xref: /petsc/src/ts/tutorials/ex20adj.c (revision 3ba1676111f5c958fe6c2729b46ca4d523958bb3)

static char help[] = "Performs adjoint sensitivity analysis for the van der Pol equation.\n";

/* ------------------------------------------------------------------------

   This program solves the van der Pol DAE ODE equivalent
      [ u_1' ] = [          u_2                ]  (2)
      [ u_2' ]   [ \mu ((1 - u_1^2) u_2 - u_1) ]
   on the domain 0 <= x <= 1, with the boundary conditions
       u_1(0) = 2, u_2(0) = - 2/3 +10/(81*\mu) - 292/(2187*\mu^2),
   and
       \mu = 10^6 ( y'(0) ~ -0.6666665432100101).,
   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.

   Notes:
   This code demonstrates the TSAdjoint interface to a DAE system.

   The user provides the implicit right-hand-side function
   [ F(u',u,t) ] = [u' - f(u,t)] = [ u_1'] - [        u_2             ]
                                   [ u_2']   [ \mu ((1-u_1^2)u_2-u_1) ]

   and the Jacobian of F (from the PETSc user manual)

              dF   dF
   J(F) = a * -- + --
              du'  du

   and the JacobianP of the explicit right-hand side of (2) f(u,t) ( which is equivalent to -F(0,u,t)).
   df   [       0               ]
   -- = [                       ]
   dp   [ (1 - u_1^2) u_2 - u_1 ].

   See ex20.c for more details on the Jacobian.

  ------------------------------------------------------------------------- */
#include <petscts.h>
#include <petsctao.h>

typedef struct _n_User *User;
struct _n_User {
  PetscReal mu;
  PetscReal next_output;

  /* Sensitivity analysis support */
  PetscInt  steps;
  PetscReal ftime;
  Mat       A;                    /* Jacobian matrix */
  Mat       Jacp;                 /* JacobianP matrix */
  Vec       U, lambda[2], mup[2]; /* adjoint variables */
};

/* ----------------------- 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(PETSC_SUCCESS);
}

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(PETSC_SUCCESS);
}

/* ----------------------- 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(PETSC_SUCCESS);
}

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 * (2.0 * u[0] * u[1] + 1.0);
  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 (B && A != B) {
    PetscCall(MatAssemblyBegin(B, MAT_FINAL_ASSEMBLY));
    PetscCall(MatAssemblyEnd(B, MAT_FINAL_ASSEMBLY));
  }
  PetscFunctionReturn(PETSC_SUCCESS);
}

static PetscErrorCode RHSJacobianP(TS ts, PetscReal t, Vec U, Mat A, void *ctx)
{
  PetscInt           row[] = {0, 1}, col[] = {0};
  PetscScalar        J[2][1];
  const PetscScalar *u;

  PetscFunctionBeginUser;
  PetscCall(VecGetArrayRead(U, &u));
  J[0][0] = 0;
  J[1][0] = (1. - u[0] * u[0]) * u[1] - u[0];
  PetscCall(MatSetValues(A, 2, row, 1, col, &J[0][0], INSERT_VALUES));
  PetscCall(MatAssemblyBegin(A, MAT_FINAL_ASSEMBLY));
  PetscCall(MatAssemblyEnd(A, MAT_FINAL_ASSEMBLY));
  PetscCall(VecRestoreArrayRead(U, &u));
  PetscFunctionReturn(PETSC_SUCCESS);
}

/* 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(PETSC_SUCCESS);
}

int main(int argc, char **argv)
{
  TS             ts;
  PetscBool      monitor = PETSC_FALSE, implicitform = PETSC_TRUE;
  PetscScalar   *x_ptr, *y_ptr, derp;
  PetscMPIInt    size;
  struct _n_User user;

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     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;
  PetscCall(PetscOptionsGetBool(NULL, NULL, "-monitor", &monitor, NULL));
  PetscCall(PetscOptionsGetReal(NULL, NULL, "-mu", &user.mu, NULL));
  PetscCall(PetscOptionsGetBool(NULL, NULL, "-implicitform", &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(MatCreate(PETSC_COMM_WORLD, &user.Jacp));
  PetscCall(MatSetSizes(user.Jacp, PETSC_DECIDE, PETSC_DECIDE, 2, 1));
  PetscCall(MatSetFromOptions(user.Jacp));
  PetscCall(MatSetUp(user.Jacp));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Create timestepping solver context
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSCreate(PETSC_COMM_WORLD, &ts));
  PetscCall(TSSetEquationType(ts, TS_EQ_ODE_EXPLICIT)); /* less Jacobian evaluations when adjoint BEuler is used, otherwise no effect */
  if (implicitform) {
    PetscCall(TSSetIFunction(ts, NULL, IFunction, &user));
    PetscCall(TSSetIJacobian(ts, user.A, user.A, IJacobian, &user));
    PetscCall(TSSetType(ts, TSCN));
  } else {
    PetscCall(TSSetRHSFunction(ts, NULL, RHSFunction, &user));
    PetscCall(TSSetRHSJacobian(ts, user.A, user.A, RHSJacobian, &user));
    PetscCall(TSSetType(ts, TSRK));
  }
  PetscCall(TSSetRHSJacobianP(ts, user.Jacp, RHSJacobianP, &user));
  PetscCall(TSSetMaxTime(ts, user.ftime));
  PetscCall(TSSetTimeStep(ts, 0.001));
  PetscCall(TSSetExactFinalTime(ts, TS_EXACTFINALTIME_MATCHSTEP));
  if (monitor) PetscCall(TSMonitorSet(ts, Monitor, &user, NULL));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Set 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));
  PetscCall(TSSetTimeStep(ts, 0.001));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
    Save trajectory of solution so that TSAdjointSolve() may be used
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSSetSaveTrajectory(ts));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Set runtime options
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(TSSetFromOptions(ts));

