How to repeatedly compute gradient at different points?

Hi there,

Can I repeatedly compute the gradient at different points? So far, I tried with the Burgers' equation code, by wrapping everything in a function jac(x), adding adj_inc_timestep and slightly changing the target functional, but got this error message:

Traceback (most recent call last):
  File "/home/Projects/adjointwrapper.py", line 42, in <module>
    print jac(x)
  File "/home/Projects/adjointwrapper.py", line 28, in jac
    adj_start_timestep()
  File "/usr/lib/python2.7/dist-packages/dolfin_adjoint/adjglobals.py", line 25, in adj_start_timestep
    adjointer.time.start(time)
  File "/usr/lib/python2.7/dist-packages/libadjoint/libadjoint.py", line 830, in start
    "time.start() called after simulation started!")
libadjoint.exceptions.LibadjointErrorInvalidInputs: time.start() called after simulation started!
[Finished in 5.0s with exit code -6]

Could you please advice what might be wrong? The full code is attached.

from dolfin import *
from dolfin_adjoint import *
# set_log_level(WARNING) #ERROR #INFO

def jac(x):

    nu = Constant(x)

    n = 30
    mesh = UnitSquareMesh(n, n)
    V = VectorFunctionSpace(mesh, "CG", 2)

    ic = project(Expression(("sin(2*pi*x[0])", "cos(2*pi*x[1])"), degree=2),  V)
    u = ic.copy(deepcopy=True)
    u_next = Function(V)
    v = TestFunction(V)

    timestep = Constant(0.01)

    F = (inner((u_next - u)/timestep, v)
       + inner(grad(u_next)*u_next, v)
       + nu*inner(grad(u_next), grad(v)))*dx

    bc = DirichletBC(V, (0.0, 0.0), "on_boundary")

    t = 0.0
    end = 0.05
    adj_start_timestep()
    while (t < end):
        solve(F == 0, u_next, bc, annotate=True)
        u.assign(u_next)
        t += float(timestep)
        adj_inc_timestep(t, t > end - .5*float(timestep))

    J = Functional(inner(u, u)*dx*dt) # integral over time
    dJdnu = compute_gradient(J, Control(nu), forget=False)
    return float(dJdnu)

x = 0.0001
print jac(x)
x = 0.0002
print jac(x)

Thanks!

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