Actual source code: ex6.c
1: static char help[] = "Time-dependent PDE in 2d for calculating joint PDF. \n";
2: /*
3: p_t = -x_t*p_x -y_t*p_y + f(t)*p_yy
4: xmin < x < xmax, ymin < y < ymax;
5: x_t = (y - ws) y_t = (ws/2H)*(Pm - Pmax*sin(x))
7: Boundary conditions: -bc_type 0 => Zero dirichlet boundary
8: -bc_type 1 => Steady state boundary condition
9: Steady state boundary condition found by setting p_t = 0
10: */
12: #include <petscdm.h>
13: #include <petscdmda.h>
14: #include <petscts.h>
16: /*
17: User-defined data structures and routines
18: */
19: typedef struct {
20: PetscScalar ws; /* Synchronous speed */
21: PetscScalar H; /* Inertia constant */
22: PetscScalar D; /* Damping constant */
23: PetscScalar Pmax; /* Maximum power output of generator */
24: PetscScalar PM_min; /* Mean mechanical power input */
25: PetscScalar lambda; /* correlation time */
26: PetscScalar q; /* noise strength */
27: PetscScalar mux; /* Initial average angle */
28: PetscScalar sigmax; /* Standard deviation of initial angle */
29: PetscScalar muy; /* Average speed */
30: PetscScalar sigmay; /* standard deviation of initial speed */
31: PetscScalar rho; /* Cross-correlation coefficient */
32: PetscScalar t0; /* Initial time */
33: PetscScalar tmax; /* Final time */
34: PetscScalar xmin; /* left boundary of angle */
35: PetscScalar xmax; /* right boundary of angle */
36: PetscScalar ymin; /* bottom boundary of speed */
37: PetscScalar ymax; /* top boundary of speed */
38: PetscScalar dx; /* x step size */
39: PetscScalar dy; /* y step size */
40: PetscInt bc; /* Boundary conditions */
41: PetscScalar disper_coe; /* Dispersion coefficient */
42: DM da;
43: } AppCtx;
45: PetscErrorCode Parameter_settings(AppCtx *);
46: PetscErrorCode ini_bou(Vec, AppCtx *);
47: PetscErrorCode IFunction(TS, PetscReal, Vec, Vec, Vec, void *);
48: PetscErrorCode IJacobian(TS, PetscReal, Vec, Vec, PetscReal, Mat, Mat, void *);
49: PetscErrorCode PostStep(TS);
51: int main(int argc, char **argv)
52: {
53: Vec x; /* Solution vector */
54: TS ts; /* Time-stepping context */
55: AppCtx user; /* Application context */
56: Mat J;
57: PetscViewer viewer;
60: PetscInitialize(&argc, &argv, "petscopt_ex6", help);
61: /* Get physics and time parameters */
62: Parameter_settings(&user);
63: /* Create a 2D DA with dof = 1 */
64: DMDACreate2d(PETSC_COMM_WORLD, DM_BOUNDARY_NONE, DM_BOUNDARY_NONE, DMDA_STENCIL_STAR, 4, 4, PETSC_DECIDE, PETSC_DECIDE, 1, 1, NULL, NULL, &user.da);
65: DMSetFromOptions(user.da);
66: DMSetUp(user.da);
67: /* Set x and y coordinates */
68: DMDASetUniformCoordinates(user.da, user.xmin, user.xmax, user.ymin, user.ymax, 0.0, 1.0);
70: /* Get global vector x from DM */
