static char help[] = "Solves a ODE-constrained optimization problem -- finding the optimal initial conditions for the van der Pol equation.\n"; /* Notes: This code demonstrates how to solve an ODE-constrained optimization problem with TAO, TSAdjoint and TS. The nonlinear problem is written in an ODE equivalent form. The objective is to minimize the difference between observation and model prediction by finding optimal values for initial conditions. The gradient is computed with the discrete adjoint of an implicit method or an explicit method, see ex20adj.c for details. */ #include #include typedef struct _n_User *User; struct _n_User { TS ts; PetscReal mu; PetscReal next_output; /* Sensitivity analysis support */ PetscInt steps; PetscReal ftime; Mat A; /* Jacobian matrix for ODE */ Mat Jacp; /* JacobianP matrix for ODE*/ Mat H; /* Hessian matrix for optimization */ Vec U, Lambda[1], Mup[1]; /* first-order adjoint variables */ Vec Lambda2[2]; /* second-order adjoint variables */ Vec Ihp1[1]; /* working space for Hessian evaluations */ Vec Dir; /* direction vector */ PetscReal ob[2]; /* observation used by the cost function */ PetscBool implicitform; /* implicit ODE? */ }; PetscErrorCode Adjoint2(Vec, PetscScalar[], User); /* ----------------------- Explicit form of the ODE -------------------- */ static PetscErrorCode RHSFunction(TS ts, PetscReal t, Vec U, Vec F, void *ctx) { User user = (User)ctx; PetscScalar *f; const PetscScalar *u; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); PetscCall(VecGetArray(F, &f)); f[0] = u[1]; f[1] = user->mu * ((1. - u[0] * u[0]) * u[1] - u[0]); PetscCall(VecRestoreArrayRead(U, &u)); PetscCall(VecRestoreArray(F, &f)); PetscFunctionReturn(0); } static PetscErrorCode RHSJacobian(TS ts, PetscReal t, Vec U, Mat A, Mat B, void *ctx) { User user = (User)ctx; PetscReal mu = user->mu; PetscInt rowcol[] = {0, 1}; PetscScalar J[2][2]; const PetscScalar *u; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); J[0][0] = 0; J[1][0] = -mu * (2.0 * u[1] * u[0] + 1.); J[0][1] = 1.0; J[1][1] = mu * (1.0 - u[0] * u[0]); PetscCall(MatSetValues(A, 2, rowcol, 2, rowcol, &J[0][0], INSERT_VALUES)); PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); if (A != B) { PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); } PetscCall(VecRestoreArrayRead(U, &u)); PetscFunctionReturn(0); } static PetscErrorCode RHSHessianProductUU(TS ts, PetscReal t, Vec U, Vec *Vl, Vec Vr, Vec *VHV, void *ctx) { const PetscScalar *vl, *vr, *u; PetscScalar *vhv; PetscScalar dJdU[2][2][2] = {{{0}}}; PetscInt i, j, k; User user = (User)ctx; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); PetscCall(VecGetArrayRead(Vl[0], &vl)); PetscCall(VecGetArrayRead(Vr, &vr)); PetscCall(VecGetArray(VHV[0], &vhv)); dJdU[1][0][0] = -2. * user->mu * u[1]; dJdU[1][1][0] = -2. * user->mu * u[0]; dJdU[1][0][1] = -2. * user->mu * u[0]; for (j = 0; j < 2; j++) { vhv[j] = 0; for (k = 0; k < 2; k++) for (i = 0; i < 2; i++) vhv[j] += vl[i] * dJdU[i][j][k] * vr[k]; } PetscCall(VecRestoreArrayRead(U, &u)); PetscCall(VecRestoreArrayRead(Vl[0], &vl)); PetscCall(VecRestoreArrayRead(Vr, &vr)); PetscCall(VecRestoreArray(VHV[0], &vhv)); PetscFunctionReturn(0); } /* ----------------------- Implicit