Actual source code: ex20adj.c
1: static char help[] = "Performs adjoint sensitivity analysis for the van der Pol equation.\n";
3: /* ------------------------------------------------------------------------
5: This program solves the van der Pol DAE ODE equivalent
6: [ u_1' ] = [ u_2 ] (2)
7: [ u_2' ] [ \mu ((1 - u_1^2) u_2 - u_1) ]
8: on the domain 0 <= x <= 1, with the boundary conditions
9: u_1(0) = 2, u_2(0) = - 2/3 +10/(81*\mu) - 292/(2187*\mu^2),
10: and
11: \mu = 10^6 ( y'(0) ~ -0.6666665432100101).,
12: and computes the sensitivities of the final solution w.r.t. initial conditions and parameter \mu with the implicit theta method and its discrete adjoint.
14: In an IMEX setting, we can split (2) by component,
16: [ u_1' ] = [ u_2 ] + [ 0 ]
17: [ u_2' ] [ 0 ] [ \mu ((1 - u_1^2) u_2 - u_1) ]
19: where
21: [ G(u,t) ] = [ u_2 ]
22: [ 0 ]
24: and
26: [ F(u',u,t) ] = [ u_1' ] - [ 0 ]
27: [ u_2' ] [ \mu ((1 - u_1^2) u_2 - u_1) ]
29: Notes:
30: This code demonstrates the TSAdjoint interface to a DAE system.
32: The user provides the implicit right-hand-side function
33: [ F(u',u,t) ] = [u' - f(u,t)] = [ u_1'] - [ u_2 ]
34: [ u_2'] [ \mu ((1-u_1^2)u_2-u_1) ]
36: and the Jacobian of F (from the PETSc user manual)
38: dF dF
39: J(F) = a * -- + --
40: du' du
42: and the JacobianP of the explicit right-hand side of (2) f(u,t) ( which is equivalent to -F(0,u,t)).
43: df [ 0 ]
44: -- = [ ]
45: dp [ (1 - u_1^2) u_2 - u_1 ].
47: See ex20.c for more details on the Jacobian.
49: ------------------------------------------------------------------------- */
50: #include <petscts.h>
51: #include <petsctao.h>
53: typedef struct _n_User *User;
54: struct _n_User {
55: PetscReal mu;
56: PetscReal next_output;
57: PetscBool imex;
58: /* Sensitivity analysis support */
59: PetscInt steps;
60: PetscReal ftime;
61: Mat A; /* IJacobian matrix */
62: Mat B; /* RHSJacobian matrix */
63: Mat Jacp; /* IJacobianP matrix */
64: Mat Jacprhs; /* RHSJacobianP matrix */
65: Vec U, lambda[2], mup[2]; /* adjoint variables */
66: };
68: /* ----------------------- Explicit form of the ODE -------------------- */
70: static PetscErrorCode RHSFunction(TS ts, PetscReal t, Vec U, Vec F, void *ctx)
71: {
72: User user = (User)ctx;
73: PetscScalar *f;
74: const PetscScalar *u;
76: PetscFunctionBeginUser;
77: PetscCall(VecGetArrayRead(U, &u));
78: PetscCall(VecGetArray(F, &f));
79: f[0] = u[1];
80: if (user->imex) {
81: f[1] = 0.0;
82: } else {
83: f[1] = user->mu * ((1. - u[0] * u[0]) * u[1] - u[0]);
84: }
85: PetscCall(VecRestoreArrayRead(U, &u));
86: PetscCall(VecRestoreArray(F, &f));
87: PetscFunctionReturn(PETSC_SUCCESS);
88: }
90: static PetscErrorCode RHSJacobian(TS ts, PetscReal t, Vec U, Mat A, Mat B, void *ctx)
91: {
92: User user = (User)ctx;
93: PetscReal mu = user->mu;
94: PetscInt rowcol[] = {0, 1};
95: PetscScalar J[2][2];
96: const PetscScalar *u;
98: PetscFunctionBeginUser;
99: PetscCall(VecGetArrayRead(U, &u));
100: J[0][0] = 0;
101: J[0][1] = 1.0;
102: if (user->imex) {
103: J[1][0] = 0.0;
104: J[1][1] = 0.0;
105: } else {
106: J[1][0] = -mu * (2.0 * u[1] * u[0] + 1.);
107: J[1][1] = mu * (1.0 - u[0] * u[0]);
108: }
109: PetscCall(MatSetValues(A, 2, rowcol, 2, rowcol, &J[0][0], INSERT_VALUES));
110: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
111: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
112: if (A != B) {
113: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
114: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
115: }
116: PetscCall(VecRestoreArrayRead(U, &u));
117: PetscFunctionReturn(PETSC_SUCCESS);
118: }
120: /* ----------------------- Implicit form of the ODE -------------------- */
122: static PetscErrorCode IFunction(TS ts, PetscReal t, Vec U, Vec Udot, Vec F, void *ctx)