71: DMCreateGlobalVector(user.da, &x);
73: ini_bou(x, &user);
74: PetscViewerBinaryOpen(PETSC_COMM_WORLD, "ini_x", FILE_MODE_WRITE, &viewer);
75: VecView(x, viewer);
76: PetscViewerDestroy(&viewer);
78: /* Get Jacobian matrix structure from the da */
79: DMSetMatType(user.da, MATAIJ);
80: DMCreateMatrix(user.da, &J);
82: TSCreate(PETSC_COMM_WORLD, &ts);
83: TSSetProblemType(ts, TS_NONLINEAR);
84: TSSetIFunction(ts, NULL, IFunction, &user);
85: TSSetIJacobian(ts, J, J, IJacobian, &user);
86: TSSetApplicationContext(ts, &user);
87: TSSetMaxTime(ts, user.tmax);
88: TSSetExactFinalTime(ts, TS_EXACTFINALTIME_MATCHSTEP);
89: TSSetTime(ts, user.t0);
90: TSSetTimeStep(ts, .005);
91: TSSetFromOptions(ts);
92: TSSetPostStep(ts, PostStep);
93: TSSolve(ts, x);
95: PetscViewerBinaryOpen(PETSC_COMM_WORLD, "fin_x", FILE_MODE_WRITE, &viewer);
96: VecView(x, viewer);
97: PetscViewerDestroy(&viewer);
99: VecDestroy(&x);
100: MatDestroy(&J);
101: DMDestroy(&user.da);
102: TSDestroy(&ts);
103: PetscFinalize();
104: return 0;
105: }
107: PetscErrorCode PostStep(TS ts)
108: {
109: Vec X;
110: AppCtx *user;
111: PetscScalar sum;
112: PetscReal t;
114: TSGetApplicationContext(ts, &user);
115: TSGetTime(ts, &t);
116: TSGetSolution(ts, &X);
117: VecSum(X, &sum);
118: PetscPrintf(PETSC_COMM_WORLD, "sum(p)*dw*dtheta at t = %3.2f = %3.6f\n", (double)t, (double)(sum * user->dx * user->dy));
119: return 0;
120: }
122: PetscErrorCode ini_bou(Vec X, AppCtx *user)
123: {
124: DM cda;
125: DMDACoor2d **coors;
126: PetscScalar **p;
127: Vec gc;
128: PetscInt i, j;
129: PetscInt xs, ys, xm, ym, M, N;
130: PetscScalar xi, yi;
131: PetscScalar sigmax = user->sigmax, sigmay = user->sigmay;
132: PetscScalar rho = user->rho;
133: PetscScalar mux = user->mux, muy = user->muy;
134: PetscMPIInt rank;
137: MPI_Comm_rank(PETSC_COMM_WORLD, &rank);
138: DMDAGetInfo(user->da, NULL, &M, &N, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL);
139: user->dx = (user->xmax - user->xmin) / (M - 1);
140: user->dy = (user->ymax - user->ymin) / (N - 1);
141: DMGetCoordinateDM(user->da, &cda);
142: DMGetCoordinates(user->da, &gc);
143: DMDAVecGetArray(cda, gc, &coors);
144: DMDAVecGetArray(user->da, X, &p);
145: DMDAGetCorners(cda, &xs, &ys, 0, &xm, &ym, 0);
146: for (i = xs; i < xs + xm; i++) {
147: for (j = ys; j < ys + ym; j++) {
148: xi = coors[j][i].x;
149: yi = coors[j][i].y;
150: if (i == 0 || j == 0 || i == M - 1 || j == N - 1) p[j][i] = 0.0;
151: else
152: p[j][i] = (0.5 / (PETSC_PI * sigmax * sigmay * PetscSqrtScalar(1.0 - rho * rho))) * PetscExpScalar(-0.5 / (1 - rho * rho) * (PetscPowScalar((xi - mux) / sigmax, 2) + PetscPowScalar((yi - muy) / sigmay, 2) - 2 * rho * (xi - mux) * (yi - muy) / (sigmax * sigmay)));
