code: def find_bounds(model):
      
      lower_bounds = np.asarray([rxn.lower_bound for rxn in model.reactions],
                                dtype=float)
      upper_bounds = np.asarray([rxn.upper_bound for rxn in model.reactions],
                                dtype=float)
      lower_bound = np.nanmedian(lower_bounds[lower_bounds != 0.0])
      upper_bound = np.nanmedian(upper_bounds[upper_bounds != 0.0])
      if np.isnan(lower_bound):
          LOGGER.warning("Could not identify a median lower bound.")
          lower_bound = -1000.0
      if np.isnan(upper_bound):
          LOGGER.warning("Could not identify a median upper bound.")
          upper_bound = 1000.0
      return lower_bound, upper_bound
docs: Return the median upper and lower bound of the metabolic model.
  
      Bounds can vary from model to model. Cobrapy defaults to (-1000, 1000) but
      this may not be the case for merged or autogenerated models. In these
      cases, this function is used to iterate over all the bounds of all the
      reactions and find the median bound values in the model, which are
      then used as the 'most common' bounds.
  
      Parameters
      ----------
      model : cobra.Model
          The metabolic model under investigation.