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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _convert_types(self):
 """ convert lists and dictionaries that are useful for users to np vectors that are usable by machines """

        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]))