153: }
154: }
155: /* p[N/2+N%2][M/2+M%2] = 1/(user->dx*user->dy); */
157: DMDAVecRestoreArray(cda, gc, &coors);
158: DMDAVecRestoreArray(user->da, X, &p);
159: return 0;
160: }
162: /* First advection term */
163: PetscErrorCode adv1(PetscScalar **p, PetscScalar y, PetscInt i, PetscInt j, PetscInt M, PetscScalar *p1, AppCtx *user)
164: {
165: PetscScalar f;
166: /* PetscScalar v1,v2,v3,v4,v5,s1,s2,s3; */
167: /* if (i > 2 && i < M-2) {
168: v1 = (y-user->ws)*(p[j][i-2] - p[j][i-3])/user->dx;
169: v2 = (y-user->ws)*(p[j][i-1] - p[j][i-2])/user->dx;
170: v3 = (y-user->ws)*(p[j][i] - p[j][i-1])/user->dx;
171: v4 = (y-user->ws)*(p[j][i+1] - p[j][i])/user->dx;
172: v5 = (y-user->ws)*(p[j][i+1] - p[j][i+2])/user->dx;
174: s1 = v1/3.0 - (7.0/6.0)*v2 + (11.0/6.0)*v3;
175: s2 =-v2/6.0 + (5.0/6.0)*v3 + (1.0/3.0)*v4;
176: s3 = v3/3.0 + (5.0/6.0)*v4 - (1.0/6.0)*v5;
178: *p1 = 0.1*s1 + 0.6*s2 + 0.3*s3;
179: } else *p1 = 0.0; */
180: f = (y - user->ws);
181: *p1 = f * (p[j][i + 1] - p[j][i - 1]) / (2 * user->dx);
182: return 0;
183: }
185: /* Second advection term */
186: PetscErrorCode adv2(PetscScalar **p, PetscScalar x, PetscInt i, PetscInt j, PetscInt N, PetscScalar *p2, AppCtx *user)
187: {
188: PetscScalar f;
189: /* PetscScalar v1,v2,v3,v4,v5,s1,s2,s3; */
190: /* if (j > 2 && j < N-2) {
191: v1 = (user->ws/(2*user->H))*(user->PM_min - user->Pmax*sin(x))*(p[j-2][i] - p[j-3][i])/user->dy;
192: v2 = (user->ws/(2*user->H))*(user->PM_min - user->Pmax*sin(x))*(p[j-1][i] - p[j-2][i])/user->dy;
193: v3 = (user->ws/(2*user->H))*(user->PM_min - user->Pmax*sin(x))*(p[j][i] - p[j-1][i])/user->dy;
194: v4 = (user->ws/(2*user->H))*(user->PM_min - user->Pmax*sin(x))*(p[j+1][i] - p[j][i])/user->dy;
195: v5 = (user->ws/(2*user->H))*(user->PM_min - user->Pmax*sin(x))*(p[j+2][i] - p[j+1][i])/user->dy;
197: s1 = v1/3.0 - (7.0/6.0)*v2 + (11.0/6.0)*v3;
198: s2 =-v2/6.0 + (5.0/6.0)*v3 + (1.0/3.0)*v4;
199: s3 = v3/3.0 + (5.0/6.0)*v4 - (1.0/6.0)*v5;
201: *p2 = 0.1*s1 + 0.6*s2 + 0.3*s3;
202: } else *p2 = 0.0; */
203: f = (user->ws / (2 * user->H)) * (user->PM_min - user->Pmax * PetscSinScalar(x));
204: *p2 = f * (p[j + 1][i] - p[j - 1][i]) / (2 * user->dy);
205: return 0;
206: }
208: /* Diffusion term */
209: PetscErrorCode diffuse(PetscScalar **p, PetscInt i, PetscInt j, PetscReal t, PetscScalar *p_diff, AppCtx *user)
210: {
213: *p_diff = user->disper_coe * ((p[j - 1][i] - 2 * p[j][i] + p[j + 1][i]) / (user->dy * user->dy));
214: return 0;
215: }
217: PetscErrorCode BoundaryConditions(PetscScalar **p, DMDACoor2d **coors, PetscInt i, PetscInt j, PetscInt M, PetscInt N, PetscScalar **f, AppCtx *user)
218: {
219: PetscScalar fwc, fthetac;
220: PetscScalar w = coors[j][i].y, theta = coors[j][i].x;
