def test_masked_data__insitu(self):
# Test that the error is raised in the right place.
with self.temp_filename('.nc') as nc_path:
saver = Saver(nc_path, 'NETCDF4')
with self.assertRaisesRegexp(ValueError, self.exp_emsg):
saver._create_cf_cell_measure_variable(self.cube,
self.names_map, self.cm)
def test_masked_data__insitu(self):
# Test that the error is raised in the right place.
with self.temp_filename(".nc") as nc_path:
saver = Saver(nc_path, "NETCDF4")
with self.assertRaisesRegex(ValueError, self.exp_emsg):
saver._create_generic_cf_array_var(self.cube, self.names_map,
self.cm)
def _grid_mapping_variable(self, coord_system):
"""
Return a mock netCDF variable that represents the conversion
of the given coordinate system.
"""
cube = self._cube_with_cs(coord_system)
class NCMock(mock.Mock):
def setncattr(self, name, attr):
setattr(self, name, attr)
# Calls the actual NetCDF saver with appropriate mocking, returning
# the grid variable that gets created.
grid_variable = NCMock(name='NetCDFVariable')
create_var_fn = mock.Mock(side_effect=[grid_variable])
dataset = mock.Mock(variables=[], createVariable=create_var_fn)
saver = mock.Mock(spec=Saver, _coord_systems=[], _dataset=dataset)
variable = NCMock()
# This is the method we're actually testing!
Saver._create_cf_grid_mapping(saver, cube, variable)
self.assertEqual(create_var_fn.call_count, 1)
self.assertEqual(variable.grid_mapping,
grid_variable.grid_mapping_name)
return grid_variable
def _grid_mapping_variable(self, coord_system):
"""
Return a mock netCDF variable that represents the conversion
of the given coordinate system.
"""
cube = self._cube_with_cs(coord_system)
class NCMock(mock.Mock):
def setncattr(self, name, attr):
setattr(self, name, attr)
# Calls the actual NetCDF saver with appropriate mocking, returning
# the grid variable that gets created.
grid_variable = NCMock(name='NetCDFVariable')
create_var_fn = mock.Mock(side_effect=[grid_variable])
dataset = mock.Mock(variables=[],
createVariable=create_var_fn)
saver = mock.Mock(spec=Saver, _coord_systems=[],
_dataset=dataset)
variable = NCMock()
# This is the method we're actually testing!
Saver._create_cf_grid_mapping(saver, cube, variable)
self.assertEqual(create_var_fn.call_count, 1)
self.assertEqual(variable.grid_mapping,
grid_variable.grid_mapping_name)
return grid_variable
def test_masked_data__insitu(self):
# Test that the error is raised in the right place.
with self.temp_filename('.nc') as nc_path:
saver = Saver(nc_path, 'NETCDF4')
with self.assertRaisesRegexp(ValueError, self.exp_emsg):
saver._create_cf_cell_measure_variable(self.cube,
self.names_map,
self.cm)
def construct_cf_grid_mapping_variable(self, cube):
# Calls the actual NetCDF saver with appropriate mocking, returning
# the grid variable that gets created.
grid_variable = mock.Mock(name='NetCDFVariable')
create_var_fn = mock.Mock(side_effect=[grid_variable])
dataset = mock.Mock(variables=[], createVariable=create_var_fn)
saver = mock.Mock(spec=Saver, _coord_systems=[], _dataset=dataset)
variable = mock.Mock()
Saver._create_cf_grid_mapping(saver, cube, variable)
self.assertEqual(create_var_fn.call_count, 1)
self.assertEqual(variable.grid_mapping,
grid_variable.grid_mapping_name)
return grid_variable
def construct_cf_grid_mapping_variable(self, cube):
# Calls the actual NetCDF saver with appropriate mocking, returning
# the grid variable that gets created.
grid_variable = mock.Mock(name='NetCDFVariable')
create_var_fn = mock.Mock(side_effect=[grid_variable])
dataset = mock.Mock(variables=[],
createVariable=create_var_fn)
saver = mock.Mock(spec=Saver, _coord_systems=[],
_dataset=dataset)
variable = mock.Mock()
Saver._create_cf_grid_mapping(saver, cube, variable)
self.assertEqual(create_var_fn.call_count, 1)
self.assertEqual(variable.grid_mapping,
grid_variable.grid_mapping_name)
return grid_variable
def check_call(self, coord_name, coord_system, units, expected_units):
coord = iris.coords.DimCoord([30, 45],
coord_name,
units=units,
coord_system=coord_system)
result = Saver._cf_coord_standardised_units(coord)
self.assertEqual(result, expected_units)
def test_mercator_no_ellipsoid(self):
# Create a Cube with a Mercator coordinate system.
cube = self._mercator_cube()
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path)
def test_transverse_mercator_no_ellipsoid(self):