123: {
124: User user = (User)ctx;
125: const PetscScalar *u, *udot;
126: PetscScalar *f;
128: PetscFunctionBeginUser;
129: PetscCall(VecGetArrayRead(U, &u));
130: PetscCall(VecGetArrayRead(Udot, &udot));
131: PetscCall(VecGetArray(F, &f));
132: if (user->imex) {
133: f[0] = udot[0];
134: } else {
135: f[0] = udot[0] - u[1];
136: }
137: f[1] = udot[1] - user->mu * ((1.0 - u[0] * u[0]) * u[1] - u[0]);
138: PetscCall(VecRestoreArrayRead(U, &u));
139: PetscCall(VecRestoreArrayRead(Udot, &udot));
140: PetscCall(VecRestoreArray(F, &f));
141: PetscFunctionReturn(PETSC_SUCCESS);
142: }
144: static PetscErrorCode IJacobian(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal a, Mat A, Mat B, void *ctx)
145: {
146: User user = (User)ctx;
147: PetscInt rowcol[] = {0, 1};
148: PetscScalar J[2][2];
149: const PetscScalar *u;
151: PetscFunctionBeginUser;
152: PetscCall(VecGetArrayRead(U, &u));
154: if (user->imex) {
155: J[0][0] = a;
156: J[0][1] = 0.0;
157: } else {
158: J[0][0] = a;
159: J[0][1] = -1.0;
160: }
161: J[1][0] = user->mu * (2.0 * u[0] * u[1] + 1.0);
162: J[1][1] = a - user->mu * (1.0 - u[0] * u[0]);
164: PetscCall(MatSetValues(B, 2, rowcol, 2, rowcol, &J[0][0], INSERT_VALUES));
165: PetscCall(VecRestoreArrayRead(U, &u));
167: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
168: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
169: if (B && A != B) {
170: PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
171: PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
172: }
173: PetscFunctionReturn(PETSC_SUCCESS);
174: }
176: static PetscErrorCode IJacobianP(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal a, Mat A, void *ctx)
177: {
178: PetscInt row[] = {0, 1}, col[] = {0};
179: PetscScalar J[2][1];
180: const PetscScalar *u;
182: PetscFunctionBeginUser;
183: PetscCall(VecGetArrayRead(U, &u));
184: J[0][0] = 0;
185: J[1][0] = -((1.0 - u[0] * u[0]) * u[1] - u[0]);
186: PetscCall(MatSetValues(A, 2, row, 1, col, &J[0][0], INSERT_VALUES));
187: PetscCall(VecRestoreArrayRead(U, &u));
188: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
189: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
190: PetscFunctionReturn(PETSC_SUCCESS);
191: }
193: static PetscErrorCode RHSJacobianP(TS ts, PetscReal t, Vec U, Mat A, void *ctx)
194: {
195: User user = (User)ctx;
197: PetscFunctionBeginUser;
198: if (!user->imex) {
199: PetscInt row[] = {0, 1}, col[] = {0};
200: PetscScalar J[2][1];
201: const PetscScalar *u;
202: PetscCall(VecGetArrayRead(U, &u));
203: J[0][0] = 0;
204: J[1][0] = (1. - u[0] * u[0]) * u[1] - u[0];
205: PetscCall(MatSetValues(A, 2, row, 1, col, &J[0][0], INSERT_VALUES));
206: PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
207: PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
208: PetscCall(VecRestoreArrayRead(U, &u));
209: }
210: PetscFunctionReturn(PETSC_SUCCESS);
211: }
213: /* Monitor timesteps and use interpolation to output at integer multiples of 0.1 */
214: static PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal t, Vec U, void *ctx)
215: {
216: const PetscScalar *u;
217: PetscReal tfinal, dt;
218: User user = (User)ctx;
219: Vec interpolatedU;
221: PetscFunctionBeginUser;
222: PetscCall(TSGetTimeStep(ts, &dt));
223: PetscCall(TSGetMaxTime(ts, &tfinal));
225: while (user->next_output <= t && user->next_output <= tfinal) {
226: PetscCall(VecDuplicate(U, &interpolatedU));
227: PetscCall(TSInterpolate(ts, user->next_output, interpolatedU));
228: PetscCall(VecGetArrayRead(interpolatedU, &u));
229: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "[%g] %" PetscInt_FMT " TS %g (dt = %g) X %g %g\n", (double)user->next_output, step, (double)t, (double)dt, (double)PetscRealPart(u[0]), (double)PetscRealPart(u[1])));
