class TestDataValues(TemplateTestCase):
def setUp(self):
super(TestDataValues, self).setUp()
self.data_array = np.array([-999., -999., -999., -999., -999., 1., 2., 3., 4., 5])
self.data_masked = np.ma.masked_array([-4, -3, -2, -1, 0, 1., 2., 3., 4., 5],
mask=[True, True, True, True, True, False, False, False, False, False])
self.template = DatasetTemplate(
dimensions={'TIME': 10},
variables={
'TIME': {
'_dimensions': ['TIME'],
'_datatype': 'float32',
'_data': np.array([np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8])
},
'X': {
'_dimensions': ['TIME'],
'_datatype': 'float32',
'_FillValue': -999.,
'_data': self.data_array
},
'Y': {
'_dimensions': ['TIME'],
'_datatype': 'float32',
'_fill_value': -999.,
'_data': self.data_masked
}
}
)
def test_fill_values(self):
self.template.to_netcdf(self.temp_nc_file)
dataset = Dataset(self.temp_nc_file)
dataset.set_auto_mask(True)
for varname in ('X', 'Y'):
dsvar = dataset.variables[varname]
self.assertEqual(-999., dsvar._FillValue)
self.assertIsInstance(dsvar[:], np.ma.MaskedArray)
self.assertTrue(dsvar[:5].mask.all())
self.assertTrue((dsvar[5:] == self.data_array[5:]).all())
def test_fill_value_aliases(self):
self.template.variables['X']['_fill_value'] = -999. # both aliases, but equal so should still work
self.template.to_netcdf(self.temp_nc_file)
dataset = Dataset(self.temp_nc_file)
self.assertEqual(-999., dataset.variables['X']._FillValue)
del self._temp_nc_file
self.template.variables['X']['_fill_value'] = -666. # now they're different, which is an error
self.assertRaises(ValueError, self.template.to_netcdf, self.temp_nc_file)
def test_get_data_range(self):
self.assertEqual((1, 8), self.template.get_data_range('TIME'))
self.assertEqual((1, 5), self.template.get_data_range('X'))
self.assertEqual((1, 5), self.template.get_data_range('Y'))
class TestDataValues(TemplateTestCase):
def setUp(self):
super(TestDataValues, self).setUp()
self.data_array = np.array(
[-999., -999., -999., -999., -999., 1., 2., 3., 4., 5])
self.data_masked = np.ma.masked_array(
[-4, -3, -2, -1, 0, 1., 2., 3., 4., 5],
mask=[
True, True, True, True, True, False, False, False, False, False
])
self.template = DatasetTemplate(
dimensions={'TIME': 10},
variables={
'TIME': {
'_dimensions': ['TIME'],
'_datatype': 'float64',
'valid_min': 0,
'valid_max': 10,
'_data': np.array([np.nan, np.nan, 1, 2, 3, 4, 5, 6, 7, 8])
},
'X': {
'_dimensions': ['TIME'],
'_datatype': 'float32',
'valid_min': 1,
'valid_max': 5,
'_FillValue': -999,
'_data': self.data_array
},
'Y': {
'_dimensions': ['TIME'],
'_datatype': 'float32',
'valid_range': [-4, 5],
'_fill_value': -999,
'_data': self.data_masked
},
'N': {
'_dimensions': ['TIME'],
'_datatype': 'int32',
'valid_range': [-4, 5],
'_fill_value': -999,
'_data': self.data_array
}
})
def test_fill_values(self):
self.template.to_netcdf(self.temp_nc_file)
dataset = Dataset(self.temp_nc_file)
dataset.set_auto_mask(True)
for varname in ('X', 'Y'):
dsvar = dataset.variables[varname]
self.assertEqual(-999., dsvar._FillValue)
self.assertIsInstance(dsvar[:], np.ma.MaskedArray)
self.assertTrue(dsvar[:5].mask.all())
self.assertTrue((dsvar[5:] == self.data_array[5:]).all())
def test_fill_value_aliases(self):
self.template.variables['X'][
'_fill_value'] = -999. # both aliases, but equal so should still work
self.template.to_netcdf(self.temp_nc_file)
dataset = Dataset(self.temp_nc_file)
self.assertEqual(-999., dataset.variables['X']._FillValue)
del self._temp_nc_file
self.template.variables['X'][
'_fill_value'] = -666. # now they're different, which is an error
self.assertRaises(ValueError, self.template.to_netcdf,
self.temp_nc_file)
def test_get_data_range(self):
self.assertEqual((1, 8), self.template.get_data_range('TIME'))
self.assertEqual((1, 5), self.template.get_data_range('X'))
self.assertEqual((1, 5), self.template.get_data_range('Y'))
def test_var_attr_datatype_conversion(self):
"""
test to check the conversion of some attributes matches the datatype of the variable as
defined in the template
"""
self.template.to_netcdf(self.temp_nc_file)
dataset = Dataset(self.temp_nc_file)
TIME = dataset.variables['TIME']
self.assertEqual(TIME.dtype, TIME.valid_min.dtype)
self.assertEqual(TIME.dtype, TIME.valid_max.dtype)
X = dataset.variables['X']
self.assertEqual(X.dtype, X.valid_min.dtype)
self.assertEqual(X.dtype, X.valid_max.dtype)
self.assertEqual(X.dtype, X._FillValue.dtype)
for v in ['Y', 'N']:
var = dataset.variables[v]
self.assertEqual(var.dtype, var.valid_range.dtype)
self.assertEqual(var.dtype, var._FillValue.dtype)