223: if (user->bc == 0) { /* Natural boundary condition */
224: f[j][i] = p[j][i];
225: } else { /* Steady state boundary condition */
226: fthetac = user->ws / (2 * user->H) * (user->PM_min - user->Pmax * PetscSinScalar(theta));
227: fwc = (w * w / 2.0 - user->ws * w);
228: if (i == 0 && j == 0) { /* left bottom corner */
229: f[j][i] = fwc * (p[j][i + 1] - p[j][i]) / user->dx + fthetac * p[j][i] - user->disper_coe * (p[j + 1][i] - p[j][i]) / user->dy;
230: } else if (i == 0 && j == N - 1) { /* right bottom corner */
231: f[j][i] = fwc * (p[j][i + 1] - p[j][i]) / user->dx + fthetac * p[j][i] - user->disper_coe * (p[j][i] - p[j - 1][i]) / user->dy;
232: } else if (i == M - 1 && j == 0) { /* left top corner */
233: f[j][i] = fwc * (p[j][i] - p[j][i - 1]) / user->dx + fthetac * p[j][i] - user->disper_coe * (p[j + 1][i] - p[j][i]) / user->dy;
234: } else if (i == M - 1 && j == N - 1) { /* right top corner */
235: f[j][i] = fwc * (p[j][i] - p[j][i - 1]) / user->dx + fthetac * p[j][i] - user->disper_coe * (p[j][i] - p[j - 1][i]) / user->dy;
236: } else if (i == 0) { /* Bottom edge */
237: f[j][i] = fwc * (p[j][i + 1] - p[j][i]) / (user->dx) + fthetac * p[j][i] - user->disper_coe * (p[j + 1][i] - p[j - 1][i]) / (2 * user->dy);
238: } else if (i == M - 1) { /* Top edge */
239: f[j][i] = fwc * (p[j][i] - p[j][i - 1]) / (user->dx) + fthetac * p[j][i] - user->disper_coe * (p[j + 1][i] - p[j - 1][i]) / (2 * user->dy);
240: } else if (j == 0) { /* Left edge */
241: f[j][i] = fwc * (p[j][i + 1] - p[j][i - 1]) / (2 * user->dx) + fthetac * p[j][i] - user->disper_coe * (p[j + 1][i] - p[j][i]) / (user->dy);
242: } else if (j == N - 1) { /* Right edge */
243: f[j][i] = fwc * (p[j][i + 1] - p[j][i - 1]) / (2 * user->dx) + fthetac * p[j][i] - user->disper_coe * (p[j][i] - p[j - 1][i]) / (user->dy);
244: }
245: }
246: return 0;
247: }
249: PetscErrorCode IFunction(TS ts, PetscReal t, Vec X, Vec Xdot, Vec F, void *ctx)
250: {
251: AppCtx *user = (AppCtx *)ctx;
252: DM cda;
253: DMDACoor2d **coors;
254: PetscScalar **p, **f, **pdot;
255: PetscInt i, j;
256: PetscInt xs, ys, xm, ym, M, N;
257: Vec localX, gc, localXdot;
258: PetscScalar p_adv1, p_adv2, p_diff;
261: DMDAGetInfo(user->da, NULL, &M, &N, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL);
262: DMGetCoordinateDM(user->da, &cda);
263: DMDAGetCorners(cda, &xs, &ys, 0, &xm, &ym, 0);
265: DMGetLocalVector(user->da, &localX);
266: DMGetLocalVector(user->da, &localXdot);
268: DMGlobalToLocalBegin(user->da, X, INSERT_VALUES, localX);
269: DMGlobalToLocalEnd(user->da, X, INSERT_VALUES, localX);
270: DMGlobalToLocalBegin(user->da, Xdot, INSERT_VALUES, localXdot);
271: DMGlobalToLocalEnd(user->da, Xdot, INSERT_VALUES, localXdot);
