code: def test_univariate_plots_output_type(series_to_plot, plot_func):
      """Tests whether plots accepting univariate series have correct output types."""
      _check_soft_dependencies("matplotlib")
      import matplotlib
      import matplotlib.pyplot as plt
  
      matplotlib.use("agg")
      fig, ax = plot_func(series_to_plot)
  
      is_fig_figure = isinstance(fig, plt.Figure)
      is_ax_array = isinstance(ax, np.ndarray)
      is_ax_array_axis = all([isinstance(ax_, plt.Axes) for ax_ in ax])
  
      assert (
          is_fig_figure and is_ax_array and is_ax_array_axis
      ), "".join(
          [
              f"{plot_func.__name__} should return plt.Figure and array of plt.Axes,",
              f"but returned: {type(fig)} and {type(ax)}",
          ]
      )
  
imports: import re
  import numpy
  import pandas
  import pytest
  from sktime.datasets import load_airline
  from sktime.tests.test_switch import run_test_for_class
  from sktime.utils.plotting import plot_correlations, plot_lags, plot_series
  from sktime.utils.validation._dependencies import _check_soft_dependencies
  from sktime.utils.validation.series import VALID_DATA_TYPES
label_desc: Use image node_id 13 for calling a global function with example usage: test_univariate_plots_output_type(series_to_plot, plot_func) without return types