# Create a Cube with a transverse Mercator coordinate system.
cube = self._transverse_mercator_cube()
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube)
self.assertCDL(nc_path)
def test_big_endian(self):
# Create a Cube with big-endian data.
cube = self._simple_cube('>f4')
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path, basename='endian', flags='')
def test_stereographic_no_ellipsoid(self):
# Create a Cube with a stereographic coordinate system.
cube = self._stereo_cube()
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path)
def test_stereographic(self):
# Create a Cube with a stereographic coordinate system.
ellipsoid = GeogCS(6377563.396, 6356256.909)
cube = self._stereo_cube(ellipsoid)
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path)
def test_big_endian(self):
# Create a Cube with big-endian data.
cube = self._simple_cube(">f4")
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube)
result_path = self.result_path("endian", "cdl")
self.assertCDL(nc_path, result_path, flags="")
def test_big_endian(self):
# Create a Cube with big-endian data.
cube = self._simple_cube('>f4')
with self.temp_filename('nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path, ('unit', 'fileformats', 'netcdf', 'Saver',
'write', 'endian.cdl'), flags='')
def test_transverse_mercator(self):
# Create a Cube with a transverse Mercator coordinate system.
ellipsoid = GeogCS(6377563.396, 6356256.909)
cube = self._transverse_mercator_cube(ellipsoid)
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path)
def test_little_endian(self):
# Create a Cube with little-endian data.
cube = self._simple_cube('<f4')
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
result_path = self.result_path('endian', 'cdl')
self.assertCDL(nc_path, result_path, flags='')
def _check_bounds_setting(self, climatological=False):
# Generic test that can run with or without a climatological coord.
cube = stock.climatology_3d()
coord = cube.coord("time").copy()
# Over-write original value from stock.climatology_3d with test value.
coord.climatological = climatological
# Set up expected strings.
if climatological:
property_name = "climatology"
varname_extra = "climatology"
else:
property_name = "bounds"
varname_extra = "bnds"
boundsvar_name = "time_" + varname_extra
# Set up arguments for testing _create_cf_bounds.
saver = mock.MagicMock(spec=Saver)
# NOTE: 'saver' must have spec=Saver to fake isinstance(save, Saver),
# so it can pass as 'self' in the call to _create_cf_cbounds.
# Mock a '_dataset' property; not automatic because 'spec=Saver'.
saver._dataset = mock.MagicMock()
# Mock the '_ensure_valid_dtype' method to return an object with a
# suitable 'shape' and 'dtype'.
saver._ensure_valid_dtype.return_value = mock.Mock(
shape=coord.bounds.shape, dtype=coord.bounds.dtype
)
var = mock.MagicMock(spec=nc.Variable)
# Make the main call.
Saver._create_cf_bounds(saver, coord, var, "time")
# Test the call of _setncattr in _create_cf_bounds.
setncattr_call = mock.call(
property_name, boundsvar_name.encode(encoding="ascii")
)
self.assertEqual(setncattr_call, var.setncattr.call_args)
# Test the call of createVariable in _create_cf_bounds.
dataset = saver._dataset
expected_dimensions = var.dimensions + ("bnds",)
create_var_call = mock.call(
boundsvar_name, coord.bounds.dtype, expected_dimensions
)
self.assertEqual(create_var_call, dataset.createVariable.call_args)
def test_no_unlimited_dimensions(self):
cube = self._simple_cube(">f4")
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube, unlimited_dimensions=None)
ds = nc.Dataset(nc_path)
for dim in ds.dimensions.values():
self.assertFalse(dim.isunlimited())
ds.close()
def test_lazy_preserved_save(self):
fpath = tests.get_data_path(
('NetCDF', 'label_and_climate', 'small_FC_167_mon_19601101.nc'))
acube = iris.load_cube(fpath)
self.assertTrue(acube.has_lazy_data())
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(acube)
self.assertTrue(acube.has_lazy_data())
def test_no_unlimited_dimensions(self):
cube = self._simple_cube('>f4')
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, unlimited_dimensions=None)
ds = nc.Dataset(nc_path)
for dim in six.itervalues(ds.dimensions):
self.assertFalse(dim.isunlimited())
ds.close()
def test_lazy_preserved_save(self):
fpath = tests.get_data_path(
("NetCDF", "label_and_climate", "small_FC_167_mon_19601101.nc"))
acube = iris.load_cube(fpath, "air_temperature")
self.assertTrue(acube.has_lazy_data())
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(acube)
self.assertTrue(acube.has_lazy_data())
def test_transverse_mercator_no_ellipsoid(self):
