code: def moma(model, solution=None, linear=True):
      
      with model:
          add_moma(model=model, solution=solution, linear=linear)
          solution = model.optimize()
      return solution
docs: Compute a single solution based on (linear) MOMA.
  
      Compute a new flux distribution that is at a minimal distance to a
      previous reference solution. Minimization of metabolic adjustment (MOMA) is
      generally used to assess the impact
      of knock-outs. Thus the typical usage is to provide a wildtype flux
      distribution as reference and a model in knock-out state.
  
      Parameters
      ----------
      model : cobra.Model
          The model state to compute a MOMA-based solution for.
      solution : cobra.Solution, optional
          A (wildtype) reference solution.
      linear : bool, optional
          Whether to use the linear MOMA formulation or not (default True).
  
      Returns
      -------
      cobra.Solution
          A flux distribution that is at a minimal distance compared to the
          reference solution.
  
      See Also
      --------
      add_moma : add MOMA constraints and objective