230: PetscCall(VecRestoreArrayRead(interpolatedU, &u));
231: PetscCall(VecDestroy(&interpolatedU));
232: user->next_output += 0.1;
233: }
234: PetscFunctionReturn(PETSC_SUCCESS);
235: }
237: int main(int argc, char **argv)
238: {
239: TS ts;
240: PetscBool monitor = PETSC_FALSE, implicitform = PETSC_TRUE;
241: PetscScalar *x_ptr, *y_ptr, derp;
242: PetscMPIInt size;
243: struct _n_User user;
245: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
246: Initialize program
247: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
248: PetscFunctionBeginUser;
249: PetscCall(PetscInitialize(&argc, &argv, NULL, help));
250: PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size));
251: PetscCheck(size == 1, PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This is a uniprocessor example only!");
253: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
254: Set runtime options
255: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
256: user.next_output = 0.0;
257: user.mu = 1.0e3;
258: user.steps = 0;
259: user.ftime = 0.5;
260: user.imex = PETSC_FALSE;
261: PetscCall(PetscOptionsGetBool(NULL, NULL, "-monitor", &monitor, NULL));
262: PetscCall(PetscOptionsGetReal(NULL, NULL, "-mu", &user.mu, NULL));
263: PetscCall(PetscOptionsGetBool(NULL, NULL, "-implicitform", &implicitform, NULL));
264: PetscCall(PetscOptionsGetBool(NULL, NULL, "-imexform", &user.imex, NULL));
266: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
267: Create necessary matrix and vectors, solve same ODE on every process
268: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
269: PetscCall(MatCreate(PETSC_COMM_WORLD, &user.A));
270: PetscCall(MatSetSizes(user.A, PETSC_DECIDE, PETSC_DECIDE, 2, 2));
271: PetscCall(MatSetFromOptions(user.A));
272: PetscCall(MatSetUp(user.A));
273: PetscCall(MatCreateVecs(user.A, &user.U, NULL));
274: PetscCall(MatDuplicate(user.A, MAT_DO_NOT_COPY_VALUES, &user.B));
275: PetscCall(MatCreate(PETSC_COMM_WORLD, &user.Jacp));
276: PetscCall(MatSetSizes(user.Jacp, PETSC_DECIDE, PETSC_DECIDE, 2, 1));
277: PetscCall(MatSetFromOptions(user.Jacp));
278: PetscCall(MatSetUp(user.Jacp));
279: PetscCall(MatDuplicate(user.Jacp, MAT_DO_NOT_COPY_VALUES, &user.Jacprhs));
280: PetscCall(MatZeroEntries(user.Jacprhs));
282: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
283: Create timestepping solver context
284: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
285: PetscCall(TSCreate(PETSC_COMM_WORLD, &ts));
286: PetscCall(TSSetEquationType(ts, TS_EQ_ODE_EXPLICIT)); /* less Jacobian evaluations when adjoint BEuler is used, otherwise no effect */
287: if (user.imex) {
288: PetscCall(TSSetIFunction(ts, NULL, IFunction, &user));
289: PetscCall(TSSetIJacobian(ts, user.A, user.A, IJacobian, &user));
290: PetscCall(TSSetIJacobianP(ts, user.Jacp, IJacobianP, &user));
291: PetscCall(TSSetRHSFunction(ts, NULL, RHSFunction, &user));
292: PetscCall(TSSetRHSJacobian(ts, user.B, NULL, RHSJacobian, &user));
293: PetscCall(TSSetRHSJacobianP(ts, user.Jacprhs, NULL, &user));
294: PetscCall(TSSetType(ts, TSARKIMEX));
295: } else {
296: if (implicitform) {
297: PetscCall(TSSetIFunction(ts, NULL, IFunction, &user));
298: PetscCall(TSSetIJacobian(ts, user.A, user.A, IJacobian, &user));
299: PetscCall(TSSetIJacobianP(ts, user.Jacp, IJacobianP, &user));
300: PetscCall(TSSetType(ts, TSCN));
301: } else {
302: PetscCall(TSSetRHSFunction(ts, NULL, RHSFunction, &user));
303: PetscCall(TSSetRHSJacobian(ts, user.A, user.A, RHSJacobian, &user));
304: PetscCall(TSSetRHSJacobianP(ts, user.Jacp, RHSJacobianP, &user));
305: PetscCall(TSSetType(ts, TSRK));
306: }
307: }
308: PetscCall(TSSetMaxTime(ts, user.ftime));
