def test_basic(self):
"""Test function returns a cube with expected metadata"""
halo_size_km = 162.
result = create_cube_with_halo(self.cube, 1000. * halo_size_km)
self.assertIsInstance(result, iris.cube.Cube)
self.assertEqual(result.name(), 'grid_with_halo')
self.assertFalse(result.attributes)
def test_values(self):
"""Test coordinate values with standard halo radius (rounds down to 1
grid cell)"""
halo_size_km = 162.
x_min = self.cube.coord(axis='x').points[0] - self.grid_spacing
x_max = self.cube.coord(axis='x').points[-1] + self.grid_spacing
expected_x_points = np.arange(x_min, x_max + 1, self.grid_spacing)
y_min = self.cube.coord(axis='y').points[0] - self.grid_spacing
y_max = self.cube.coord(axis='y').points[-1] + self.grid_spacing
expected_y_points = np.arange(y_min, y_max + 1, self.grid_spacing)
result = create_cube_with_halo(self.cube, 1000. * halo_size_km)
self.assertSequenceEqual(result.data.shape, (13, 13))
self.assertArrayAlmostEqual(
result.coord(axis='x').points, expected_x_points)
self.assertArrayAlmostEqual(
result.coord(axis='y').points, expected_y_points)
# check explicitly that the original grid remains an exact subset of
# the output cube (ie that padding hasn't shifted the existing grid)
self.assertArrayAlmostEqual(
result.coord(axis='x').points[1:-1],
self.cube.coord(axis='x').points)
self.assertArrayAlmostEqual(
result.coord(axis='y').points[1:-1],
self.cube.coord(axis='y').points)
def process(cube, halo_radius=162000.0):
"""Generate a zeroed grid with halo from a source cube.
Create a template cube defining a new grid by adding a fixed width halo on
all sides to the input cube grid. The cube contains no meaningful data.
Args:
cube (iris.cube.Cube):
The cube to be processed.
halo_radius (float):
Radius in metres of which to pad the input grid.
Default is 162,000
Returns:
result (iris.cube.Cube):
The processed Cube defining the halo-padded grid (data set to 0)
"""
result = create_cube_with_halo(cube, halo_radius)
return result
def process(cube: cli.inputcube, *, halo_radius: float = 162000.0):
"""Generate a zeroed grid with halo from a source cube.
Create a template cube defining a new grid by adding a fixed width halo on
all sides to the input cube grid. The cube contains no meaningful data.
Args:
cube (iris.cube.Cube):
Contains data on the source grid.
halo_radius (float):
Radius in metres of which to pad the input grid.
Returns:
iris.cube.Cube:
The processed cube defining the halo-padded grid (data set to 0)
"""
from improver.utilities.pad_spatial import create_cube_with_halo
result = create_cube_with_halo(cube, halo_radius)
return result
def main(argv=None):
"""Generate target grid with a halo around the source file grid."""
parser = ArgParser(description='Generate grid with halo from a source '
'domain input file. The grid is populated with zeroes.')
parser.add_argument('input_file',
metavar='INPUT_FILE',
help="NetCDF file "
"containing data on a source grid.")
parser.add_argument('output_file',
metavar='OUTPUT_FILE',
help="NetCDF "
"file defining the target grid with additional halo.")
parser.add_argument('--halo_radius',
metavar='HALO_RADIUS',
default=162000,
type=float,
help="Size of halo (in m) with which to "
"pad the input grid. Default is 162 000 m.")
args = parser.parse_args(args=argv)
cube = load_cube(args.input_file)
halo_cube = create_cube_with_halo(cube, args.halo_radius)
save_netcdf(halo_cube, args.output_file)