form of the ODE -------------------- */ static PetscErrorCode IFunction(TS ts, PetscReal t, Vec U, Vec Udot, Vec F, void *ctx) { User user = (User)ctx; const PetscScalar *u, *udot; PetscScalar *f; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); PetscCall(VecGetArrayRead(Udot, &udot)); PetscCall(VecGetArray(F, &f)); f[0] = udot[0] - u[1]; f[1] = udot[1] - user->mu * ((1.0 - u[0] * u[0]) * u[1] - u[0]); PetscCall(VecRestoreArrayRead(U, &u)); PetscCall(VecRestoreArrayRead(Udot, &udot)); PetscCall(VecRestoreArray(F, &f)); PetscFunctionReturn(0); } static PetscErrorCode IJacobian(TS ts, PetscReal t, Vec U, Vec Udot, PetscReal a, Mat A, Mat B, void *ctx) { User user = (User)ctx; PetscInt rowcol[] = {0, 1}; PetscScalar J[2][2]; const PetscScalar *u; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); J[0][0] = a; J[0][1] = -1.0; J[1][0] = user->mu * (1.0 + 2.0 * u[0] * u[1]); J[1][1] = a - user->mu * (1.0 - u[0] * u[0]); PetscCall(MatSetValues(B, 2, rowcol, 2, rowcol, &J[0][0], INSERT_VALUES)); PetscCall(VecRestoreArrayRead(U, &u)); PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY)); if (A != B) { PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY)); } PetscFunctionReturn(0); } /* Monitor timesteps and use interpolation to output at integer multiples of 0.1 */ static PetscErrorCode Monitor(TS ts, PetscInt step, PetscReal t, Vec U, void *ctx) { const PetscScalar *u; PetscReal tfinal, dt; User user = (User)ctx; Vec interpolatedU; PetscFunctionBeginUser; PetscCall(TSGetTimeStep(ts, &dt)); PetscCall(TSGetMaxTime(ts, &tfinal)); while (user->next_output <= t && user->next_output <= tfinal) { PetscCall(VecDuplicate(U, &interpolatedU)); PetscCall(TSInterpolate(ts, user->next_output, interpolatedU)); PetscCall(VecGetArrayRead(interpolatedU, &u)); 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]))); PetscCall(VecRestoreArrayRead(interpolatedU, &u)); PetscCall(VecDestroy(&interpolatedU)); user->next_output += 0.1; } PetscFunctionReturn(0); } static PetscErrorCode IHessianProductUU(TS ts, PetscReal t, Vec U, Vec *Vl, Vec Vr, Vec *VHV, void *ctx) { const PetscScalar *vl, *vr, *u; PetscScalar *vhv; PetscScalar dJdU[2][2][2] = {{{0}}}; PetscInt i, j, k; User user = (User)ctx; PetscFunctionBeginUser; PetscCall(VecGetArrayRead(U, &u)); PetscCall(VecGetArrayRead(Vl[0], &vl)); PetscCall(VecGetArrayRead(Vr, &vr)); PetscCall(VecGetArray(VHV[0], &vhv)); dJdU[1][0][0] = 2. * user->mu * u[1]; dJdU[1][1][0] = 2. * user->mu * u[0]; dJdU[1][0][1] = 2. * user->mu * u[0]; for (j = 0; j < 2; j++) { vhv[j] = 0; for (k = 0; k < 2; k++) for (i = 0; i < 2; i++) vhv[j] += vl[i] * dJdU[i][j][k] * vr[k]; } PetscCall(VecRestoreArrayRead(U, &u)); PetscCall(VecRestoreArrayRead(Vl[0], &vl)); PetscCall(VecRestoreArrayRead(Vr, &vr)); PetscCall(VecRestoreArray(VHV[0], &vhv)); PetscFunctionReturn(0); } /* ------------------ User-defined routines for TAO -------------------------- */ static PetscErrorCode FormFunctionGradient(Tao