309: PetscCall(TSSetTimeStep(ts, 0.001));
310: PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_MATCHSTEP));
311: if (monitor) PetscCall(TSMonitorSet(ts, Monitor, &user, NULL));
313: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
314: Set initial conditions
315: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
316: PetscCall(VecGetArray(user.U, &x_ptr));
317: x_ptr[0] = 2.0;
318: x_ptr[1] = -2.0 / 3.0 + 10.0 / (81.0 * user.mu) - 292.0 / (2187.0 * user.mu * user.mu);
319: PetscCall(VecRestoreArray(user.U, &x_ptr));
320: PetscCall(TSSetTimeStep(ts, 0.001));
322: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
323: Save trajectory of solution so that TSAdjointSolve() may be used
324: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
325: PetscCall(TSSetSaveTrajectory(ts));
327: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
328: Set runtime options
329: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
330: PetscCall(TSSetFromOptions(ts));
332: PetscCall(TSSolve(ts, user.U));
333: PetscCall(TSGetSolveTime(ts, &user.ftime));
334: PetscCall(TSGetStepNumber(ts, &user.steps));
336: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
337: Adjoint model starts here
338: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
339: PetscCall(MatCreateVecs(user.A, &user.lambda[0], NULL));
340: /* Set initial conditions for the adjoint integration */
341: PetscCall(VecGetArray(user.lambda[0], &y_ptr));
342: y_ptr[0] = 1.0;
343: y_ptr[1] = 0.0;
344: PetscCall(VecRestoreArray(user.lambda[0], &y_ptr));
345: PetscCall(MatCreateVecs(user.A, &user.lambda[1], NULL));
346: PetscCall(VecGetArray(user.lambda[1], &y_ptr));
347: y_ptr[0] = 0.0;
348: y_ptr[1] = 1.0;
349: PetscCall(VecRestoreArray(user.lambda[1], &y_ptr));
351: PetscCall(MatCreateVecs(user.Jacp, &user.mup[0], NULL));
352: PetscCall(VecGetArray(user.mup[0], &x_ptr));
353: x_ptr[0] = 0.0;
354: PetscCall(VecRestoreArray(user.mup[0], &x_ptr));
355: PetscCall(MatCreateVecs(user.Jacp, &user.mup[1], NULL));
356: PetscCall(VecGetArray(user.mup[1], &x_ptr));
357: x_ptr[0] = 0.0;
358: PetscCall(VecRestoreArray(user.mup[1], &x_ptr));
360: PetscCall(TSSetCostGradients(ts, 2, user.lambda, user.mup));
362: PetscCall(TSAdjointSolve(ts));
364: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt initial conditions: d[y(tf)]/d[y0] d[y(tf)]/d[z0]\n"));
365: PetscCall(VecView(user.lambda[0], PETSC_VIEWER_STDOUT_WORLD));
366: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt initial conditions: d[z(tf)]/d[y0] d[z(tf)]/d[z0]\n"));
367: PetscCall(VecView(user.lambda[1], PETSC_VIEWER_STDOUT_WORLD));
369: PetscCall(VecGetArray(user.mup[0], &x_ptr));
370: PetscCall(VecGetArray(user.lambda[0], &y_ptr));
371: derp = y_ptr[1] * (-10.0 / (81.0 * user.mu * user.mu) + 2.0 * 292.0 / (2187.0 * user.mu * user.mu * user.mu)) + x_ptr[0];
372: PetscCall(VecRestoreArray(user.mup[0], &x_ptr));
373: PetscCall(VecRestoreArray(user.lambda[0], &y_ptr));
374: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt parameters: d[y(tf)]/d[mu]\n%g\n", (double)PetscRealPart(derp)));
376: PetscCall(VecGetArray(user.mup[1], &x_ptr));
377: PetscCall(VecGetArray(user.lambda[1], &y_ptr));
378: derp = y_ptr[1] * (-10.0 / (81.0 * user.mu * user.mu) + 2.0 * 292.0 / (2187.0 * user.mu * user.mu * user.mu)) + x_ptr[0];
379: PetscCall(VecRestoreArray(user.mup[1], &x_ptr));
380: PetscCall(VecRestoreArray(user.lambda[1], &y_ptr));
381: PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensivitity wrt parameters: d[z(tf)]/d[mu]\n%g\n", (double)PetscRealPart(derp)));
383: /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
384: Free work space. All PETSc objects should be destroyed when they
385: are no longer needed.
