old_contents: import numpy as np
  import pandas as pd
  import pytest
  
  @pytest.fixture(params=['no_na', 'with_na'])
  def event(self, request):
      x = np.arange(0, 1.1, .1)
      if request.param == 'no_na':
          return x
      elif request.param == 'with_na':
          x[x < 0.5] = np.nan
          return x
  
  @pytest.fixture
  def positive_control(self):
      """Exact, known positive controls for modality estimation"""
      size = 20
      psi0 = pd.Series(np.zeros(size), name='excluded')
      psi1 = pd.Series(np.ones(size), name='included')
      middle = pd.Series( 0.5 *np.ones(size), name='middle')
      bimodal = pd.Series(np.concatenate([np.ones( size /2),
                                          np.zeros( size /2)]),
                          name='bimodal')
      uncategorized = pd.Series(np.linspace(0, 1, size),
                                name='uncategorized')
      df = pd.concat([psi0, psi1, middle, bimodal, uncategorized], axis=1)
      return df
  
new_contents: import numpy as np
  import pandas as pd
  import pytest
  
  
  @pytest.fixture(params=['no_na', 'with_na'])
  def event(self, request):
      x = np.arange(0, 1.1, .1)
      if request.param == 'no_na':
          return x
      elif request.param == 'with_na':
          x[x < 0.5] = np.nan
          return x
  
  
  @pytest.fixture
  def positive_control(self):
      """Exact, known positive controls for modality estimation"""
      size = 20
      psi0 = pd.Series(np.zeros(size), name='excluded')
      psi1 = pd.Series(np.ones(size), name='included')
      middle = pd.Series(0.5 * np.ones(size), name='middle')
      bimodal = pd.Series(np.concatenate([np.ones(size / 2),
                                          np.zeros(size / 2)]),
                          name='bimodal')
      uncategorized = pd.Series(np.linspace(0, 1, size),
                                name='uncategorized')
      df = pd.concat([psi0, psi1, middle, bimodal, uncategorized], axis=1)
      return df
  
subject: Fix lint