def report_fit(self):
        if not self.fitted:
            print('Model not yet fit.')
            return

        print('Null Log-liklihood: {0:.3f}'.format(
            self.log_likelihoods['null']))
        print('Log-liklihood at convergence: {0:.3f}'.format(
            self.log_likelihoods['convergence']))
        print('Log-liklihood Ratio: {0:.3f}\n'.format(
            self.log_likelihoods['ratio']))

        tbl = PrettyTable(
            ['Component', ])
        tbl = PrettyTable()

        tbl.add_column('Component', self.fit_parameters.index.values)
        for col in ('Coefficient', 'Std. Error', 'T-Score'):
            tbl.add_column(col, self.fit_parameters[col].values)

        tbl.align['Component'] = 'l'
        tbl.float_format = '.3'

        print(tbl)
Print a report of the fit results.
dataset/ETHPy150Open UDST/urbansim/urbansim/models/dcm.py/MNLDiscreteChoiceModel.report_fit