old_contents: import numpy as np
  from msmbuilder.msm import MarkovStateModel, BayesianMarkovStateModel
  from matplotlib.axes import SubplotBase
  from seaborn.apionly import JointGrid
  
  from ..plots import plot_pop_resids, plot_msm_network, plot_timescales, plot_implied_timescales
  
  rs = np.random.RandomState(42)
  data = rs.randint(low=0, high=10, size=100000)
  msm = MarkovStateModel()
  msm.fit(data)
  bmsm = BayesianMarkovStateModel()
  bmsm.fit(data)
  
  
  def test_plot_pop_resids():
      ax = plot_pop_resids(msm)
  
      assert isinstance(ax, JointGrid)
  
  
  def test_plot_msm_network():
      ax = plot_msm_network(msm)
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_timescales_msm():
      ax = plot_timescales(msm, n_timescales=3, xlabel='x', ylabel='y')
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_timescales_bmsm():
      ax = plot_timescales(bmsm)
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_implied_timescales():
      lag_times = [1, 10, 50, 100, 200, 250, 500]
      msm_objs = []
      for lag in lag_times:
          # Construct MSM
          msm = MarkovStateModel(lag_time=lag, n_timescales=5)
          msm.fit(clustered_trajs)
          msm_objs.append(msm)
      ax = plot_implied_timescales(msm_objs)
      assert isinstance(ax, SubplotBase)
  
new_contents: import numpy as np
  from msmbuilder.msm import MarkovStateModel, BayesianMarkovStateModel
  from matplotlib.axes import SubplotBase
  from seaborn.apionly import JointGrid
  
  from ..plots import plot_pop_resids, plot_msm_network, plot_timescales, plot_implied_timescales
  
  rs = np.random.RandomState(42)
  data = rs.randint(low=0, high=10, size=100000)
  msm = MarkovStateModel()
  msm.fit(data)
  bmsm = BayesianMarkovStateModel()
  bmsm.fit(data)
  
  
  def test_plot_pop_resids():
      ax = plot_pop_resids(msm)
  
      assert isinstance(ax, JointGrid)
  
  
  def test_plot_msm_network():
      ax = plot_msm_network(msm)
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_timescales_msm():
      ax = plot_timescales(msm, n_timescales=3, xlabel='x', ylabel='y')
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_timescales_bmsm():
      ax = plot_timescales(bmsm)
  
      assert isinstance(ax, SubplotBase)
  
  
  def test_plot_implied_timescales():
      lag_times = [1, 10, 50, 100, 200, 250, 500]
      msm_objs = []
      for lag in lag_times:
          # Construct MSM
          msm = MarkovStateModel(lag_time=lag, n_timescales=5)
          msm.fit(data)
          msm_objs.append(msm)
      ax = plot_implied_timescales(msm_objs)
      assert isinstance(ax, SubplotBase)
  
subject: Fix test