  PetscCall(TSSolve(ts, user.U));
  PetscCall(TSGetSolveTime(ts, &user.ftime));
  PetscCall(TSGetStepNumber(ts, &user.steps));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Adjoint model starts here
     - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(MatCreateVecs(user.A, &user.lambda[0], NULL));
  /* Set initial conditions for the adjoint integration */
  PetscCall(VecGetArray(user.lambda[0], &y_ptr));
  y_ptr[0] = 1.0;
  y_ptr[1] = 0.0;
  PetscCall(VecRestoreArray(user.lambda[0], &y_ptr));
  PetscCall(MatCreateVecs(user.A, &user.lambda[1], NULL));
  PetscCall(VecGetArray(user.lambda[1], &y_ptr));
  y_ptr[0] = 0.0;
  y_ptr[1] = 1.0;
  PetscCall(VecRestoreArray(user.lambda[1], &y_ptr));

  PetscCall(MatCreateVecs(user.Jacp, &user.mup[0], NULL));
  PetscCall(VecGetArray(user.mup[0], &x_ptr));
  x_ptr[0] = 0.0;
  PetscCall(VecRestoreArray(user.mup[0], &x_ptr));
  PetscCall(MatCreateVecs(user.Jacp, &user.mup[1], NULL));
  PetscCall(VecGetArray(user.mup[1], &x_ptr));
  x_ptr[0] = 0.0;
  PetscCall(VecRestoreArray(user.mup[1], &x_ptr));

  PetscCall(TSSetCostGradients(ts, 2, user.lambda, user.mup));

  PetscCall(TSAdjointSolve(ts));

  PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt initial conditions: d[y(tf)]/d[y0]  d[y(tf)]/d[z0]\n"));
  PetscCall(VecView(user.lambda[0], PETSC_VIEWER_STDOUT_WORLD));
  PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt initial conditions: d[z(tf)]/d[y0]  d[z(tf)]/d[z0]\n"));
  PetscCall(VecView(user.lambda[1], PETSC_VIEWER_STDOUT_WORLD));

  PetscCall(VecGetArray(user.mup[0], &x_ptr));
  PetscCall(VecGetArray(user.lambda[0], &y_ptr));
  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];
  PetscCall(VecRestoreArray(user.mup[0], &x_ptr));
  PetscCall(VecRestoreArray(user.lambda[0], &y_ptr));
  PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensitivity wrt parameters: d[y(tf)]/d[mu]\n%g\n", (double)PetscRealPart(derp)));

  PetscCall(VecGetArray(user.mup[1], &x_ptr));
  PetscCall(VecGetArray(user.lambda[1], &y_ptr));
  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];
  PetscCall(VecRestoreArray(user.mup[1], &x_ptr));
  PetscCall(VecRestoreArray(user.lambda[1], &y_ptr));
  PetscCall(PetscPrintf(PETSC_COMM_WORLD, "\n sensivitity wrt parameters: d[z(tf)]/d[mu]\n%g\n", (double)PetscRealPart(derp)));

  /* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
     Free work space.  All PETSc objects should be destroyed when they
     are no longer needed.
   - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - */
  PetscCall(MatDestroy(&user.A));
  PetscCall(MatDestroy(&user.Jacp));
  PetscCall(VecDestroy(&user.U));
  PetscCall(VecDestroy(&user.lambda[0]));
  PetscCall(VecDestroy(&user.lambda[1]));
  PetscCall(VecDestroy(&user.mup[0]));
  PetscCall(VecDestroy(&user.mup[1]));
  PetscCall(TSDestroy(&ts));

  PetscCall(PetscFinalize());
  return 0;
}

/*TEST

    test:
      requires: revolve
      args: -monitor 0 -ts_type theta -ts_theta_endpoint -ts_theta_theta 0.5 -viewer_binary_skip_info -ts_dt 0.001 -mu 100000

    test:
      suffix: 2
      args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only

    test:
      suffix: 3
      args: -ts_type cn -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only 0
      output_file: output/ex20adj_2.out

    test:
      suffix: 4
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 5
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 6
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 7
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 8
      requires: revolve !cams
      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
      output_file: output/ex20adj_3.out

    test:
      suffix: 9
      requires: revolve !cams
      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
      output_file: output/ex20adj_4.out

    test:
      requires: revolve
      suffix: 10
      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
      output_file: output/ex20adj_2.out

    test:
      requires: revolve
      suffix: 11
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 12
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 13
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 14
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 15
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 16
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 17
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 18
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 19
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 20
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 21
      requires: revolve
      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
      output_file: output/ex20adj_2.out

    test:
      suffix: 22
      args: -ts_type beuler -ts_dt 0.001 -mu 100000 -ts_max_steps 15 -ts_trajectory_type memory -ts_trajectory_solution_only
      output_file: output/ex20adj_2.out

    test:
      suffix: 23
      requires: cams
      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
      output_file: output/ex20adj_5.out

    test:
      suffix: 24
      requires: cams
      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
      output_file: output/ex20adj_6.out

TEST*/