docs: def moma2(self, objective, wt_obj):
          """Find the smallest redistribution vector using Euclidean distance.
  
          Minimizing the redistribution of fluxes using a quadratic objective
          function. The distance is minimized by minimizing the sum of
          (wild type - knockout)^2.
  
          Creates the constraint that the we select the optimal flux vector that
          is closest to the wildtype. This might still return an arbitrary flux
          vector the maximizes the objective function.
  
          Args:
              objective: Objective reaction for the model.
              wt_obj: The flux value for your wild type objective reactions.
                  Can either use an expiremental value or on determined by FBA
                  by using :meth:`.get_fba_obj_flux(objective)`.
          """
          obj_expr = 0
          for reaction in self._adjustment_reactions():
              v_wt = self._v_wt[reaction]
              v = self._v[reaction]
              obj_expr += (v_wt - v)**2
  
          self._prob.set_objective(obj_expr)
  
          with self.constraints(self._v_wt[objective] >= wt_obj):
              self._solve(lp.ObjectiveSense.Minimize)