273: DMGetCoordinatesLocal(user->da, &gc);
275: DMDAVecGetArrayRead(cda, gc, &coors);
276: DMDAVecGetArrayRead(user->da, localX, &p);
277: DMDAVecGetArrayRead(user->da, localXdot, &pdot);
278: DMDAVecGetArray(user->da, F, &f);
280: user->disper_coe = PetscPowScalar((user->lambda * user->ws) / (2 * user->H), 2) * user->q * (1.0 - PetscExpScalar(-t / user->lambda));
281: for (i = xs; i < xs + xm; i++) {
282: for (j = ys; j < ys + ym; j++) {
283: if (i == 0 || j == 0 || i == M - 1 || j == N - 1) {
284: BoundaryConditions(p, coors, i, j, M, N, f, user);
285: } else {
286: adv1(p, coors[j][i].y, i, j, M, &p_adv1, user);
287: adv2(p, coors[j][i].x, i, j, N, &p_adv2, user);
288: diffuse(p, i, j, t, &p_diff, user);
289: f[j][i] = -p_adv1 - p_adv2 + p_diff - pdot[j][i];
290: }
291: }
292: }
293: DMDAVecRestoreArrayRead(user->da, localX, &p);
294: DMDAVecRestoreArrayRead(user->da, localX, &pdot);
295: DMRestoreLocalVector(user->da, &localX);
296: DMRestoreLocalVector(user->da, &localXdot);
297: DMDAVecRestoreArray(user->da, F, &f);
298: DMDAVecRestoreArrayRead(cda, gc, &coors);
300: return 0;
301: }
303: PetscErrorCode IJacobian(TS ts, PetscReal t, Vec X, Vec Xdot, PetscReal a, Mat J, Mat Jpre, void *ctx)
304: {
305: AppCtx *user = (AppCtx *)ctx;
306: DM cda;
307: DMDACoor2d **coors;
308: PetscInt i, j;
309: PetscInt xs, ys, xm, ym, M, N;
310: Vec gc;
311: PetscScalar val[5], xi, yi;
312: MatStencil row, col[5];
313: PetscScalar c1, c3, c5;
316: DMDAGetInfo(user->da, NULL, &M, &N, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL, NULL);
317: DMGetCoordinateDM(user->da, &cda);
318: DMDAGetCorners(cda, &xs, &ys, 0, &xm, &ym, 0);
320: DMGetCoordinatesLocal(user->da, &gc);
321: DMDAVecGetArrayRead(cda, gc, &coors);
322: for (i = xs; i < xs + xm; i++) {
323: for (j = ys; j < ys + ym; j++) {
324: PetscInt nc = 0;
325: xi = coors[j][i].x;
326: yi = coors[j][i].y;
327: row.i = i;
328: row.j = j;
329: if (i == 0 || j == 0 || i == M - 1 || j == N - 1) {
330: if (user->bc == 0) {
331: col[nc].i = i;
332: col[nc].j = j;
333: val[nc++] = 1.0;
334: } else {
335: PetscScalar fthetac, fwc;
336: fthetac = user->ws / (2 * user->H) * (user->PM_min - user->Pmax * PetscSinScalar(xi));
337: fwc = (yi * yi / 2.0 - user->ws * yi);
338: if (i == 0 && j == 0) {
339: col[nc].i = i + 1;
340: col[nc].j = j;
341: val[nc++] = fwc / user->dx;
342: col[nc].i = i;
343: col[nc].j = j + 1;
344: val[nc++] = -user->disper_coe / user->dy;
345: col[nc].i = i;
346: col[nc].j = j;
347: val[nc++] = -fwc / user->dx + fthetac + user->disper_coe / user->dy;
348: } else if (i == 0 && j == N - 1) {
349: col[nc].i = i + 1;
350: col[nc].j = j;
351: val[nc++] = fwc / user->dx;