tao, Vec IC, PetscReal *f, Vec G, void *ctx) { User user_ptr = (User)ctx; TS ts = user_ptr->ts; const PetscScalar *x_ptr; PetscScalar *y_ptr; PetscFunctionBeginUser; PetscCall(VecCopy(IC, user_ptr->U)); /* set up the initial condition */ PetscCall(TSSetTime(ts, 0.0)); PetscCall(TSSetStepNumber(ts, 0)); PetscCall(TSSetTimeStep(ts, 0.001)); /* can be overwritten by command line options */ PetscCall(TSSetFromOptions(ts)); PetscCall(TSSolve(ts, user_ptr->U)); PetscCall(VecGetArrayRead(user_ptr->U, &x_ptr)); PetscCall(VecGetArray(user_ptr->Lambda[0], &y_ptr)); *f = (x_ptr[0] - user_ptr->ob[0]) * (x_ptr[0] - user_ptr->ob[0]) + (x_ptr[1] - user_ptr->ob[1]) * (x_ptr[1] - user_ptr->ob[1]); y_ptr[0] = 2. * (x_ptr[0] - user_ptr->ob[0]); y_ptr[1] = 2. * (x_ptr[1] - user_ptr->ob[1]); PetscCall(VecRestoreArray(user_ptr->Lambda[0], &y_ptr)); PetscCall(VecRestoreArrayRead(user_ptr->U, &x_ptr)); PetscCall(TSSetCostGradients(ts, 1, user_ptr->Lambda, NULL)); PetscCall(TSAdjointSolve(ts)); PetscCall(VecCopy(user_ptr->Lambda[0], G)); PetscFunctionReturn(0); } static PetscErrorCode FormHessian(Tao tao, Vec U, Mat H, Mat Hpre, void *ctx) { User user_ptr = (User)ctx; PetscScalar harr[2]; PetscScalar *x_ptr; const PetscInt rows[2] = {0, 1}; PetscInt col; PetscFunctionBeginUser; PetscCall(VecCopy(U, user_ptr->U)); PetscCall(VecGetArray(user_ptr->Dir, &x_ptr)); x_ptr[0] = 1.; x_ptr[1] = 0.; PetscCall(VecRestoreArray(user_ptr->Dir, &x_ptr)); PetscCall(Adjoint2(user_ptr->U, harr, user_ptr)); col = 0; PetscCall(MatSetValues(H, 2, rows, 1, &col, harr, INSERT_VALUES)); PetscCall(VecCopy(U, user_ptr->U)); PetscCall(VecGetArray(user_ptr->Dir, &x_ptr)); x_ptr[0] = 0.; x_ptr[1] = 1.; PetscCall(VecRestoreArray(user_ptr->Dir, &x_ptr)); PetscCall(Adjoint2(user_ptr->U, harr, user_ptr)); col = 1; PetscCall(MatSetValues(H, 2, rows, 1, &col, harr, INSERT_VALUES)); PetscCall(MatAssemblyBegin(H, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(H, MAT_FINAL_ASSEMBLY)); if (H != Hpre) { PetscCall(MatAssemblyBegin(Hpre, MAT_FINAL_ASSEMBLY)); PetscCall(MatAssemblyEnd(Hpre, MAT_FINAL_ASSEMBLY)); } PetscFunctionReturn(0); } static PetscErrorCode MatrixFreeHessian(Tao tao, Vec U, Mat H, Mat Hpre, void *ctx) { User user_ptr = (User)ctx; PetscFunctionBeginUser; PetscCall(VecCopy(U, user_ptr->U)); PetscFunctionReturn(0); } /* ------------ Routines calculating second-order derivatives -------------- */ /* Compute the Hessian-vector product for the cost function using Second-order adjoint */ PetscErrorCode Adjoint2(Vec U, PetscScalar arr[], User ctx) { TS ts = ctx->ts; PetscScalar *x_ptr, *y_ptr; Mat tlmsen; PetscFunctionBeginUser; PetscCall(TSAdjointReset(ts)); PetscCall(TSSetTime(ts, 0.0)); PetscCall(TSSetStepNumber(ts, 0)); PetscCall(TSSetTimeStep(ts, 0.001)); PetscCall(TSSetFromOptions(ts)); PetscCall(TSSetCostHessianProducts(ts, 1, ctx->Lambda2, NULL, ctx->Dir)); PetscCall(TSAdjointSetForward(ts, NULL)); PetscCall(TSSolve(ts, U)); /* Set terminal conditions for first- and second-order adjonts */ PetscCall(VecGetArray(U, &x_ptr)); PetscCall(VecGetArray(ctx->Lambda[0], &y_ptr)); y_ptr[0] = 