code: def test_with_intercept(order, seasonal):
      n_params = None
      for intercept in (False, True):
          modl = ARIMA(
              order=order,
              seasonal_order=seasonal,
              with_intercept=intercept,
          ).fit(lynx)
  
          if not intercept:  # first time
              n_params = modl.params().shape[0]
          else:
              # With an intercept, should be 1 more
              assert modl.params().shape[0] == n_params + 1
  
imports: import numpy
  import pandas
  from pmdarima.arima import ARIMA, auto_arima, AutoARIMA, ARMAtoMA
  from pmdarima.arima import _validation
  from pmdarima.compat.pytest import pytest_error_str
  from pmdarima.datasets import load_lynx, load_wineind, load_heartrate
  from numpy.random import RandomState
  from numpy.testing import assert_array_almost_equal, assert_almost_equal, assert_allclose
  from statsmodels import api
  from sklearn.metrics import mean_squared_error
  import datetime
  import joblib
  import os
  import pickle
  import pytest
  import tempfile
  import time
label_desc: Use image node_id 18 for calling a global function with example usage: test_with_intercept(order, seasonal) without return types