How to use the cmdstanpy.utils.check_sampler_csv function in cmdstanpy

ValueError, 'config error, expected thin = 2'
        ):
            check_sampler_csv(
                path=csv_good, iter_warmup=100, iter_sampling=20, thin=2
            )
        with self.assertRaisesRegex(
            ValueError, 'config error, expected save_warmup'
        ):
            check_sampler_csv(
                path=csv_good,
                iter_warmup=100,
                iter_sampling=10,
                save_warmup=True,
            )
        with self.assertRaisesRegex(ValueError, 'expected 1000 draws'):
            check_sampler_csv(path=csv_good, iter_warmup=100)

self.assertEqual(dict['thin'], 7)
        self.assertEqual(dict['draws_sampling'], 70)
        self.assertEqual(dict['seed'], 12345)
        self.assertEqual(dict['max_depth'], 11)
        self.assertEqual(dict['delta'], 0.98)

        with self.assertRaisesRegex(ValueError, 'config error'):
            check_sampler_csv(
                path=csv_file,
                is_fixed_param=False,
                iter_sampling=490,
                iter_warmup=490,
                thin=9,
            )
        with self.assertRaisesRegex(ValueError, 'expected 490 draws, found 70'):
            check_sampler_csv(
                path=csv_file,
                is_fixed_param=False,
                iter_sampling=490,
                iter_warmup=490,
            )

def test_check_sampler_csv_2(self):
        csv_bad = os.path.join(DATAFILES_PATH, 'no_such_file.csv')
        with self.assertRaises(Exception):
            check_sampler_csv(csv_bad)

def test_check_sampler_csv_metric_1(self):
        csv_bad = os.path.join(DATAFILES_PATH, 'output_bad_metric_1.csv')
        with self.assertRaisesRegex(Exception, 'expecting metric'):
            check_sampler_csv(csv_bad)

def test_check_sampler_csv_3(self):
        csv_bad = os.path.join(DATAFILES_PATH, 'output_bad_cols.csv')
        with self.assertRaisesRegex(Exception, '8 items'):
            check_sampler_csv(csv_bad)

def test_check_sampler_csv_metric_3(self):
        csv_bad = os.path.join(DATAFILES_PATH, 'output_bad_metric_3.csv')
        with self.assertRaisesRegex(
            Exception, 'invalid or missing mass matrix specification'
        ):
            check_sampler_csv(csv_bad)

Populates attributes for draws, column_names, num_params, metric_type.
        Raises exception when inconsistencies detected.
        """
        dzero = {}
        for i in range(self.runset.chains):
            if i == 0:
                dzero = check_sampler_csv(
                    path=self.runset.csv_files[i],
                    is_fixed_param=self._is_fixed_param,
                    iter_sampling=self._iter_sampling,
                    iter_warmup=self._iter_warmup,
                    save_warmup=self._save_warmup,
                    thin=self._thin,
                )
            else:
                drest = check_sampler_csv(
                    path=self.runset.csv_files[i],
                    is_fixed_param=self._is_fixed_param,
                    iter_sampling=self._iter_sampling,
                    iter_warmup=self._iter_warmup,
                    save_warmup=self._save_warmup,
                    thin=self._thin,
                )
                for key in dzero:
                    if (
                        key not in ['id', 'diagnostic_file']
                        and dzero[key] != drest[key]
                    ):
                        raise ValueError(
                            'csv file header mismatch, '
                            'file {}, key {} is {}, expected {}'.format(
                                self.runset.csv_files[i],

def _validate_csv_files(self) -> None:
        """
        Checks that csv output files for all chains are consistent.
        Populates attributes for draws, column_names, num_params, metric_type.
        Raises exception when inconsistencies detected.
        """
        dzero = {}
        for i in range(self.runset.chains):
            if i == 0:
                dzero = check_sampler_csv(
                    path=self.runset.csv_files[i],
                    is_fixed_param=self._is_fixed_param,
                    iter_sampling=self._iter_sampling,
                    iter_warmup=self._iter_warmup,
                    save_warmup=self._save_warmup,
                    thin=self._thin,
                )
            else:
                drest = check_sampler_csv(
                    path=self.runset.csv_files[i],
                    is_fixed_param=self._is_fixed_param,
                    iter_sampling=self._iter_sampling,
                    iter_warmup=self._iter_warmup,
                    save_warmup=self._save_warmup,
                    thin=self._thin,
                )