2. * (x_ptr[0] - ctx->ob[0]); y_ptr[1] = 2. * (x_ptr[1] - ctx->ob[1]); PetscCall(VecRestoreArray(ctx->Lambda[0], &y_ptr)); PetscCall(VecRestoreArray(U, &x_ptr)); PetscCall(TSForwardGetSensitivities(ts, NULL, &tlmsen)); PetscCall(MatDenseGetColumn(tlmsen, 0, &x_ptr)); PetscCall(VecGetArray(ctx->Lambda2[0], &y_ptr)); y_ptr[0] = 2. * x_ptr[0]; y_ptr[1] = 2. * x_ptr[1]; PetscCall(VecRestoreArray(ctx->Lambda2[0], &y_ptr)); PetscCall(MatDenseRestoreColumn(tlmsen, &x_ptr)); PetscCall(TSSetCostGradients(ts, 1, ctx->Lambda, NULL)); if (ctx->implicitform) { PetscCall(TSSetIHessianProduct(ts, ctx->Ihp1, IHessianProductUU, NULL, NULL, NULL, NULL, NULL, NULL, ctx)); } else { PetscCall(TSSetRHSHessianProduct(ts, ctx->Ihp1, RHSHessianProductUU, NULL, NULL, NULL, NULL, NULL, NULL, ctx)); } PetscCall(TSAdjointSolve(ts)); PetscCall(VecGetArray(ctx->Lambda2[0], &x_ptr)); arr[0] = x_ptr[0]; arr[1] = x_ptr[1]; PetscCall(VecRestoreArray(ctx->Lambda2[0], &x_ptr)); PetscCall(TSAdjointReset(ts)); PetscCall(TSAdjointResetForward(ts)); PetscFunctionReturn(0); } PetscErrorCode FiniteDiff(Vec U, PetscScalar arr[], User ctx) { Vec Up, G, Gp; const PetscScalar eps = PetscRealConstant(1e-7); PetscScalar *u; Tao tao = NULL; PetscReal f; PetscFunctionBeginUser; PetscCall(VecDuplicate(U, &Up)); PetscCall(VecDuplicate(U, &G)); PetscCall(VecDuplicate(U, &Gp)); PetscCall(FormFunctionGradient(tao, U, &f, G, ctx)); PetscCall(VecCopy(U, Up)); PetscCall(VecGetArray(Up, &u)); u[0] += eps; PetscCall(VecRestoreArray(Up, &u)); PetscCall(FormFunctionGradient(tao, Up, &f, Gp, ctx)); PetscCall(VecAXPY(Gp, -1, G)); PetscCall(VecScale(Gp, 1. / eps)); PetscCall(VecGetArray(Gp, &u)); arr[0] = u[0]; arr[1] = u[1]; PetscCall(VecRestoreArray(Gp, &u)); PetscCall(VecCopy(U, Up)); PetscCall(VecGetArray(Up, &u)); u[1] += eps; PetscCall(VecRestoreArray(Up, &u)); PetscCall(FormFunctionGradient(tao, Up, &f, Gp, ctx)); PetscCall(VecAXPY(Gp, -1, G)); PetscCall(VecScale(Gp, 1. / eps)); PetscCall(VecGetArray(Gp, &u)); arr[2] = u[0]; arr[3] = u[1]; PetscCall(VecRestoreArray(Gp, &u)); PetscCall(VecDestroy(&G)); PetscCall(VecDestroy(&Gp)); PetscCall(VecDestroy(&Up)); PetscFunctionReturn(0); } static PetscErrorCode HessianProductMat(Mat mat, Vec svec, Vec y) { User user_ptr; PetscScalar *y_ptr; PetscFunctionBeginUser; PetscCall(MatShellGetContext(mat, &user_ptr)); PetscCall(VecCopy(svec, user_ptr->Dir)); PetscCall(VecGetArray(y, &y_ptr)); PetscCall(Adjoint2(user_ptr->U, y_ptr, user_ptr)); PetscCall(VecRestoreArray(y, &y_ptr)); PetscFunctionReturn(0); } int main(int argc, char **argv) { PetscBool monitor = PETSC_FALSE, mf = PETSC_TRUE; PetscInt mode = 0; PetscMPIInt size; struct _n_User user; Vec x; /* working vector for TAO */ PetscScalar *x_ptr, arr[4]; PetscScalar ic1 = 2.2, ic2 = -0.7; /* initial guess for TAO */ Tao tao; KSP ksp; PC pc; /* Initialize program */ PetscFunctionBeginUser; PetscCall(PetscInitialize(&argc, &argv, NULL, help)); PetscCallMPI(MPI_Comm_size(PETSC_COMM_WORLD, &size)); PetscCheck(size == 1, PETSC_COMM_WORLD, PETSC_ERR_WRONG_MPI_SIZE, "This is a uniprocessor example only!"); /* Set