old_contents: """
  Test Pearson module, pearson_1d function
  
  Run with::
  
      nosetests test_pearson_1d.py
  
  This is a test module.
  
  It is designed to be run the with the "nose" testing package (via the
  "nosetests" script.
  
  Nose will look for any functions with "test" in their names, and run them.
  Nose reports any errors, or any failures.
  
  A failure is where one of the test conditions run with an "assert" command
  fails.  For example, if I did:
  
      assert_almost_equal(1, 2)
  
  then this would "fail".
  
  So we use the tests to check that the results of our function are (still) as we
  expect.
  """
  # Python 3 compatibility
  from __future__ import absolute_import, division, print_function
  
  import numpy as np
  
  from .. import pearson
  
  from numpy.testing import assert_almost_equal
  
  
  def test_pearson_1d():
      # Test pearson_1d routine
      x = np.random.rand(22)
      y = np.random.rand(22)
      # Does routine give same answer as np.corrcoef?
      expected = np.corrcoef(x, y)[0, 1]
      actual = pearson.pearson_1d(x, y)
      # Did you, gentle user, forget to return the value?
      if actual is None:
          raise RuntimeError("function returned None")
      assert_almost_equal(expected, actual)
  
new_contents: """
  Test Pearson module, pearson_1d function
  
  Run with::
  
      nosetests test_pearson_1d.py
  
  This is a test module.
  
  It is designed to be run the with the "nose" testing package (via the
  "nosetests" script.
  
  Nose will look for any functions with "test" in their names, and run them.
  Nose reports any errors, or any failures.
  
  A failure is where one of the test conditions run with an "assert" command
  fails.  For example, if I did:
  
      assert_almost_equal(1, 2)
  
  then this would "fail".
  
  So we use the tests to check that the results of our function are (still) as we
  expect.
  """
  # Python 3 compatibility
  from __future__ import absolute_import, division, print_function
  
  import numpy as np
  
  import sys
  
  sys.path.append("code/utils")
  import pearson
  
  from numpy.testing import assert_almost_equal
  
  
  def test_pearson_1d():
      # Test pearson_1d routine
      x = np.random.rand(22)
      y = np.random.rand(22)
      # Does routine give same answer as np.corrcoef?
      expected = np.corrcoef(x, y)[0, 1]
      actual = pearson.pearson_1d(x, y)
      # Did you, gentle user, forget to return the value?
      if actual is None:
          raise RuntimeError("function returned None")
      assert_almost_equal(expected, actual)
  
subject: improve coverage