old_contents: import numpy as np
  from numpy.testing import dec
  
  import statsmodels.api as sm
  from statsmodels.graphics.tsaplots import plot_acf
  import statsmodels.tsa.arima_process as tsp
  
  
  try:
      import matplotlib.pyplot as plt
      have_matplotlib = True
  except:
      have_matplotlib = False
  
  
  @dec.skipif(not have_matplotlib)
  def test_plot_acf():
      # Just test that it runs.
      fig = plt.figure()
      ax = fig.add_subplot(111)
  
      ar = np.r_[1., -0.9]
      ma = np.r_[1.,  0.9]
      armaprocess = tsp.ArmaProcess(ar, ma)
      acf = armaprocess.acf(20)[:20]
      plot_acf(acf, ax=ax)
  
      plt.close(fig)
  
  
new_contents: import numpy as np
  import pandas as pd
  from numpy.testing import dec
  
  import statsmodels.api as sm
  from statsmodels.graphics.tsaplots import plot_acf, month_plot, quarter_plot
  import statsmodels.tsa.arima_process as tsp
  
  
  try:
      import matplotlib.pyplot as plt
      have_matplotlib = True
  except:
      have_matplotlib = False
  
  
  @dec.skipif(not have_matplotlib)
  def test_plot_acf():
      # Just test that it runs.
      fig = plt.figure()
      ax = fig.add_subplot(111)
  
      ar = np.r_[1., -0.9]
      ma = np.r_[1.,  0.9]
      armaprocess = tsp.ArmaProcess(ar, ma)
      acf = armaprocess.acf(20)[:20]
      plot_acf(acf, ax=ax)
  
      plt.close(fig)
  
  
  @dec.skipif(not have_matplotlib)
  def test_plot_month():
      dta = sm.datasets.elnino.load_pandas().data
      dta['YEAR'] = dta.YEAR.astype(int).astype(str)
      dta = dta.set_index('YEAR').T.unstack()
      dates = map(lambda x : pd.datetools.parse('1 '+' '.join(x)),
                                              dta.index.values)
  
      # test dates argument
      fig = month_plot(dta.values, dates=dates, ylabel='el nino')
      plt.close(fig)
  
      # test with a TimeSeries DatetimeIndex with no freq
      dta.index = pd.DatetimeIndex(dates)
      fig = month_plot(dta)
      plt.close(fig)
  
      # w freq
      dta.index = pd.DatetimeIndex(dates, freq='M')
      fig = month_plot(dta)
      plt.close(fig)
  
      # test with a TimeSeries PeriodIndex
      dta.index = pd.PeriodIndex(dates, freq='M')
      fig = month_plot(dta)
      plt.close(fig)
  
  @dec.skipif(not have_matplotlib)
  def test_plot_quarter():
      dta = sm.datasets.macrodata.load_pandas().data
      dates = map('Q'.join, zip(dta.year.astype(int).astype(str),
                                dta.quarter.astype(int).astype(str)))
  
      # test dates argument
      quarter_plot(dta.unemp.values, dates)
  
      # test with a DatetimeIndex with no freq
      parser = pd.datetools.parse_time_string
      dta.set_index(pd.DatetimeIndex(x[0] for x in map(parser, dates)),
                    inplace=True)
      quarter_plot(dta.unemp)
  
      # w freq
      dta.set_index(pd.DatetimeIndex((x[0] for x in map(parser, dates)),
                                     freq='QS-Oct'),
                    inplace=True)
      quarter_plot(dta.unemp)
  
      # w PeriodIndex
      dta.set_index(pd.PeriodIndex((x[0] for x in map(parser, dates)),
                                     freq='Q'),
                    inplace=True)
      quarter_plot(dta.unemp)
  
subject: Add test for seasonality plots.