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)