386: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
387: PetscCall(MatDestroy(&user.A));
388: PetscCall(MatDestroy(&user.B));
389: PetscCall(MatDestroy(&user.Jacp));
390: PetscCall(MatDestroy(&user.Jacprhs));
391: PetscCall(VecDestroy(&user.U));
392: PetscCall(VecDestroy(&user.lambda[0]));
393: PetscCall(VecDestroy(&user.lambda[1]));
394: PetscCall(VecDestroy(&user.mup[0]));
395: PetscCall(VecDestroy(&user.mup[1]));
396: PetscCall(TSDestroy(&ts));
398: PetscCall(PetscFinalize());
399: return 0;
400: }
402: /*TEST
404: test:
405: requires: revolve
406: args: -monitor 0 -ts_type theta -ts_theta_endpoint -ts_theta_theta 0.5 -viewer_binary_skip_info -ts_dt 0.001 -mu 100000
408: test:
409: suffix: 2
410: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only
412: test:
413: suffix: 3
414: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only 0
415: output_file: output/ex20adj_2.out
417: test:
418: suffix: 4
419: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_stride 5 -ts_trajectory_solution_only -ts_trajectory_save_stack
420: output_file: output/ex20adj_2.out
422: test:
423: suffix: 5
424: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack
425: output_file: output/ex20adj_2.out
427: test:
428: suffix: 6
429: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_stride 5 -ts_trajectory_solution_only -ts_trajectory_save_stack 0
430: output_file: output/ex20adj_2.out
432: test:
433: suffix: 7
434: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack 0
435: output_file: output/ex20adj_2.out
437: test:
438: suffix: 8
439: requires: revolve !cams
440: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 5 -ts_trajectory_solution_only -ts_trajectory_monitor
441: output_file: output/ex20adj_3.out
443: test:
444: suffix: 9
445: requires: revolve !cams
446: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 5 -ts_trajectory_solution_only 0 -ts_trajectory_monitor
447: output_file: output/ex20adj_4.out
449: test:
450: requires: revolve
451: suffix: 10
452: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 5 -ts_trajectory_revolve_online -ts_trajectory_solution_only
453: output_file: output/ex20adj_2.out
455: test:
456: requires: revolve
457: suffix: 11
458: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 5 -ts_trajectory_revolve_online -ts_trajectory_solution_only 0
459: output_file: output/ex20adj_2.out
461: test:
462: suffix: 12
463: requires: revolve
464: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_solution_only
465: output_file: output/ex20adj_2.out
467: test:
468: suffix: 13
469: requires: revolve
470: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_solution_only 0
471: output_file: output/ex20adj_2.out
473: test:
474: suffix: 14
475: requires: revolve
476: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_stride 5 -ts_trajectory_solution_only -ts_trajectory_save_stack
477: output_file: output/ex20adj_2.out
479: test:
480: suffix: 15
481: requires: revolve
482: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_stride 5 -ts_trajectory_solution_only -ts_trajectory_save_stack 0
483: output_file: output/ex20adj_2.out
485: test:
486: suffix: 16
487: requires: revolve
488: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack
489: output_file: output/ex20adj_2.out
491: test:
492: suffix: 17
493: requires: revolve
494: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack 0
495: output_file: output/ex20adj_2.out
497: test:
498: suffix: 18
499: requires: revolve
500: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_stride 5 -ts_trajectory_solution_only -ts_trajectory_save_stack
501: output_file: output/ex20adj_2.out
503: test:
504: suffix: 19
505: requires: revolve
506: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack
507: output_file: output/ex20adj_2.out
509: test:
510: suffix: 20
511: requires: revolve
512: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_solution_only 0
513: output_file: output/ex20adj_2.out
515: test:
516: suffix: 21
517: requires: revolve
518: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_cps_ram 3 -ts_trajectory_max_cps_disk 8 -ts_trajectory_stride 5 -ts_trajectory_solution_only 0 -ts_trajectory_save_stack 0
519: output_file: output/ex20adj_2.out
521: test:
522: suffix: 22
523: args: -ts_type beuler -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only
524: output_file: output/ex20adj_2.out
526: test:
527: suffix: 23
528: requires: cams
529: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_units_ram 5 -ts_trajectory_solution_only -ts_trajectory_monitor -ts_trajectory_memory_type cams
530: output_file: output/ex20adj_5.out
532: test:
533: suffix: 24
534: requires: cams
535: args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_max_units_ram 5 -ts_trajectory_solution_only 0 -ts_trajectory_monitor -ts_trajectory_memory_type cams
536: output_file: output/ex20adj_6.out
538: test:
539: suffix: 25
540: args: -imexform -ts_max_steps 15 -ts_trajectory_type memory
541: output_file: output/ex20adj_imex.out
542: TEST*/