# Create a Cube with a transverse Mercator coordinate system.
cube = self._transverse_mercator_cube()
with self.temp_filename('nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
self.assertCDL(nc_path, ('unit', 'fileformats', 'netcdf', 'Saver',
'write',
'transverse_mercator_no_ellipsoid.cdl'))
def test_default_unlimited_dimensions(self):
cube = self._simple_cube('>f4')
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
ds = nc.Dataset(nc_path)
self.assertTrue(ds.dimensions['dim0'].isunlimited())
self.assertFalse(ds.dimensions['dim1'].isunlimited())
ds.close()
def test_valid_range_and_valid_min_valid_max_provided(self):
# Conflicting attributes should raise a suitable exception.
self.data = self.data.astype('int8')
self.container.attributes['valid_range'] = [1, 2]
self.container.attributes['valid_min'] = [1]
msg = 'Both "valid_range" and "valid_min"'
with Saver(mock.Mock(), 'NETCDF4') as saver:
with self.assertRaisesRegexp(ValueError, msg):
saver.check_attribute_compliance(self.container, self.data)
def test_reserved_attributes(self):
cube = self._simple_cube('>f4')
cube.attributes['dimensions'] = 'something something_else'
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube)
ds = nc.Dataset(nc_path)
res = ds.getncattr('dimensions')
ds.close()
self.assertEqual(res, 'something something_else')
def test_default_unlimited_dimensions(self):
# Default is no unlimited dimensions.
cube = self._simple_cube(">f4")
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube)
ds = nc.Dataset(nc_path)
self.assertFalse(ds.dimensions["dim0"].isunlimited())
self.assertFalse(ds.dimensions["dim1"].isunlimited())
ds.close()
def test_reserved_attributes(self):
cube = self._simple_cube(">f4")
cube.attributes["dimensions"] = "something something_else"
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube)
ds = nc.Dataset(nc_path)
res = ds.getncattr("dimensions")
ds.close()
self.assertEqual(res, "something something_else")
def test_valid_range_and_valid_min_valid_max_provided(self):
# Conflicting attributes should raise a suitable exception.
self.data_dtype = np.dtype("int8")
self.container.attributes["valid_range"] = [1, 2]
self.container.attributes["valid_min"] = [1]
msg = 'Both "valid_range" and "valid_min"'
with Saver(mock.Mock(), "NETCDF4") as saver:
with self.assertRaisesRegex(ValueError, msg):
saver.check_attribute_compliance(self.container,
self.data_dtype)
def test_valid_max_saved(self):
cube = tests.stock.lat_lon_cube()
cube.data = cube.data.astype("int32")
cube.coord(axis="x").attributes["valid_max"] = 2
with self.temp_filename(".nc") as nc_path:
with Saver(nc_path, "NETCDF4") as saver:
saver.write(cube, unlimited_dimensions=[])
ds = nc.Dataset(nc_path)
self.assertArrayEqual(ds.variables["longitude"].valid_max, 2)
ds.close()
def test_valid_min_saved(self):
cube = tests.stock.lat_lon_cube()
cube.data = cube.data.astype('int32')
cube.attributes['valid_min'] = 1
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, unlimited_dimensions=[])
ds = nc.Dataset(nc_path)
self.assertArrayEqual(ds.valid_min, 1)
ds.close()
def test_valid_max_saved(self):
cube = tests.stock.lat_lon_cube()
cube.data = cube.data.astype('int32')
cube.coord(axis='x').attributes['valid_max'] = 2
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, unlimited_dimensions=[])
ds = nc.Dataset(nc_path)
self.assertArrayEqual(ds.variables['longitude'].valid_max, 2)
ds.close()
def _netCDF_var(self, cube, **kwargs):
# Get the netCDF4 Variable for a cube from a temp file
standard_name = cube.standard_name
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, **kwargs)
ds = nc.Dataset(nc_path)
var, = [
var for var in ds.variables.values()
if var.standard_name == standard_name
]
yield var
def check_call(self, coord_name, coord_system, units, expected_units):
coord = iris.coords.DimCoord([30, 45], coord_name, units=units,
coord_system=coord_system)
result = Saver._cf_coord_identity(coord)
self.assertEqual(result, (coord.standard_name, coord.long_name,
expected_units))
def test_no_hyphen(self):
# CF explicitly prohibits hyphen, even though it is fine in NetCDF.
self.assertEqual(Saver.cf_valid_var_name('valid-netcdf'),
'valid_netcdf')
def test_no_replacement(self):
self.assertEqual(Saver.cf_valid_var_name('valid_Nam3'),
'valid_Nam3')
def test_leading_invalid(self):
self.assertEqual(Saver.cf_valid_var_name('?invalid'),
'var__invalid')
def test_special_chars(self):
self.assertEqual(Saver.cf_valid_var_name('inv?alid'),
'inv_alid')
def test_leading_underscore(self):
self.assertEqual(Saver.cf_valid_var_name('_invalid'),
'var__invalid')
def test_leading_number(self):
self.assertEqual(Saver.cf_valid_var_name('2invalid'),
'var_2invalid')
