code: def test_the_r_src():
      # this is the test the R code provides
      fit = ARIMA(
          order=(2, 0, 1), trend="c", suppress_warnings=True
      ).fit(abc)
  
      # the R code's AIC = 135.4
      assert abs(135.4 - fit.aic()) < 1.0
  
      # the R code's AICc = ~ 137
      assert abs(137 - fit.aicc()) < 1.0
  
      # the R code's BIC = ~145
      assert abs(145 - fit.bic()) < 1.0
  
      # R's coefficients:
      #     ar1      ar2     ma1    mean
      # -0.6515  -0.2449  0.8012  5.0370
  
      arparams = fit.arparams()
      assert_almost_equal(arparams, [-0.6515, -0.2449], decimal=3)
  
      maparams = fit.maparams()
      assert_almost_equal(maparams, [0.8012], decimal=3)
  
      # > fit = forecast::auto.arima(abc, max.p=5, max.d=5,
      #             max.q=5, max.order=100, stepwise=F)
      fit = auto_arima(
          abc,
          max_p=5,
          max_d=5,
          max_q=5,
          max_order=100,
          seasonal=False,
          trend="c",
          suppress_warnings=True,
          error_action="ignore",
      )
  
      assert abs(135.28 - fit.aic()) < 1.0
  
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 14 for calling a global function with example usage: test_the_r_src() without return types