def test_no_unlimited_future_default(self):
cube = lat_lon_cube()
with iris.FUTURE.context(netcdf_no_unlimited=True):
with self.temp_filename('foo.nc') as nc_out:
save(cube, nc_out)
ds = nc.Dataset(nc_out)
self.assertFalse(ds.dimensions['latitude'].isunlimited())
def test_unlimited_dim_latitude(self):
cube = lat_lon_cube()
unlim_dim_name = 'latitude'
with self.temp_filename('foo.nc') as nc_out:
save(cube, nc_out, unlimited_dimensions=[unlim_dim_name])
ds = nc.Dataset(nc_out)
self.assertTrue(ds.dimensions[unlim_dim_name].isunlimited())
def test_no_unlimited_default(self):
cube = lat_lon_cube()
with iris.FUTURE.context(netcdf_no_unlimited=False):
with self.temp_filename("foo.nc") as nc_out:
save(cube, nc_out)
ds = nc.Dataset(nc_out)
self.assertTrue(ds.dimensions["latitude"].isunlimited())
def test_unlimited_dim_latitude(self):
cube = lat_lon_cube()
unlim_dim_name = 'latitude'
with self.temp_filename('foo.nc') as nc_out:
save(cube, nc_out, unlimited_dimensions=[unlim_dim_name])
ds = nc.Dataset(nc_out)
self.assertTrue(ds.dimensions[unlim_dim_name].isunlimited())
def test_multi_wrong_length(self):
# Test that when a list of a different length to the number of cubes
# is passed as the fill_value argument, an error is raised
cubes = self._make_cubes()
fill_values = [1., 2., 3., 4.]
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
with self.assertRaises(ValueError):
save(cubes, 'dummy.nc', fill_value=fill_values)
def test_multi_wrong_length(self):
# Test that when a list of a different length to the number of cubes
# is passed as the fill_value argument, an error is raised
cubes = self._make_cubes()
fill_values = [1., 2., 3., 4.]
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
with self.assertRaises(ValueError):
save(cubes, 'dummy.nc', fill_value=fill_values)
def test_custom_conventions__ignored(self):
# Ensure that we drop existing conventions attributes and replace with
# CF convention.
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, CF_CONVENTIONS_VERSION)
def test_custom_conventions__ignored(self):
# Ensure that we drop existing conventions attributes and replace with
# CF convention.
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, CF_CONVENTIONS_VERSION)
def test_custom_conventions__allowed(self):
# Ensure that existing conventions attributes are passed through if the
# relevant Iris option is set.
with mock.patch.object(self.options, 'conventions_override', True):
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, self.custom_conventions)
def test_custom_conventions__allowed(self):
# Ensure that existing conventions attributes are passed through if the
# relevant Iris option is set.
with mock.patch.object(self.options, 'conventions_override', True):
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, self.custom_conventions)
def test_custom_conventions__allowed__missing(self):
# Ensure the default conventions attribute is set if the relevant Iris
# option is set but there is no custom conventions attribute.
del self.cube.attributes['Conventions']
with mock.patch.object(self.options, 'conventions_override', True):
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, CF_CONVENTIONS_VERSION)
def test_custom_conventions__allowed__missing(self):
# Ensure the default conventions attribute is set if the relevant Iris
# option is set but there is no custom conventions attribute.
del self.cube.attributes['Conventions']
with mock.patch.object(self.options, 'conventions_override', True):
with self.temp_filename('.nc') as nc_path:
save(self.cube, nc_path, 'NETCDF4')
ds = nc.Dataset(nc_path)
res = ds.getncattr('Conventions')
ds.close()
self.assertEqual(res, CF_CONVENTIONS_VERSION)
def test_custom_conventions(self):
# Ensure that we drop existing conventions attributes and replace with
# CF convention.
cube = Cube([0])
cube.attributes["Conventions"] = "convention1 convention2"
with self.temp_filename(".nc") as nc_path:
save(cube, nc_path, "NETCDF4")
ds = nc.Dataset(nc_path)
res = ds.getncattr("Conventions")
ds.close()
self.assertEqual(res, CF_CONVENTIONS_VERSION)
def test_attributes_arrays(self):
# Ensure that attributes containing NumPy arrays can be equality
# checked and their cubes saved as appropriate.
c1 = Cube([1], attributes={'bar': np.arange(2)})
c2 = Cube([2], attributes={'bar': np.arange(2)})
with self.temp_filename('foo.nc') as nc_out:
save([c1, c2], nc_out)
ds = nc.Dataset(nc_out)
res = ds.getncattr('bar')
ds.close()
self.assertArrayEqual(res, np.arange(2))
def test_attributes_arrays(self):
# Ensure that attributes containing NumPy arrays can be equality
# checked and their cubes saved as appropriate.
c1 = Cube([1], attributes={'bar': np.arange(2)})
c2 = Cube([2], attributes={'bar': np.arange(2)})
with self.temp_filename('foo.nc') as nc_out:
save([c1, c2], nc_out)
ds = nc.Dataset(nc_out)
res = ds.getncattr('bar')
ds.close()
self.assertArrayEqual(res, np.arange(2))
def test_single_string(self):
# Test that when a string is passed as the fill_value argument,
# that value is passed to calls to Saver.write
cube = Cube(["abc", "def", "hij"])
fill_value = "xyz"
with mock.patch("iris.fileformats.netcdf.Saver") as Saver:
save(cube, "dummy.nc", fill_value=fill_value)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(1, write.call_count)
_, _, kwargs = write.mock_calls[0]
self.assertEqual(fill_value, kwargs["fill_value"])
def test_single_string(self):
# Test that when a string is passed as the fill_value argument,
# that value is passed to calls to Saver.write
cube = Cube(['abc', 'def', 'hij'])
fill_value = 'xyz'
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cube, 'dummy.nc', fill_value=fill_value)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(1, write.call_count)
_, _, kwargs = write.mock_calls[0]
self.assertEqual(fill_value, kwargs['fill_value'])
def test_single_string(self):
# Test that when a string is passed as the fill_value argument,
# that value is passed to calls to Saver.write
cube = Cube(['abc', 'def', 'hij'])
fill_value = 'xyz'
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cube, 'dummy.nc', fill_value=fill_value)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(1, write.call_count)
_, _, kwargs = write.mock_calls[0]
self.assertEqual(fill_value, kwargs['fill_value'])
def test_None(self):