runtime options */ user.next_output = 0.0; user.mu = 1.0e3; user.steps = 0; user.ftime = 0.5; user.implicitform = PETSC_TRUE; PetscCall(PetscOptionsGetBool(NULL, NULL, "-monitor", &monitor, NULL)); PetscCall(PetscOptionsGetReal(NULL, NULL, "-mu", &user.mu, NULL)); PetscCall(PetscOptionsGetInt(NULL, NULL, "-mode", &mode, NULL)); PetscCall(PetscOptionsGetReal(NULL, NULL, "-ic1", &ic1, NULL)); PetscCall(PetscOptionsGetReal(NULL, NULL, "-ic2", &ic2, NULL)); PetscCall(PetscOptionsGetBool(NULL, NULL, "-my_tao_mf", &mf, NULL)); /* matrix-free hessian for optimization */ PetscCall(PetscOptionsGetBool(NULL, NULL, "-implicitform", &user.implicitform, NULL)); /* Create necessary matrix and vectors, solve same ODE on every process */ PetscCall(MatCreate(PETSC_COMM_WORLD, &user.A)); PetscCall(MatSetSizes(user.A, PETSC_DECIDE, PETSC_DECIDE, 2, 2)); PetscCall(MatSetFromOptions(user.A)); PetscCall(MatSetUp(user.A)); PetscCall(MatCreateVecs(user.A, &user.U, NULL)); PetscCall(MatCreateVecs(user.A, &user.Dir, NULL)); PetscCall(MatCreateVecs(user.A, &user.Lambda[0], NULL)); PetscCall(MatCreateVecs(user.A, &user.Lambda2[0], NULL)); PetscCall(MatCreateVecs(user.A, &user.Ihp1[0], NULL)); /* Create timestepping solver context */ PetscCall(TSCreate(PETSC_COMM_WORLD, &user.ts)); PetscCall(TSSetEquationType(user.ts, TS_EQ_ODE_EXPLICIT)); /* less Jacobian evaluations when adjoint BEuler is used, otherwise no effect */ if (user.implicitform) { PetscCall(TSSetIFunction(user.ts, NULL, IFunction, &user)); PetscCall(TSSetIJacobian(user.ts, user.A, user.A, IJacobian, &user)); PetscCall(TSSetType(user.ts, TSCN)); } else { PetscCall(TSSetRHSFunction(user.ts, NULL, RHSFunction, &user)); PetscCall(TSSetRHSJacobian(user.ts, user.A, user.A, RHSJacobian, &user)); PetscCall(TSSetType(user.ts, TSRK)); } PetscCall(TSSetMaxTime(user.ts, user.ftime)); PetscCall(TSSetExactFinalTime(user.ts, TS_EXACTFINALTIME_MATCHSTEP)); if (monitor) { PetscCall(TSMonitorSet(user.ts, Monitor, &user, NULL)); } /* Set ODE initial conditions */ PetscCall(VecGetArray(user.U, &x_ptr)); x_ptr[0] = 2.0; x_ptr[1] = -2.0 / 3.0 + 10.0 / (81.0 * user.mu) - 292.0 / (2187.0 * user.mu * user.mu); PetscCall(VecRestoreArray(user.U, &x_ptr)); /* Set runtime options */ PetscCall(TSSetFromOptions(user.ts)); /* Obtain the observation */ PetscCall(TSSolve(user.ts, user.U)); PetscCall(VecGetArray(user.U, &x_ptr)); user.ob[0] = x_ptr[0]; user.ob[1] = x_ptr[1]; PetscCall(VecRestoreArray(user.U, &x_ptr)); PetscCall(VecDuplicate(user.U, &x)); PetscCall(VecGetArray(x, &x_ptr)); x_ptr[0] = ic1; x_ptr[1] = ic2; PetscCall(VecRestoreArray(x, &x_ptr)); /* Save trajectory of solution so that TSAdjointSolve() may be used */ PetscCall(TSSetSaveTrajectory(user.ts)); /* Compare finite difference and second-order adjoint. */ switch (mode) { case 2: PetscCall(FiniteDiff(x, arr, &user)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n Finite difference approximation of the Hessian\n")); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%g %g\n%g %g\n", (double)arr[0], (double)arr[1], (double)arr[2], (double)arr[3])); break; case 1: /* Compute