code: def test_issue_30():
      # From the issue:
      vec = np.array([33.0, 44.0, 58.0, 49.0, 46.0, 98.0, 97.0])
  
      arm = AutoARIMA(
          out_of_sample_size=1, seasonal=False, suppress_warnings=True
      )
      arm.fit(vec)
  
      # This is a way to force it:
      ARIMA(order=(0, 1, 0), out_of_sample_size=1).fit(vec)
  
      # Want to make sure it works with X arrays as well
      X = np.random.RandomState(1).rand(vec.shape[0], 2)
      auto_arima(
          vec,
          X=X,
          out_of_sample_size=1,
          seasonal=False,
          suppress_warnings=True,
      )
  
      # This is a way to force it:
      ARIMA(order=(0, 1, 0), out_of_sample_size=1).fit(vec, X=X)
  
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 3 for calling a global function with example usage: test_issue_30() without return types