# Test that when no fill_value argument is passed, the fill_value
# argument to Saver.write is None or not present.
cubes = self._make_cubes()
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc')
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call in write.mock_calls:
_, _, kwargs = call
if 'fill_value' in kwargs:
self.assertIs(None, kwargs['fill_value'])
def test_multiple(self):
# Test that when a list is passed as the fill_value argument,
# each element is passed to separate calls to Saver.write
cubes = self._make_cubes()
fill_values = [123., 456., 789.]
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc', fill_value=fill_values)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call, fill_value in zip(write.mock_calls, fill_values):
_, _, kwargs = call
self.assertEqual(fill_value, kwargs['fill_value'])
def test_single(self):
# Test that when a single value is passed as the fill_value argument,
# that value is passed to each call to Saver.write
cubes = self._make_cubes()
fill_value = 12345.
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc', fill_value=fill_value)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call in write.mock_calls:
_, _, kwargs = call
self.assertEqual(fill_value, kwargs['fill_value'])
def test_None(self):
# Test that when no fill_value argument is passed, the fill_value
# argument to Saver.write is None or not present.
cubes = self._make_cubes()
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc')
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call in write.mock_calls:
_, _, kwargs = call
if 'fill_value' in kwargs:
self.assertIs(None, kwargs['fill_value'])
def test_single(self):
# Test that when a single value is passed as the fill_value argument,
# that value is passed to each call to Saver.write
cubes = self._make_cubes()
fill_value = 12345.
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc', fill_value=fill_value)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call in write.mock_calls:
_, _, kwargs = call
self.assertEqual(fill_value, kwargs['fill_value'])
def test_multiple(self):
# Test that when a list is passed as the fill_value argument,
# each element is passed to separate calls to Saver.write
cubes = self._make_cubes()
fill_values = [123., 456., 789.]
with mock.patch('iris.fileformats.netcdf.Saver') as Saver:
save(cubes, 'dummy.nc', fill_value=fill_values)
# Get the Saver.write mock
with Saver() as saver:
write = saver.write
self.assertEqual(3, write.call_count)
for call, fill_value in zip(write.mock_calls, fill_values):
_, _, kwargs = call
self.assertEqual(fill_value, kwargs['fill_value'])
def test_no_special_attribute_clash(self):
# Ensure that saving multiple cubes with netCDF4 protected attributes
# works as expected.
# Note that here we are testing variable attribute clashes only - by
# saving multiple cubes the attributes are saved as variable
# attributes rather than global attributes.
c1 = Cube([0], var_name='test', attributes={'name': 'bar'})
c2 = Cube([0], var_name='test_1', attributes={'name': 'bar_1'})
with self.temp_filename('foo.nc') as nc_out:
save([c1, c2], nc_out)
ds = nc.Dataset(nc_out)
res = ds.variables['test'].getncattr('name')
res_1 = ds.variables['test_1'].getncattr('name')
ds.close()
self.assertEqual(res, 'bar')
self.assertEqual(res_1, 'bar_1')
def test_no_special_attribute_clash(self):
# Ensure that saving multiple cubes with netCDF4 protected attributes
# works as expected.
# Note that here we are testing variable attribute clashes only - by
# saving multiple cubes the attributes are saved as variable
# attributes rather than global attributes.
c1 = Cube([0], var_name="test", attributes={"name": "bar"})
c2 = Cube([0], var_name="test_1", attributes={"name": "bar_1"})
with self.temp_filename("foo.nc") as nc_out:
save([c1, c2], nc_out)
ds = nc.Dataset(nc_out)
res = ds.variables["test"].getncattr("name")
res_1 = ds.variables["test_1"].getncattr("name")
ds.close()
self.assertEqual(res, "bar")
self.assertEqual(res_1, "bar_1")
def test_no_special_attribute_clash(self):
# Ensure that saving multiple cubes with netCDF4 protected attributes
# works as expected.
# Note that here we are testing variable attribute clashes only - by
# saving multiple cubes the attributes are saved as variable
# attributes rather than global attributes.
c1 = Cube([0], var_name='test', attributes={'name': 'bar'})
c2 = Cube([0], var_name='test_1', attributes={'name': 'bar_1'})
with self.temp_filename('foo.nc') as nc_out:
save([c1, c2], nc_out)
ds = nc.Dataset(nc_out)
res = ds.variables['test'].getncattr('name')
res_1 = ds.variables['test_1'].getncattr('name')
ds.close()
self.assertEqual(res, 'bar')
self.assertEqual(res_1, 'bar_1')
def test_no_unlimited_dims(self):
cube = lat_lon_cube()
with self.temp_filename('foo.nc') as nc_out:
save(cube, nc_out)
ds = nc.Dataset(nc_out)
self.assertFalse(ds.dimensions['latitude'].isunlimited())
def test_no_unlimited_dims(self):
cube = lat_lon_cube()
with self.temp_filename('foo.nc') as nc_out:
save(cube, nc_out)
ds = nc.Dataset(nc_out)
self.assertFalse(ds.dimensions['latitude'].isunlimited())