code: def test_mean_diff_plot(close_figures):
      # Seed the random number generator.
      # This ensures that the results below are reproducible.
      np.random.seed(11111)
      m1 = np.random.random(20)
      m2 = np.random.random(20)
  
      fig = plt.figure()
      ax = fig.add_subplot(111)
  
      # basic test.
      mean_diff_plot(m1, m2, ax=ax)
  
      # Test with pandas Series.
      p1 = pd.Series(m1)
      p2 = pd.Series(m2)
      mean_diff_plot(p1, p2)
  
      # Test plotting on assigned axis.
      fig, ax = plt.subplots(2)
      mean_diff_plot(m1, m2, ax=ax[0])
  
      # Test the setting of confidence intervals.
      mean_diff_plot(m1, m2, sd_limit=0)
  
      # Test asethetic controls.
      mean_diff_plot(m1, m2, scatter_kwds={"color": "green", "s": 10})
  
      mean_diff_plot(m1, m2, mean_line_kwds={"color": "green", "lw": 5})
  
      mean_diff_plot(
          m1,
          m2,
          limit_lines_kwds={"color": "green", "lw": 5, "ls": "dotted"},
      )
  
imports: import numpy
  import pandas
  import pytest
  from statsmodels.graphics.agreement import mean_diff_plot
label_desc: Use image node_id 1 for calling a global function with example usage: test_mean_diff_plot(close_figures) without return types