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 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_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_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_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_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_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 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_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_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_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_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_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_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_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_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_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_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_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_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 test_valid_range_saved(self):
cube = tests.stock.lat_lon_cube()
cube.data = cube.data.astype("int32")
vrange = np.array([1, 2], dtype="int32")
cube.attributes["valid_range"] = vrange
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_range, vrange)
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 test_zlib(self):
cube = self._simple_cube('>f4')
with mock.patch('iris.fileformats.netcdf.netCDF4') as api:
with Saver('/dummy/path', 'NETCDF4') as saver:
saver.write(cube, zlib=True)
dataset = api.Dataset.return_value
create_var_calls = mock.call.createVariable(
'air_pressure_anomaly', np.dtype('float32'), ['dim0', 'dim1'],
fill_value=None, shuffle=True, least_significant_digit=None,
contiguous=False, zlib=True, fletcher32=False,
endian='native', complevel=4, chunksizes=None).call_list()
dataset.assert_has_calls(create_var_calls)
def test_least_significant_digit(self):
cube = Cube(np.array([1.23, 4.56, 7.89]),
standard_name='surface_temperature', long_name=None,
var_name='temp', units='K')
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, least_significant_digit=1)
cube_saved = iris.load_cube(nc_path)
self.assertEqual(
cube_saved.attributes['least_significant_digit'], 1)
self.assertFalse(np.all(cube.data == cube_saved.data))
self.assertArrayAllClose(cube.data, cube_saved.data, 0.1)
def test_custom_unlimited_dimensions(self):
cube = self._transverse_mercator_cube()
unlimited_dimensions = ['projection_y_coordinate',
'projection_x_coordinate']
# test coordinates by name
with self.temp_filename('.nc') as nc_path:
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, unlimited_dimensions=unlimited_dimensions)
ds = nc.Dataset(nc_path)
for dim in unlimited_dimensions:
self.assertTrue(ds.dimensions[dim].isunlimited())
ds.close()
# test coordinate arguments
with self.temp_filename('.nc') as nc_path:
coords = [cube.coord(dim) for dim in unlimited_dimensions]
with Saver(nc_path, 'NETCDF4') as saver:
saver.write(cube, unlimited_dimensions=coords)
ds = nc.Dataset(nc_path)
for dim in unlimited_dimensions:
self.assertTrue(ds.dimensions[dim].isunlimited())
ds.close()
