def Jhat(ic):
time = Constant(0.0)
form = model.rhs(ic, time, params)*dP
(u, xs, ys) = main(ic, form, time, Scheme, dt=dt)
return assemble(Jform(u))
def Jhat(ic):
time = Constant(0.0)
form = model.rhs(ic, time, params) * dP
(u, xs, ys) = main(ic, form, time, Scheme, dt=dt)
return assemble(Jform(u))
for i in range(5):
solver.step(dt)
xs.append(float(time))
ys.append(u.vector().array()[15])
return (u, xs, ys)
if __name__ == "__main__":
u0 = interpolate(state_init, V, name="InitialValue")
Scheme = BackwardEuler
u = Function(V, name="Solution")
v = TestFunction(V)
time = Constant(0.0)
form = model.rhs(u, time, params)*dP
## Step 0. Check forward order-of-convergence (nothing to do with adjoints)
check = False
plot = False
dt = 0.5
u.assign(u0)
fwd_timer = Timer("Forward run")
(u, xs, ys) = main(u, form, time, Scheme, dt=dt)
fwd_time = fwd_timer.stop()
info_red("Forward time: %s" % fwd_time)
replay = False
if replay:
for i in range(4):
solver.step(dt)
xs.append(float(time))
ys.append(u.vector().array()[15])
return (u, xs, ys)
if __name__ == "__main__":
u0 = interpolate(state_init, V, name="InitialValue")
Scheme = BackwardEuler
u = Function(V, name="Solution")
v = TestFunction(V)
time = Constant(0.0)
form = model.rhs(u, time, params) * dP
## Step 0. Check forward order-of-convergence (nothing to do with adjoints)
check = False
plot = False
dt = 0.01
u.assign(u0)
fwd_timer = Timer("Forward run")
(u, xs, ys) = main(u, form, time, Scheme, dt=dt)
fwd_time = fwd_timer.stop()
info_red("Forward time: %s" % fwd_time)
replay = True
if replay:
replay_timer = Timer("Replay")
