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