intended for problems with well-separated time scales, especially when a slow scale is strongly nonlinear such that it
486: is expensive to solve with a fully implicit method. The user should provide the stiff part of the equation using `TSSetIFunction()` and the
487: non-stiff part with `TSSetRHSFunction()`.
489: Level: beginner
491: Notes:
492: The default is a 3-stage scheme, it can be changed with `TSEIMEXSetMaxRows()` or -ts_eimex_max_rows
494: This method currently only works with ODEs, for which the stiff part $ F(t,X,Xdot) $ has the form $ Xdot + Fhat(t,X)$.
496: The general system is written as
498: $$
499: F(t,X,Xdot) = G(t,X)
500: $$
502: where F represents the stiff part and G 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.
506: Another common form for the system is
508: $$
509: y'=f(x)+g(x)
510: $$
512: The relationship between F,G and f,g is
514: $$
515: F = y'-f(x), G = g(x)
516: $$
518: .seealso: [](ch_ts), `TSCreate()`, `TS`, `TSSetType()`, `TSEIMEXSetMaxRows()`, `TSEIMEXSetRowCol()`, `TSEIMEXSetOrdAdapt()`, `TSType`
519: M*/
520: PETSC_EXTERN PetscErrorCode TSCreate_EIMEX(TS ts)
521: {
522: TS_EIMEX *ext;
524: PetscFunctionBegin;
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;
537: ts->usessnes = PETSC_TRUE;
539: PetscCall(PetscNew(&ext));
540: ts->data = (void *)ext;
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;
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: }