352: col[nc].i = i;
353: col[nc].j = j - 1;
354: val[nc++] = user->disper_coe / user->dy;
355: col[nc].i = i;
356: col[nc].j = j;
357: val[nc++] = -fwc / user->dx + fthetac - user->disper_coe / user->dy;
358: } else if (i == M - 1 && j == 0) {
359: col[nc].i = i - 1;
360: col[nc].j = j;
361: val[nc++] = -fwc / user->dx;
362: col[nc].i = i;
363: col[nc].j = j + 1;
364: val[nc++] = -user->disper_coe / user->dy;
365: col[nc].i = i;
366: col[nc].j = j;
367: val[nc++] = fwc / user->dx + fthetac + user->disper_coe / user->dy;
368: } else if (i == M - 1 && j == N - 1) {
369: col[nc].i = i - 1;
370: col[nc].j = j;
371: val[nc++] = -fwc / user->dx;
372: col[nc].i = i;
373: col[nc].j = j - 1;
374: val[nc++] = user->disper_coe / user->dy;
375: col[nc].i = i;
376: col[nc].j = j;
377: val[nc++] = fwc / user->dx + fthetac - user->disper_coe / user->dy;
378: } else if (i == 0) {
379: col[nc].i = i + 1;
380: col[nc].j = j;
381: val[nc++] = fwc / user->dx;
382: col[nc].i = i;
383: col[nc].j = j + 1;
384: val[nc++] = -user->disper_coe / (2 * user->dy);
385: col[nc].i = i;
386: col[nc].j = j - 1;
387: val[nc++] = user->disper_coe / (2 * user->dy);
388: col[nc].i = i;
389: col[nc].j = j;
390: val[nc++] = -fwc / user->dx + fthetac;
391: } else if (i == M - 1) {
392: col[nc].i = i - 1;
393: col[nc].j = j;
394: val[nc++] = -fwc / user->dx;
395: col[nc].i = i;
396: col[nc].j = j + 1;
397: val[nc++] = -user->disper_coe / (2 * user->dy);
398: col[nc].i = i;
399: col[nc].j = j - 1;
400: val[nc++] = user->disper_coe / (2 * user->dy);
401: col[nc].i = i;
402: col[nc].j = j;
403: val[nc++] = fwc / user->dx + fthetac;
404: } else if (j == 0) {
405: col[nc].i = i + 1;
406: col[nc].j = j;
407: val[nc++] = fwc / (2 * user->dx);
408: col[nc].i = i - 1;
409: col[nc].j = j;
410: val[nc++] = -fwc / (2 * user->dx);
411: col[nc].i = i;
412: col[nc].j = j + 1;
413: val[nc++] = -user->disper_coe / user->dy;
414: col[nc].i = i;
415: col[nc].j = j;
416: val[nc++] = user->disper_coe / user->dy + fthetac;
417: } else if (j == N - 1) {
418: col[nc].i = i + 1;
419: col[nc].j = j;
420: val[nc++] = fwc / (2 * user->dx);
421: col[nc].i = i - 1;
422: col[nc].j = j;
423: val[nc++] = -fwc / (2 * user->dx);
424: col[nc].i = i;
425: col[nc].j = j - 1;
426: val[nc++] = user->disper_coe / user->dy;
427: col[nc].i = i;
428: col[nc].j = j;
429: val[nc++] = -user->disper_coe / user->dy + fthetac;
430: }
431: }
432: } else {
433: c1 = (yi - user->ws) / (2 * user->dx);
434: c3 = (user->ws / (2.0 * user->H)) * (user->PM_min - user->Pmax * PetscSinScalar(xi)) / (2 * user->dy);
435: c5 = (PetscPowScalar((user->lambda * user->ws) / (2 * user->H), 2) * user->q * (1.0 - PetscExpScalar(-t / user->lambda))) / (user->dy * user->dy);
