logging bug: decision variable scaling and cyclic constraints

[yunlongxu-numagic]

as such, the evaluated function outputs are also done with the wrong inputs (scaled inputs)

see here

[yunlongxu-numagic]

it's a little complicated, see here

• recording decision variable: we want unscaled
• call batch_forward: we want unscaled
• call constraints: we want scaled

[yunlongxu-numagic]

an additional issue: when the larger infeasibility is cyclic cons, the debugger gives wrong name and location of the maximum infeasibility (it gives the constraint that has the larger violation among the group excluding cyclic cons)

this is because cyclic cons are not recorded, to record, we can add the following snippet to the logging here:

        # HACK: try to include cyclic cons in logging
        # Cyclic-con is NOT defined at every point on the mesh, but to log, we need to
        # make it also num_stages x num_columns. So make only the last stages non-zero
        cyclic_cons = np.zeros((self.num_stages, len(self._cyclic_vars)))
        cyclic_cons[-1, :] = cons["cyclic"]
        cyclic_con_columns = ["cyclic_con." + n for n in self._cyclic_vars]
        cylic_cons_df = pd.DataFrame(data=cyclic_cons, columns=cyclic_con_columns)

        dec_var_df = pd.DataFrame(
            data=self.dec_var_operator.get_stage_var_array(unscaled_dec_var),
            columns=self.dec_var_operator.stage_var_names,
        )

        outputs_df = pd.DataFrame(
            model_return.outputs,
            columns=["outputs." + n for n in self.model.get_group_names("outputs")],
        )

        df_list = [
            dec_var_df,
            outputs_df,
            interval_cons_df,
            stage_cons_df,
            cylic_cons_df,
        ]

[yunlongxu-numagic]

closed by #79