code: def _convert_types(self):
          
          self.fars = np.array(self.fars)
          self.parking_rates = np.array([self.parking_rates[use] for use in self.uses])
          self.res_ratios = {}
          assert len(self.uses) == len(self.residential_uses)
          for k, v in self.forms.items():
              self.forms[k] = np.array([self.forms[k].get(use, 0.0) for use in self.uses])
              # normalize if not already
              self.forms[k] /= self.forms[k].sum()
              self.res_ratios[k] = pd.Series(self.forms[k])[self.residential_uses].sum()
          self.costs = np.transpose(np.array([self.costs[use] for use in self.uses]))
docs: convert lists and dictionaries that are useful for users to
          np vectors that are usable by machines