436: col[nc].i = i - 1;
437: col[nc].j = j;
438: val[nc++] = c1;
439: col[nc].i = i + 1;
440: col[nc].j = j;
441: val[nc++] = -c1;
442: col[nc].i = i;
443: col[nc].j = j - 1;
444: val[nc++] = c3 + c5;
445: col[nc].i = i;
446: col[nc].j = j + 1;
447: val[nc++] = -c3 + c5;
448: col[nc].i = i;
449: col[nc].j = j;
450: val[nc++] = -2 * c5 - a;
451: }
452: MatSetValuesStencil(Jpre, 1, &row, nc, col, val, INSERT_VALUES);
453: }
454: }
455: DMDAVecRestoreArrayRead(cda, gc, &coors);
457: MatAssemblyBegin(Jpre, MAT_FINAL_ASSEMBLY);
458: MatAssemblyEnd(Jpre, MAT_FINAL_ASSEMBLY);
459: if (J != Jpre) {
460: MatAssemblyBegin(J, MAT_FINAL_ASSEMBLY);
461: MatAssemblyEnd(J, MAT_FINAL_ASSEMBLY);
462: }
463: return 0;
464: }
466: PetscErrorCode Parameter_settings(AppCtx *user)
467: {
468: PetscBool flg;
472: /* Set default parameters */
473: user->ws = 1.0;
474: user->H = 5.0;
475: user->Pmax = 2.1;
476: user->PM_min = 1.0;
477: user->lambda = 0.1;
478: user->q = 1.0;
479: user->mux = PetscAsinScalar(user->PM_min / user->Pmax);
480: user->sigmax = 0.1;
481: user->sigmay = 0.1;
482: user->rho = 0.0;
483: user->t0 = 0.0;
484: user->tmax = 2.0;
485: user->xmin = -1.0;
486: user->xmax = 10.0;
487: user->ymin = -1.0;
488: user->ymax = 10.0;
489: user->bc = 0;
491: PetscOptionsGetScalar(NULL, NULL, "-ws", &user->ws, &flg);
492: PetscOptionsGetScalar(NULL, NULL, "-Inertia", &user->H, &flg);
493: PetscOptionsGetScalar(NULL, NULL, "-Pmax", &user->Pmax, &flg);
494: PetscOptionsGetScalar(NULL, NULL, "-PM_min", &user->PM_min, &flg);
495: PetscOptionsGetScalar(NULL, NULL, "-lambda", &user->lambda, &flg);
496: PetscOptionsGetScalar(NULL, NULL, "-q", &user->q, &flg);
497: PetscOptionsGetScalar(NULL, NULL, "-mux", &user->mux, &flg);
498: PetscOptionsGetScalar(NULL, NULL, "-sigmax", &user->sigmax, &flg);
499: PetscOptionsGetScalar(NULL, NULL, "-muy", &user->muy, &flg);
500: PetscOptionsGetScalar(NULL, NULL, "-sigmay", &user->sigmay, &flg);
501: PetscOptionsGetScalar(NULL, NULL, "-rho", &user->rho, &flg);
502: PetscOptionsGetScalar(NULL, NULL, "-t0", &user->t0, &flg);
503: PetscOptionsGetScalar(NULL, NULL, "-tmax", &user->tmax, &flg);
504: PetscOptionsGetScalar(NULL, NULL, "-xmin", &user->xmin, &flg);
505: PetscOptionsGetScalar(NULL, NULL, "-xmax", &user->xmax, &flg);
506: PetscOptionsGetScalar(NULL, NULL, "-ymin", &user->ymin, &flg);
507: PetscOptionsGetScalar(NULL, NULL, "-ymax", &user->ymax, &flg);
508: PetscOptionsGetInt(NULL, NULL, "-bc_type", &user->bc, &flg);
509: user->muy = user->ws;
510: return 0;
511: }
513: /*TEST
515: build:
516: requires: !complex
518: test:
519: args: -nox -ts_max_steps 2
520: localrunfiles: petscopt_ex6
521: timeoutfactor: 4
523: TEST*/