Method forward_run

python/adjoint/optimization_problem.py:262–294

(self)

        )

    def forward_run(self):
        # set up monitors
        self.prepare_forward_run()

        # Forward run
        if any(isinstance(m, LDOS) for m in self.objective_arguments):
            self.sim.run(
                mp.dft_ldos(self.frequencies),
                *self.step_funcs,
                until_after_sources=mp.stop_when_dft_decayed(
                    self.decay_by, self.minimum_run_time, self.maximum_run_time
                ),
            )
        else:
            self.sim.run(
                *self.step_funcs,
                until_after_sources=mp.stop_when_dft_decayed(
                    self.decay_by, self.minimum_run_time, self.maximum_run_time
                ),
            )

        # record objective quantities from user specified monitors
        self.results_list = [m() for m in self.objective_arguments]
        # evaluate objectives
        self.f0 = [fi(*self.results_list) for fi in self.objective_functions]
        if len(self.f0) == 1:
            self.f0 = self.f0[0]

        # store objective function evaluation in memory
        self.f_bank.append(self.f0)

        # update solver's current state
        self.current_state = "FWD"

    def prepare_adjoint_run(self):
        # Compute adjoint sources