code: def test_enforce_exogenous_no_exo_data(load_pos_and_neg_data):
      """Tests the enforcement of exogenous variable support in models when
      univariate data without exogenous variables is passed."""
      data = load_pos_and_neg_data
  
      exp1 = TSForecastingExperiment()
      exp1.setup(data=data, enforce_exogenous=True)
      num_models1 = len(exp1.models())
  
      exp2 = TSForecastingExperiment()
      exp2.setup(data=data, enforce_exogenous=False)
      num_models2 = len(exp2.models())
  
      # Irrespective of the enforce_exogenous flag, all models are enabled when
      # the data does not contain exogenous variables.
      assert num_models1 == num_models2
  
imports: import math
  import numpy
  import pandas
  import pytest
  from time_series_test_utils import _get_seasonal_values, _get_seasonal_values_alphanumeric, _return_data_seasonal_types_strictly_pos, _return_setup_args_raises, _return_splitter_args
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 5 for calling a global function with example usage: test_enforce_exogenous_no_exo_data(load_pos_and_neg_data) without return types