old_contents: import unittest
  import os
  import tempfile
  
  import numpy as np
  from numpy import ma
  from numpy.testing import assert_array_equal
  from netCDF4 import Dataset
  
  # Test use of vector of missing values.
  
  class VectorMissingValues(unittest.TestCase):
  
      def setUp(self):
  
          self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
  
          self.missing_values = [-999,999,0]
          self.v    = np.array([-999,0,1,2,3,999], dtype = "i2")
          self.v_ma = ma.array([-1,0,1,2,3,4], dtype = "i2", \
                      mask = [True, True, False, False, False, True])
  
          f = Dataset(self.testfile, 'w')
          d = f.createDimension('x',6)
          v = f.createVariable('v', "i2", 'x')
  
          v.missing_value = self.missing_values
          v[:] = self.v
  
          f.close()
  
  
      def tearDown(self):
  
          os.remove(self.testfile)
  
  
      def test_scaled(self):
  
          """Testing auto-conversion of masked arrays"""
  
          f = Dataset(self.testfile)
          v = f.variables["v"]
          self.assertTrue(isinstance(v[:], ma.core.MaskedArray))
          assert_array_equal(v[:], self.v_ma)
          assert_array_equal(v[2],self.v[2]) # issue #624.
          v.set_auto_mask(False)
          self.assertTrue(isinstance(v[:], np.ndarray))
          assert_array_equal(v[:], self.v)
  
          f.close()
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: import unittest
  import os
  import tempfile
  
  import numpy as np
  from numpy import ma
  from numpy.testing import assert_array_equal
  from netCDF4 import Dataset
  
  # Test use of vector of missing values.
  
  class VectorMissingValues(unittest.TestCase):
  
      def setUp(self):
  
          self.testfile = tempfile.NamedTemporaryFile(suffix='.nc', delete=False).name
  
          self.missing_values = [-999,999,0]
          self.v    = np.array([-999,0,1,2,3,999], dtype = "i2")
          self.v_ma = ma.array([-1,0,1,2,3,4], dtype = "i2", \
                      mask = [True, True, False, False, False, True])
  
          f = Dataset(self.testfile, 'w')
          d = f.createDimension('x',6)
          v = f.createVariable('v', "i2", 'x')
          # issue 730: set fill_value for vlen str vars
          v2 = f.createVariable('v2',str,'x',fill_value='<missing>')
  
          v.missing_value = self.missing_values
          v[:] = self.v
          v2[0]='first'
  
          f.close()
  
  
      def tearDown(self):
  
          os.remove(self.testfile)
  
  
      def test_scaled(self):
  
          """Testing auto-conversion of masked arrays"""
  
          f = Dataset(self.testfile)
          v = f.variables["v"]
          v2 = f.variables["v2"]
          self.assertTrue(isinstance(v[:], ma.core.MaskedArray))
          assert_array_equal(v[:], self.v_ma)
          assert_array_equal(v[2],self.v[2]) # issue #624.
          v.set_auto_mask(False)
          self.assertTrue(isinstance(v[:], np.ndarray))
          assert_array_equal(v[:], self.v)
  
          # issue 730
          assert (v2[0]=='first')
          assert (v2[1]=='<missing>')
  
  
          f.close()
  
  
  if __name__ == '__main__':
      unittest.main()
  
subject: include test for issue 730