the Hessian column by column */ PetscCall(VecCopy(x, user.U)); PetscCall(VecGetArray(user.Dir, &x_ptr)); x_ptr[0] = 1.; x_ptr[1] = 0.; PetscCall(VecRestoreArray(user.Dir, &x_ptr)); PetscCall(Adjoint2(user.U, arr, &user)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\nFirst column of the Hessian\n")); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%g\n%g\n", (double)arr[0], (double)arr[1])); PetscCall(VecCopy(x, user.U)); PetscCall(VecGetArray(user.Dir, &x_ptr)); x_ptr[0] = 0.; x_ptr[1] = 1.; PetscCall(VecRestoreArray(user.Dir, &x_ptr)); PetscCall(Adjoint2(user.U, arr, &user)); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\nSecond column of the Hessian\n")); PetscCall(PetscPrintf(PETSC_COMM_WORLD, "%g\n%g\n", (double)arr[0], (double)arr[1])); break; case 0: /* Create optimization context and set up */ PetscCall(TaoCreate(PETSC_COMM_WORLD, &tao)); PetscCall(TaoSetType(tao, TAOBLMVM)); PetscCall(TaoSetObjectiveAndGradient(tao, NULL, FormFunctionGradient, (void *)&user)); if (mf) { PetscCall(MatCreateShell(PETSC_COMM_SELF, 2, 2, 2, 2, (void *)&user, &user.H)); PetscCall(MatShellSetOperation(user.H, MATOP_MULT, (void (*)(void))HessianProductMat)); PetscCall(MatSetOption(user.H, MAT_SYMMETRIC, PETSC_TRUE)); PetscCall(TaoSetHessian(tao, user.H, user.H, MatrixFreeHessian, (void *)&user)); } else { /* Create Hessian matrix */ PetscCall(MatCreate(PETSC_COMM_WORLD, &user.H)); PetscCall(MatSetSizes(user.H, PETSC_DECIDE, PETSC_DECIDE, 2, 2)); PetscCall(MatSetUp(user.H)); PetscCall(TaoSetHessian(tao, user.H, user.H, FormHessian, (void *)&user)); } /* Not use any preconditioner */ PetscCall(TaoGetKSP(tao, &ksp)); if (ksp) { PetscCall(KSPGetPC(ksp, &pc)); PetscCall(PCSetType(pc, PCNONE)); } /* Set initial solution guess */ PetscCall(TaoSetSolution(tao, x)); PetscCall(TaoSetFromOptions(tao)); PetscCall(TaoSolve(tao)); PetscCall(TaoDestroy(&tao)); PetscCall(MatDestroy(&user.H)); break; default: break; } /* Free work space. All PETSc objects should be destroyed when they are no longer needed. */ PetscCall(MatDestroy(&user.A)); PetscCall(VecDestroy(&user.U)); PetscCall(VecDestroy(&user.Lambda[0])); PetscCall(VecDestroy(&user.Lambda2[0])); PetscCall(VecDestroy(&user.Ihp1[0])); PetscCall(VecDestroy(&user.Dir)); PetscCall(TSDestroy(&user.ts)); PetscCall(VecDestroy(&x)); PetscCall(PetscFinalize()); return 0; } /*TEST build: requires: !complex !single test: args: -ts_type cn -viewer_binary_skip_info -tao_monitor -tao_view -mu 1000 -ts_dt 0.03125 output_file: output/ex20opt_ic_1.out test: suffix: 2 args: -ts_type beuler -viewer_binary_skip_info -tao_monitor -tao_view -mu 100 -ts_dt 0.01 -tao_type bntr -tao_bnk_pc_type none output_file: output/ex20opt_ic_2.out test: suffix: 3 args: -ts_type cn -viewer_binary_skip_info -tao_monitor -tao_view -mu 100 -ts_dt 0.01 -tao_type bntr -tao_bnk_pc_type none output_file: output/ex20opt_ic_3.out test: suffix: 4 args: -implicitform 0 -ts_dt 0.01 -ts_max_steps 2 -ts_rhs_jacobian_test_mult_transpose -mat_shell_test_mult_transpose_view -ts_rhs_jacobian_test_mult -mat_shell_test_mult_view -mode 1 -my_tao_mf TEST*/