def test_cube_var_name_is_none(self):
"""
Test that the utility returns an iris.cube.Cube with a
var_name of None.
"""
result = strip_var_names(self.cube)
self.assertIsNone(result[0].var_name, None)
def test_cubelist(self):
"""Test that the utility returns an iris.cube.CubeList."""
cubes = iris.cube.CubeList([self.cube, self.cube])
result = strip_var_names(cubes)
self.assertIsInstance(result, iris.cube.CubeList)
for cube in result:
for coord in cube.coords():
self.assertIsNone(coord.var_name, None)
def test_cube_coord_var_name_is_none(self):
"""
Test that the coordinates have var_names of None.
"""
self.cube.coord("time").var_name = "time"
self.cube.coord("latitude").var_name = "latitude"
self.cube.coord("longitude").var_name = "longitude"
result = strip_var_names(self.cube)
for cube in result:
for coord in cube.coords():
self.assertIsNone(coord.var_name, None)
def test_cubelist(self):
"""Test that the utility returns an iris.cube.CubeList."""
cube1 = self.cube
cube2 = self.cube
cubes = iris.cube.CubeList([cube1, cube2])
self.cube.var_name = "air_temperature"
result = strip_var_names(cubes)
self.assertIsInstance(result, iris.cube.CubeList)
for cube in result:
for coord in cube.coords():
self.assertIsNone(coord.var_name, None)
def test_basic(self):
"""Test that the utility returns an iris.cube.CubeList."""
result = strip_var_names(self.cube)
self.assertIsInstance(result, iris.cube.CubeList)
def load_cubelist(
filepath: Union[str, List[str]],
constraints: Optional[Union[Constraint, str]] = None,
no_lazy_load: bool = False,
) -> CubeList:
"""Load cubes from filepath(s) into a cubelist. Strips off all
var names except for "threshold"-type coordinates, where this is different
from the standard or long name.
Args:
filepath:
Filepath(s) that will be loaded.
constraints:
Constraint to be applied when loading from the input filepath.
This can be in the form of an iris.Constraint or could be a string
that is intended to match the name of the cube.
The default is None.
no_lazy_load:
If True, bypass cube deferred (lazy) loading and load the whole
cube into memory. This can increase performance at the cost of
memory. If False (default) then lazy load.
Returns:
CubeList that has been created from the input filepath given the
constraints provided.
"""
# Remove legacy metadata prefix cube if present
constraints = (
iris.Constraint(cube_func=lambda cube: cube.long_name != "prefixes")
& constraints)
# Load each file individually to avoid partial merging (not used
# iris.load_raw() due to issues with time representation)
if isinstance(filepath, str):
cubes = iris.load(filepath, constraints=constraints)
else:
cubes = iris.cube.CubeList([])
for item in filepath:
cubes.extend(iris.load(item, constraints=constraints))
if not cubes:
message = "No cubes found using constraints {}".format(constraints)
raise ValueError(message)
# Remove var_name from cubes and coordinates (except where needed to
# describe probabilistic data)
cubes = strip_var_names(cubes)
for cube in cubes:
# Remove metadata attributes pointing to legacy prefix cube
cube.attributes.pop("bald__isPrefixedBy", None)
# Ensure the probabilistic coordinates are the first coordinates within
# a cube and are in the specified order.
enforce_coordinate_ordering(cube,
["realization", "percentile", "threshold"])
# Ensure the y and x dimensions are the last within the cube.
y_name = cube.coord(axis="y").name()
x_name = cube.coord(axis="x").name()
enforce_coordinate_ordering(cube, [y_name, x_name], anchor_start=False)
if no_lazy_load:
# Force cube's data into memory by touching the .data attribute.
cube.data
return cubes
